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Zhang Y, Shi K, Feng Y, Wang XB. Machine learning model using immune indicators to predict outcomes in early liver cancer. World J Gastroenterol 2025; 31:101722. [PMID: 39926221 PMCID: PMC11718606 DOI: 10.3748/wjg.v31.i5.101722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2024] [Revised: 11/15/2024] [Accepted: 12/09/2024] [Indexed: 12/30/2024] Open
Abstract
BACKGROUND Patients with early-stage hepatocellular carcinoma (HCC) generally have good survival rates following surgical resection. However, a subset of these patients experience recurrence within five years post-surgery. AIM To develop predictive models utilizing machine learning (ML) methods to detect early-stage patients at a high risk of mortality. METHODS Eight hundred and eight patients with HCC at Beijing Ditan Hospital were randomly allocated to training and validation cohorts in a 2:1 ratio. Prognostic models were generated using random survival forests and artificial neural networks (ANNs). These ML models were compared with other classic HCC scoring systems. A decision-tree model was established to validate the contribution of immune-inflammatory indicators to the long-term outlook of patients with early-stage HCC. RESULTS Immune-inflammatory markers, albumin-bilirubin scores, alpha-fetoprotein, tumor size, and International Normalized Ratio were closely associated with the 5-year survival rates. Among various predictive models, the ANN model generated using these indicators through ML algorithms exhibited superior performance, with a 5-year area under the curve (AUC) of 0.85 (95%CI: 0.82-0.88). In the validation cohort, the 5-year AUC was 0.82 (95%CI: 0.74-0.85). According to the ANN model, patients were classified into high-risk and low-risk groups, with an overall survival hazard ratio of 7.98 (95%CI: 5.85-10.93, P < 0.0001) between the two cohorts. CONCLUSION A non-invasive, cost-effective ML-based model was developed to assist clinicians in identifying high-risk early-stage HCC patients with poor postoperative prognosis following surgical resection.
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MESH Headings
- Humans
- Liver Neoplasms/mortality
- Liver Neoplasms/immunology
- Liver Neoplasms/surgery
- Liver Neoplasms/pathology
- Liver Neoplasms/blood
- Liver Neoplasms/diagnosis
- Carcinoma, Hepatocellular/mortality
- Carcinoma, Hepatocellular/immunology
- Carcinoma, Hepatocellular/surgery
- Carcinoma, Hepatocellular/pathology
- Carcinoma, Hepatocellular/blood
- Carcinoma, Hepatocellular/diagnosis
- Machine Learning
- Male
- Female
- Middle Aged
- Prognosis
- Neural Networks, Computer
- Aged
- Neoplasm Recurrence, Local/immunology
- Neoplasm Recurrence, Local/epidemiology
- Neoplasm Recurrence, Local/prevention & control
- Biomarkers, Tumor/blood
- Neoplasm Staging
- Risk Assessment/methods
- Decision Trees
- Hepatectomy
- Predictive Value of Tests
- Risk Factors
- Survival Rate
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Affiliation(s)
- Yi Zhang
- Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
| | - Ke Shi
- Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
| | - Ying Feng
- Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
| | - Xian-Bo Wang
- Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
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Gao JW, Guo Q, Weng Y, Huang ZG, Zhang HF, Wu YB, Wang JF, Zhang SL, Liu PM. Predicting the risk of coronary artery calcium progression in the general population: insights from the MESA and CARDIA studies. Clin Radiol 2025; 80:106724. [PMID: 39546957 DOI: 10.1016/j.crad.2024.10.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Revised: 09/03/2024] [Accepted: 10/10/2024] [Indexed: 11/17/2024]
Abstract
AIM Coronary artery calcium (CAC) progression is a strong predictor of cardiovascular disease. This study aims to develop and validate a practical tool for predicting individual CAC progression in the general population. MATERIALS AND METHODS Data were utilized from the Multi-Ethnic Study of Atherosclerosis (MESA) cohort, comprising 5486 participants (47.3% male, mean ± SD age: 61.9 ± 10.2 years), who were randomly assigned to either a training set or an internal validation set at a 7:3 ratio. Additionally, a separate cohort of 2447 participants (44.6% male, mean ± SD age: 40.4 ± 3.5 years) from the Coronary Artery Risk Development in Young Adults (CARDIA) study served as the external validation set. A nomogram was developed based on a Cox regression model incorporating 10 variables selected by the least absolute shrinkage and selection operator (LASSO) method to predict CAC progression. RESULTS From the 61 features considered, 10 key variables were identified: age, male sex, smoking status, waist circumference, systolic blood pressure, fasting glucose, lipid abnormalities, and the use of antihypertensive, glucose-lowering, and lipid-lowering medications. The nomogram demonstrated good discrimination with a C-statistic of 0.682 (95% confidence interval [CI], 0.665-0.699) in the training set and 0.750 (95% CI, 0.729-0.771) in the external validation set. Decision curve analysis further confirmed the nomogram's clinical utility in predicting the risk of CAC progression. CONCLUSION Our nomogram offers a practical tool for individualized prediction of CAC progression potentially aiding in the primary prevention of cardiovascular disease in clinical practice. REGISTRATION URL: https://www. CLINICALTRIALS gov; Unique identifier: NCT00005130 (CARDIA), NCT00005487 (MESA).
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Affiliation(s)
- J-W Gao
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
| | - Q Guo
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
| | - Y Weng
- Department of Endocrinology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
| | - Z-G Huang
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
| | - H-F Zhang
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
| | - Y-B Wu
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
| | - J-F Wang
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
| | - S-L Zhang
- Department of Endocrinology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China.
| | - P-M Liu
- Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China.
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Jing Y, Ren M, Li X, Sun X, Xiao Y, Xue J, Liu Z. The Effect of Systemic Immune-Inflammatory Index (SII) and Prognostic Nutritional Index (PNI) in Early Gastric Cancer. J Inflamm Res 2024; 17:10273-10287. [PMID: 39654858 PMCID: PMC11625636 DOI: 10.2147/jir.s499094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2024] [Accepted: 11/26/2024] [Indexed: 12/12/2024] Open
Abstract
Background In recent years, the systemic immune-inflammatory index (SII) and prognostic nutritional index (PNI) have been considered potential predictors of survival outcomes in various solid tumors, including gastric cancer. However, there is a notable lack of research focusing on their prognostic implications specifically in the early stage of gastric cancer. This study aims to investigate the prognostic indicators of early gastric cancer (EGC), including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), SII, PNI, and lymph node metastasis (LNM). Methods In this retrospective analysis, we examined 490 patients diagnosed with EGC (pT1Nx). The peripheral blood indices of interest were SII, PNI, PLR, and NLR. The receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) were used to determine optimal cutoff values and prognostic efficacy for each parameter. Additionally, Kaplan-Meier survival curves and multivariate Cox regression models were utilized to delineate independent prognostic factors. Results The optimal cutoff values for SII and PNI were determined as 613.05 and 42.21, respectively. Patients in the low SII (SII-L) group demonstrated significantly higher 5-year Disease-Free Survival (DFS) and Overall Survival (OS) rates of 94.7% and 96.2%, compared to the high SII (SII-H) group (DFS: 78.7%; OS: 81.9%), with both differences proving statistically significant (P < 0.001, P < 0.001). Similarly, patients in the high PNI (PNI-H) group showed superior 5-year DFS (93.3%) and OS rates (95.1%) versus the low PNI (PNI-L) group (DFS: 71.4%; OS: 74.3%), also demonstrating statistical significance (P < 0.001, P < 0.001). Multivariate analysis identified SII, PNI, and LNM as independent prognostic factors for EGC. A combined analysis of SII, PNI, and LNM yielded a C-index of 0.723 (P = 0.008). Conclusion SII, PNI, and LNM are effective markers for predicting the survival outcomes of patients undergoing radical gastrectomy for EGC.
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Affiliation(s)
- Yaoyao Jing
- Center for GI Cancer Diagnosis and Treatment, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, People’s Republic of China
| | - Minghan Ren
- Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, People’s Republic of China
| | - Xiaoxiao Li
- Center for GI Cancer Diagnosis and Treatment, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, People’s Republic of China
| | - Xiaoyuan Sun
- Center for GI Cancer Diagnosis and Treatment, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, People’s Republic of China
| | - Yan Xiao
- Department of Clinical Laboratory, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, People’s Republic of China
| | - Juan Xue
- Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, People’s Republic of China
| | - Zimin Liu
- Center for GI Cancer Diagnosis and Treatment, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, People’s Republic of China
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Ding P, Wu J, Wu H, Li T, Niu X, Yang P, Guo H, Tian Y, He J, Yang J, Gu R, Zhang L, Meng N, Li X, Guo Z, Meng L, Zhao Q. Transcriptomics-Based Liquid Biopsy for Early Detection of Recurrence in Locally Advanced Gastric Cancer. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2406276. [PMID: 39556695 DOI: 10.1002/advs.202406276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2024] [Revised: 09/29/2024] [Indexed: 11/20/2024]
Abstract
The study presents a transcriptomics-based liquid biopsy approach for early recurrence detection in locally advanced gastric cancer (LAGC). Four mRNA biomarkers (AGTR1, DNER, EPHA7, and SUSD5) linked to recurrence are identified through transcriptomic data analysis. A Risk Stratification Assessment (RSA) model combining these biomarkers with clinical features showed superior predictive accuracy for postoperative recurrence, with AUCs of 0.919 and 0.935 in surgical and liquid biopsy validation cohorts, respectively. Functional studies using human gastric cancer cell lines AGS and HGC-27 demonstrated that silencing the identified mRNA panel genes impaired cell migration, invasion, and proliferation. In vivo experiments further showed reduced tumor growth, metastasis, and lymphangiogenesis in mice, possibly mediated by the cAMP signaling pathway. This non-invasive approach offers significant potential for enhancing recurrence detection and enabling personalized treatment strategies, thereby improving patient outcomes in the management of LAGC.
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Affiliation(s)
- Ping'an Ding
- The Third Department of Surgery, the Fourth Hospital of Hebei Medical University, Shijiazhuang, 050011, China
- Hebei Key Laboratory of Precision Diagnosis and Comprehensive Treatment of Gastric Cancer, Shijiazhuang, 050011, China
- Big data analysis and mining application for precise diagnosis and treatment of gastric cancer Hebei Provincial Engineering Research Center, Shijiazhuang, 050011, China
| | - Jiaxiang Wu
- The Third Department of Surgery, the Fourth Hospital of Hebei Medical University, Shijiazhuang, 050011, China
- Hebei Key Laboratory of Precision Diagnosis and Comprehensive Treatment of Gastric Cancer, Shijiazhuang, 050011, China
- Big data analysis and mining application for precise diagnosis and treatment of gastric cancer Hebei Provincial Engineering Research Center, Shijiazhuang, 050011, China
| | - Haotian Wu
- The Third Department of Surgery, the Fourth Hospital of Hebei Medical University, Shijiazhuang, 050011, China
- Hebei Key Laboratory of Precision Diagnosis and Comprehensive Treatment of Gastric Cancer, Shijiazhuang, 050011, China
- Big data analysis and mining application for precise diagnosis and treatment of gastric cancer Hebei Provincial Engineering Research Center, Shijiazhuang, 050011, China
| | - Tongkun Li
- The Third Department of Surgery, the Fourth Hospital of Hebei Medical University, Shijiazhuang, 050011, China
- Hebei Key Laboratory of Precision Diagnosis and Comprehensive Treatment of Gastric Cancer, Shijiazhuang, 050011, China
- Big data analysis and mining application for precise diagnosis and treatment of gastric cancer Hebei Provincial Engineering Research Center, Shijiazhuang, 050011, China
| | - Xiaoman Niu
- The Third Department of Surgery, the Fourth Hospital of Hebei Medical University, Shijiazhuang, 050011, China
- Hebei Key Laboratory of Precision Diagnosis and Comprehensive Treatment of Gastric Cancer, Shijiazhuang, 050011, China
- Big data analysis and mining application for precise diagnosis and treatment of gastric cancer Hebei Provincial Engineering Research Center, Shijiazhuang, 050011, China
| | - Peigang Yang
- The Third Department of Surgery, the Fourth Hospital of Hebei Medical University, Shijiazhuang, 050011, China
- Hebei Key Laboratory of Precision Diagnosis and Comprehensive Treatment of Gastric Cancer, Shijiazhuang, 050011, China
- Big data analysis and mining application for precise diagnosis and treatment of gastric cancer Hebei Provincial Engineering Research Center, Shijiazhuang, 050011, China
| | - Honghai Guo
- The Third Department of Surgery, the Fourth Hospital of Hebei Medical University, Shijiazhuang, 050011, China
- Hebei Key Laboratory of Precision Diagnosis and Comprehensive Treatment of Gastric Cancer, Shijiazhuang, 050011, China
- Big data analysis and mining application for precise diagnosis and treatment of gastric cancer Hebei Provincial Engineering Research Center, Shijiazhuang, 050011, China
| | - Yuan Tian
- The Third Department of Surgery, the Fourth Hospital of Hebei Medical University, Shijiazhuang, 050011, China
- Hebei Key Laboratory of Precision Diagnosis and Comprehensive Treatment of Gastric Cancer, Shijiazhuang, 050011, China
- Big data analysis and mining application for precise diagnosis and treatment of gastric cancer Hebei Provincial Engineering Research Center, Shijiazhuang, 050011, China
| | - Jinchen He
- The Third Department of Surgery, the Fourth Hospital of Hebei Medical University, Shijiazhuang, 050011, China
- Hebei Key Laboratory of Precision Diagnosis and Comprehensive Treatment of Gastric Cancer, Shijiazhuang, 050011, China
- Big data analysis and mining application for precise diagnosis and treatment of gastric cancer Hebei Provincial Engineering Research Center, Shijiazhuang, 050011, China
| | - Jiaxuan Yang
- The Third Department of Surgery, the Fourth Hospital of Hebei Medical University, Shijiazhuang, 050011, China
- Hebei Key Laboratory of Precision Diagnosis and Comprehensive Treatment of Gastric Cancer, Shijiazhuang, 050011, China
- Big data analysis and mining application for precise diagnosis and treatment of gastric cancer Hebei Provincial Engineering Research Center, Shijiazhuang, 050011, China
| | - Renjun Gu
- School of Chinese Medicine & School of Integrated Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210023, China
- Department of Gastroenterology and Hepatology, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, 210002, China
| | - Lilong Zhang
- Department of General Surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei, 430065, China
| | - Ning Meng
- Department of General Surgery, Shijiazhuang People's Hospital, Shijiazhuang, Hebei, 050050, China
| | - Xiaolong Li
- Department of General Surgery, Baoding Central Hospital, Baoding, Hebei, 071030, China
| | - Zhenjiang Guo
- Department of General Surgery, Hengshui People's Hospital, Hengshui, Hebei, 053099, China
| | - Lingjiao Meng
- Research Center and Tumor Research Institute of the Fourth Hospital of Hebei Medical University, Shijiazhuang, 050011, China
| | - Qun Zhao
- The Third Department of Surgery, the Fourth Hospital of Hebei Medical University, Shijiazhuang, 050011, China
- Hebei Key Laboratory of Precision Diagnosis and Comprehensive Treatment of Gastric Cancer, Shijiazhuang, 050011, China
- Big data analysis and mining application for precise diagnosis and treatment of gastric cancer Hebei Provincial Engineering Research Center, Shijiazhuang, 050011, China
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Wen X, Li H, Li S, Chang B, Chen S, Li H, Liu C, Li G. Associated factors of periodontitis and predicted study among young man in China: a population-based cross-sectional study. BMC Public Health 2024; 24:1235. [PMID: 38704531 PMCID: PMC11070096 DOI: 10.1186/s12889-024-18732-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Accepted: 04/29/2024] [Indexed: 05/06/2024] Open
Abstract
BACKGROUND Periodontitis represents the foremost oral condition in young men, strongly correlated with socioeconomic elements and oral health behaviors. This research aimed to assess the prevalence of periodontitis and associated associations with socio-demographics and oral health practices for subsequent Hazard Ratio (HR) estimation. METHODS A total of 46,476 young men were recruited to the study between August 2022 and October 2023. A questionnaire on socio-demographic factors and oral health-related behaviors related to periodontitis was completed. The standard procedure was used for oral examination. Logistic regression and hazard ratios were used to estimate the influencing factors, whereas the nomogram was used to predict the risk of periodontitis in young men. RESULTS A total of 46,476 young men were surveyed and completed the questionnaire. The overall prevalence of periodontitis among young men was 1.74%. Out of these, 1.7% had mild periodontitis and 0.6% had moderate periodontitis. Age and dental calculus were important factors in the periodontal health of young men. This nomogram, which includes 7 easily obtainable clinical characteristics routinely collected during periodontitis risk assessment, provides clinicians with a user-friendly tool to assess the risk of periodontal disease in young men. CONCLUSIONS Regular dental prophylaxis is crucial for young men to maintain their gingival health and prevent the onset of periodontitis. Dental calculus plays a prominent role in this matter, as it serves as a significant contributing factor.
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Affiliation(s)
- Xiaohui Wen
- Department of Epidemiology, The Fourth Military Medical University, Xi'an, 710032, China
| | - Hui Li
- School of Public Health, Southwest Medical University, Luzhou, 646000, China
| | - Shiting Li
- Department of Oral Implantology, The Affiliated Stomatological Hospital, Southwest Medical University, Luzhou, 646000, China
- Institute of Stomatology, Luzhou Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Southwest Medical University, Luzhou, 646000, China
| | - Bei Chang
- Department of Stomatology, The PLA Rocket Force Characteristic Medical Center, Beijing, 100000, China
| | - Shichao Chen
- Department of Oral Implantology, The Affiliated Stomatological Hospital, Southwest Medical University, Luzhou, 646000, China
- Institute of Stomatology, Luzhou Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Southwest Medical University, Luzhou, 646000, China
| | - Hongcai Li
- Department of Stomatology, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, China
| | - Caixia Liu
- Xichang People's Hospital, Xichang, 615000, China
| | - Guangwen Li
- Department of Oral Implantology, The Affiliated Stomatological Hospital, Southwest Medical University, Luzhou, 646000, China.
- Institute of Stomatology, Luzhou Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Southwest Medical University, Luzhou, 646000, China.
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Key Laboratory of Stomatology, Department of Prosthodontics, School of Stomatology, The Fourth Military Medical University, Xi'an, 710032, China.
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Zheng Y, Ma Y, Pang C, Yin K, Liu K, Chen J, Zi M, Wei Y, Cheng X, Yuan L. A retrospective study: exploring the optimal patient population for adjuvant chemotherapy after D2 gastrectomy. J Gastrointest Surg 2024; 28:365-374. [PMID: 38583885 DOI: 10.1016/j.gassur.2024.01.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 12/28/2023] [Accepted: 01/13/2024] [Indexed: 04/09/2024]
Abstract
BACKGROUND Adjuvant chemotherapy (CT) constitutes the primary approach for treating resectable advanced gastric cancer (GC). However, the effectiveness of postoperative CT can differ across various patient groups. This retrospective study aimed to examine how variances in clinical and pathologic factors affect postoperative CT. METHODS This study enrolled 2060 patients with GC who underwent curative gastrectomy at Zhejiang Cancer Hospital between January 2008 and December 2017, with 1277 receiving postoperative CT. This study used Kaplan-Meier to determine the effect of clinical and pathology factors on CT benefits. In addition, univariate and multivariate Cox regression analyses were used to identify independent prognosis risk factors. RESULTS Both univariate and multivariate analyses demonstrated that the absence of postoperative CT is an independent factor associated with a poor prognosis in patients with GC. The Kaplan-Meier univariate analysis revealed that specific subgroups, including males, those with a normal body mass index (BMI), the elderly, individuals with gastric adenocarcinoma, cases of nerve invasion by the tumor, vascular invasion by the tumor, tumor size ≥ 5 cm, and Tumor, Node, Metastasis (TNM) stage III, exhibited improved treatment outcomes with the administration of postoperative CT. The creation of nomograms using Cox regression and the rms package holds significant clinical relevance. CONCLUSION Postoperative CT is advantageous for prolonging the survival of advanced patients undergoing D2 gastrectomy, particularly in male patients, the elderly, individuals with a normal BMI score, those diagnosed with gastric adenocarcinoma, cases, in which the tumor invades nerves or blood vessels, patients with a tumor size of ≥5 cm, and those with a TNM stage of III, as it results in improved treatment outcomes within these subgroups.
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Affiliation(s)
- Yingsong Zheng
- Postgraduate Training Base Alliance of Wenzhou Medical University (Zhejiang Cancer Hospital), Hangzhou, Zhejiang, China; Department of Gastric Surgery, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou, Zhejiang, China; Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer, Zhejiang Cancer Hospital, Hangzhou, China; Zhejiang Key Lab of Prevention, Diagnosis and Therapy of Upper Gastrointestinal Cancer, Zhejiang Cancer Hospital, Hangzhou, China
| | - Yubo Ma
- Department of Gastric Surgery, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou, Zhejiang, China; Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer, Zhejiang Cancer Hospital, Hangzhou, China; Zhejiang Key Lab of Prevention, Diagnosis and Therapy of Upper Gastrointestinal Cancer, Zhejiang Cancer Hospital, Hangzhou, China; The Second Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Chuhong Pang
- Postgraduate Training Base Alliance of Wenzhou Medical University (Zhejiang Cancer Hospital), Hangzhou, Zhejiang, China; Department of Gastric Surgery, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou, Zhejiang, China; Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer, Zhejiang Cancer Hospital, Hangzhou, China; Zhejiang Key Lab of Prevention, Diagnosis and Therapy of Upper Gastrointestinal Cancer, Zhejiang Cancer Hospital, Hangzhou, China
| | - KaiLai Yin
- Postgraduate Training Base Alliance of Wenzhou Medical University (Zhejiang Cancer Hospital), Hangzhou, Zhejiang, China; Department of Gastric Surgery, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou, Zhejiang, China; Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer, Zhejiang Cancer Hospital, Hangzhou, China; Zhejiang Key Lab of Prevention, Diagnosis and Therapy of Upper Gastrointestinal Cancer, Zhejiang Cancer Hospital, Hangzhou, China
| | - Kang Liu
- Department of Gastric Surgery, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou, Zhejiang, China; Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer, Zhejiang Cancer Hospital, Hangzhou, China; Zhejiang Key Lab of Prevention, Diagnosis and Therapy of Upper Gastrointestinal Cancer, Zhejiang Cancer Hospital, Hangzhou, China; The Second Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Jinxia Chen
- Postgraduate Training Base Alliance of Wenzhou Medical University (Zhejiang Cancer Hospital), Hangzhou, Zhejiang, China; Department of Gastric Surgery, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou, Zhejiang, China; Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer, Zhejiang Cancer Hospital, Hangzhou, China; Zhejiang Key Lab of Prevention, Diagnosis and Therapy of Upper Gastrointestinal Cancer, Zhejiang Cancer Hospital, Hangzhou, China
| | - Mengli Zi
- Postgraduate Training Base Alliance of Wenzhou Medical University (Zhejiang Cancer Hospital), Hangzhou, Zhejiang, China; Department of Gastric Surgery, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou, Zhejiang, China; Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer, Zhejiang Cancer Hospital, Hangzhou, China; Zhejiang Key Lab of Prevention, Diagnosis and Therapy of Upper Gastrointestinal Cancer, Zhejiang Cancer Hospital, Hangzhou, China
| | - Yizhou Wei
- Postgraduate Training Base Alliance of Wenzhou Medical University (Zhejiang Cancer Hospital), Hangzhou, Zhejiang, China; Department of Gastric Surgery, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou, Zhejiang, China; Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer, Zhejiang Cancer Hospital, Hangzhou, China; Zhejiang Key Lab of Prevention, Diagnosis and Therapy of Upper Gastrointestinal Cancer, Zhejiang Cancer Hospital, Hangzhou, China
| | - Xiangdong Cheng
- Department of Gastric Surgery, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou, Zhejiang, China; Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer, Zhejiang Cancer Hospital, Hangzhou, China; Zhejiang Key Lab of Prevention, Diagnosis and Therapy of Upper Gastrointestinal Cancer, Zhejiang Cancer Hospital, Hangzhou, China
| | - Li Yuan
- Department of Gastric Surgery, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou, Zhejiang, China; Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer, Zhejiang Cancer Hospital, Hangzhou, China; Zhejiang Key Lab of Prevention, Diagnosis and Therapy of Upper Gastrointestinal Cancer, Zhejiang Cancer Hospital, Hangzhou, China.
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Liu C, Tao F, Lu J, Park S, An L. Defining nomograms for predicting prognosis of early and late recurrence in gastric cancer patients after radical gastrectomy. Medicine (Baltimore) 2023; 102:e35585. [PMID: 37861478 PMCID: PMC10589600 DOI: 10.1097/md.0000000000035585] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2023] [Accepted: 09/20/2023] [Indexed: 10/21/2023] Open
Abstract
There are few studies on the predictive factors of early recurrence (ER) and late recurrence (LR) of advanced gastric cancer (GC) after curative surgery. Our study aims to explore the independent predictors influencing the prognosis between ER and LR in patients with advanced GC after curative intent surgery respectively. And we will further develop nomograms for prediction of post recurrence survival (PRS). Data of patients with GC who received radical gastrectomy was retrospectively collected. Recurrence was classified into ER and LR according to the 2 years after surgery as the cutoff value. Multivariate Cox regression analyses were used to explore significant predictors in our analysis. Then these significant predictors were integrated to construct nomograms. The 1-, 2- and 3-year probabilities of PRS in patients with ER were 30.00%, 16.36% and 11.82%, respectively. In contrast, the late group were 44.68%, 23.40%, and 23.30%, respectively. Low body mass index (hazard ratio [HR] = 0.86, P = .001), elevated monocytes count (HR = 4.54, P = .003) and neutrophil-lymphocyte ratio (HR = 1.03, P = .037) at the time of recurrence were risk factors of PRS after ER. Decreased hemoglobin (HR = 0.97, P = .008) and elevated neutrophil-lymphocyte ratio (HR = 1.06, P = .045) at the time of recurrence were risk factors of PRS after LR. The calibration curves for probability of 1-, 2-, and 3-year PRS showed excellent predictive effect. Internal validation concordance indexes of PRS were 0.722 and 0.671 for ER and LR respectively. In view of the different predictive factors of ER and LR of GC, the practical predictive model may help clinicians make reasonable decisions.
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Affiliation(s)
- Chenming Liu
- Department of General Surgery, Shaoxing People’s Hospital, Shaoxing, China
- Zhejiang University School of Medicine, Hangzhou, China
| | - Feng Tao
- Department of Gastrointestinal Surgery, Shaoxing People’s Hospital, Shaoxing, China
| | - Jialiang Lu
- Department of General Surgery, Shaoxing People’s Hospital, Shaoxing, China
- School of Medicine, Shaoxing University, Shaoxing, China
| | - Sungsoo Park
- Department of Surgery, Korea University Medical Center, Anam Hospital, Seoul, South Korea
| | - Liang An
- Department of Gastrointestinal Surgery, Shaoxing People’s Hospital, Shaoxing, China
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8
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Li X, Zhai Z, Ding W, Chen L, Zhao Y, Xiong W, Zhang Y, Lin D, Chen Z, Wang W, Gao Y, Cai S, Yu J, Zhang X, Liu H, Li G, Chen T. An artificial intelligence model to predict survival and chemotherapy benefits for gastric cancer patients after gastrectomy development and validation in international multicenter cohorts. Int J Surg 2022; 105:106889. [PMID: 36084807 DOI: 10.1016/j.ijsu.2022.106889] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 08/19/2022] [Accepted: 08/28/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND Gastric cancer (GC) is a major health problem worldwide, with high prevalence and mortality. The present GC staging system provides inadequate prognostic information and does not reflect the chemotherapy benefit of GC. METHODS Two hundred fifty-five patients who underwent surgical resection were enrolled in our study (training cohort = 212, internal validation cohort = 43). Nine clinicopathologic features were obtained to construct an support vector machine (SVM) model. The cohorts from 4 domestic centres and The Cancer Genome Atlas (TCGA) were used for external validation. RESULTS In the training cohort, the AUCs were 0.773 (95% CI 0.708-0.838) for 5-year overall survival (OS) and 0.751 (95% CI 0.683-0.820) for 5-year disease-free survival (DFS); in the domestic validation cohort, the AUCs were 0.852 (95% CI 0.810-0.894) and 0.837 (95% CI 0.792-0.882), respectively. The model performed better than the TNM staging system according to the receiver operator characteristic(ROC) curve. GC patients were significantly divided into low, moderate and high risk based on the SVM. High-risk TNM stage Ⅱ and Ⅲ patients were more likely to benefit from adjuvant chemotherapy than low-risk patients. CONCLUSIONS The SVM-based model may be used to predict OS and DFS in GC patients and the benefit of adjuvant chemotherapy in TNM stage Ⅱ and Ⅲ GC patients.
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Affiliation(s)
- Xunjun Li
- Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangdong Provincial Engineering Technology Research Center of Minimally Invasive Surgery, Guangzhou, 510515, Guangdong Province, China
| | - Zhongya Zhai
- Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangdong Provincial Engineering Technology Research Center of Minimally Invasive Surgery, Guangzhou, 510515, Guangdong Province, China
| | - Wenfu Ding
- Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangdong Provincial Engineering Technology Research Center of Minimally Invasive Surgery, Guangzhou, 510515, Guangdong Province, China
| | - Li Chen
- Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangdong Provincial Engineering Technology Research Center of Minimally Invasive Surgery, Guangzhou, 510515, Guangdong Province, China
| | - Yuyun Zhao
- School of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, Guangdong Province, China
| | - Wenjun Xiong
- Department of Gastrointestinal Surgery, Guangdong Provincial Hospital of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, Guangdong Province, China
| | - Yunfei Zhang
- Department of Gastrointestinal Surgery, First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450001, Henan Province, China
| | - Dingyi Lin
- School of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, Guangdong Province, China
| | - Zequn Chen
- Department of General Surgery, Maoming People's Hospital, Maoming, 525000, Guangdong Province, China
| | - Wei Wang
- Department of Gastrointestinal Surgery, Guangdong Provincial Hospital of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, Guangdong Province, China
| | - Yongshun Gao
- Department of Gastrointestinal Surgery, First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450001, Henan Province, China
| | - Shirong Cai
- Department of Gastrointestinal Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, Guangdong Province, China
| | - Jiang Yu
- Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangdong Provincial Engineering Technology Research Center of Minimally Invasive Surgery, Guangzhou, 510515, Guangdong Province, China
| | - Xinhua Zhang
- Department of Gastrointestinal Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, Guangdong Province, China.
| | - Hao Liu
- Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangdong Provincial Engineering Technology Research Center of Minimally Invasive Surgery, Guangzhou, 510515, Guangdong Province, China.
| | - Guoxin Li
- Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangdong Provincial Engineering Technology Research Center of Minimally Invasive Surgery, Guangzhou, 510515, Guangdong Province, China
| | - Tao Chen
- Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangdong Provincial Engineering Technology Research Center of Minimally Invasive Surgery, Guangzhou, 510515, Guangdong Province, China.
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9
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Nakauchi M, Court CM, Tang LH, Gönen M, Janjigian YY, Maron SB, Molena D, Coit DG, Brennan MF, Strong VE. Validation of the Memorial Sloan Kettering Gastric Cancer Post-Resection Survival Nomogram: Does It Stand the Test of Time? J Am Coll Surg 2022; 235:294-304. [PMID: 35839406 PMCID: PMC9298603 DOI: 10.1097/xcs.0000000000000251] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
BACKGROUND The Memorial Sloan Kettering Cancer Center (MSK) nomogram combined both gastroesophageal junction (GEJ) and gastric cancer patients and was created in an era from patients who generally did not receive neoadjuvant chemotherapy. We sought to reevaluate the MSK nomogram in the era of multidisciplinary treatment for GEJ and gastric cancer. STUDY DESIGN Using data on patients who underwent R0 resection for GEJ or gastric cancer between 2002 and 2016, the C-index of prediction for disease-specific survival (DSS) was compared between the MSK nomogram and the American Joint Committee on Cancer (AJCC) 8th edition staging system after segregating patients by tumor location (GEJ or gastric cancer) and neoadjuvant treatment. A new nomogram was created for the group for which both systems poorly predicted prognosis. RESULTS During the study period, 886 patients (645 gastric and 241 GEJ cancer) underwent up-front surgery, and 999 patients (323 gastric and 676 GEJ) received neoadjuvant treatment. Compared with the AJCC staging system, the MSK nomogram demonstrated a comparable C-index in gastric cancer patients undergoing up-front surgery (0.786 vs 0.753) and a better C-index in gastric cancer patients receiving neoadjuvant treatment (0.796 vs 0.698). In GEJ cancer patients receiving neoadjuvant chemotherapy, neither the MSK nomogram nor the AJCC staging system performed well (C-indices 0.647 and 0.646). A new GEJ nomogram was created based on multivariable Cox regression analysis and was validated with a C-index of 0.718. CONCLUSIONS The MSK gastric cancer nomogram's predictive accuracy remains high. We developed a new GEJ nomogram that can effectively predict DSS in patients receiving neoadjuvant treatment.
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Affiliation(s)
- Masaya Nakauchi
- From the Gastric and Mixed Tumor Service, Department of Surgery (Nakauchi, Court, Coit, Brennan, Strong), Memorial Sloan Kettering Cancer Center, New York, NY
| | - Colin M Court
- From the Gastric and Mixed Tumor Service, Department of Surgery (Nakauchi, Court, Coit, Brennan, Strong), Memorial Sloan Kettering Cancer Center, New York, NY
| | - Laura H Tang
- Gastrointestinal Pathology Service, Department of Pathology (Tang), Memorial Sloan Kettering Cancer Center, New York, NY
| | - Mithat Gönen
- Department of Epidemiology and Biostatistics (Gönen), Memorial Sloan Kettering Cancer Center, New York, NY
| | - Yelena Y Janjigian
- Gastrointestinal Oncology Service, Department of Medicine (Janjigian, Maron), Memorial Sloan Kettering Cancer Center, New York, NY
| | - Steven B Maron
- Gastrointestinal Oncology Service, Department of Medicine (Janjigian, Maron), Memorial Sloan Kettering Cancer Center, New York, NY
| | - Daniela Molena
- Thoracic Service, Department of Surgery (Molena), Memorial Sloan Kettering Cancer Center, New York, NY
| | - Daniel G Coit
- From the Gastric and Mixed Tumor Service, Department of Surgery (Nakauchi, Court, Coit, Brennan, Strong), Memorial Sloan Kettering Cancer Center, New York, NY
| | - Murray F Brennan
- From the Gastric and Mixed Tumor Service, Department of Surgery (Nakauchi, Court, Coit, Brennan, Strong), Memorial Sloan Kettering Cancer Center, New York, NY
| | - Vivian E Strong
- From the Gastric and Mixed Tumor Service, Department of Surgery (Nakauchi, Court, Coit, Brennan, Strong), Memorial Sloan Kettering Cancer Center, New York, NY
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10
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Huang Y, Jiang S, Li W, Fan Y, Leng Y, Gao C. Establishment and Effectiveness Evaluation of a Scoring System-RAAS (RDW, AGE, APACHE II, SOFA) for Sepsis by a Retrospective Analysis. J Inflamm Res 2022; 15:465-474. [PMID: 35082513 PMCID: PMC8786358 DOI: 10.2147/jir.s348490] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 12/25/2021] [Indexed: 01/19/2023] Open
Abstract
Background Methods Results Conclusion
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Affiliation(s)
- Yingying Huang
- Emergency Department, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China
| | - Shaowei Jiang
- Emergency Department, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China
| | - Wenjie Li
- Emergency Department, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China
| | - Yiwen Fan
- Department of Pathology Medicine Biology, The University Medical Center Groningen, Groningen, the Netherlands
| | - Yuxin Leng
- Critical Care Medicine Department, Peking University Third Hospital, Beijing, People’s Republic of China
| | - Chengjin Gao
- Emergency Department, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China
- Correspondence: Chengjin Gao; Yuxin Leng Email ;
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11
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Development of a predictive model for extragastric recurrence after curative resection for early gastric cancer. Gastric Cancer 2022; 25:255-264. [PMID: 34291321 DOI: 10.1007/s10120-021-01217-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 07/07/2021] [Indexed: 02/07/2023]
Abstract
BACKGROUND Stratification of patients who undergo curative resection for early gastric cancer (EGC) is warranted due to the heterogeneity in the risk of developing extragastric recurrence (EGR). Therefore, we aimed to stratify the need for postoperative surveillance for EGR detection in patients with EGC by developing a model for predicting EGR-free survival. METHODS This retrospective cohort study included patients who underwent postoperative surveillance after curative resection of EGC (n = 4149). Cox proportional hazard models were used to identify predictors to build a model for predicting EGR-free survival. Bootstrap-corrected c-index and calibration plots were used for internal and external (n = 2148) validations. RESULTS A risk-scoring system was constructed using variables significantly associated with EGR-free survival: pathologic T stage (pT1b[sm1], hazard ratio [HR] 4.928; pT1b[sm2], HR 5.235; pT1b[sm3], HR 7.748) and N stage (pN1, HR 4.056; pN2, HR 9.075; pN3, HR 30.659). Patients were dichotomized into a very-low-risk group or a low-or-greater-risk group. The 5-year EGR-free survival rates differed between the two groups (99.9 vs. 97.3%). The discriminative performance of the model was 0.851 (Uno's c-index) and 0.751 in the internal and external cohorts, respectively. The calibration slope was 0.916 and 1.131 in the internal and external cohorts, respectively. CONCLUSIONS Our model for predicting EGR-free survival based on the pathologic T and N stages may be useful for stratifying patients who have undergone curative surgery for EGC. The results suggest that patients in the very-low-risk group may be spared from postoperative surveillance considering their extremely high EGR-free survival rate.
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12
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Ouyang H, Shi Q, Zhu J, Shen H, Jiang S, Song K. Nomogram for predicting 1-, 5-, and 10-year survival in hemodialysis (HD) patients: a single center retrospective study. Ren Fail 2021; 43:1508-1519. [PMID: 34779699 PMCID: PMC8604490 DOI: 10.1080/0886022x.2021.1997762] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Objectives Risk of death is high for hemodialysis (HD) patients but it varies considerably among individuals. There is few clinical tool to predict long-term survival rates for HD patients yet. The aim of this study was to develop and validate a easy-to-use nomogram for prediction of 1-, 5-, and 10-year survival among HD patients. Methods This study retrospectively enrolled 643 adult HD patients who was randomly assigned to two cohorts: the training cohort (n = 438) and validation cohort (n = 205), univariate survival analyses were performed using Kaplan–Meier’s curve with log-rank test and multivariate Cox regression analyses were performed to identify predictive factors, and a easy-to-use nomogram was established. The performance was assessed using the area under the curve (AUC), calibration plots, and decision curve analysis. Results The score included seven commonly available predictors: age, diabetes, use of arteriovenous fistula (AVF), history of emergency temporary dialysis catheter placement, cardiovascular disease (CVD), hemoglobin (Hgl), and no caregiver. The score revealed good discrimination in the training and validation cohort (AUC 0.779 and 0.758, respectively) and the calibration plots showed well calibration, indicating suitable performance of the nomogram model. Decision curve analysis showed that the nomogram added more net benefit compared with the treat-all strategy or treat-none strategy with a threshold probability of 10% or greater. Conclusions This easy-to-use nomogram can accurately predict 1-, 5-, and 10-year survival for HD patients, which could be used in clinical decision-making and clinical care. Abbreviations:
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Affiliation(s)
- Han Ouyang
- Department of Nephrology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Qiuhong Shi
- Department of Nephrology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Jing Zhu
- Department of Cardiology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Huaying Shen
- Department of Nephrology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Shan Jiang
- Department of Nephrology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Kai Song
- Department of Nephrology, The Second Affiliated Hospital of Soochow University, Suzhou, China
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13
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Guo Q, Wang Y, An J, Wang S, Dong X, Zhao H. A Prognostic Model for Patients With Gastric Signet Ring Cell Carcinoma. Technol Cancer Res Treat 2021; 20:15330338211027912. [PMID: 34190015 PMCID: PMC8258759 DOI: 10.1177/15330338211027912] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Background: The aim of our study was to develop a nomogram model to predict overall survival (OS) and cancer-specific survival (CSS) in patients with gastric signet ring cell carcinoma (GSRC). Methods: GSRC patients from 2004 to 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database and randomly assigned to the training and validation sets. Multivariate Cox regression analyses screened for OS and CSS independent risk factors and nomograms were constructed. Results: A total of 7,149 eligible GSRC patients were identified, including 4,766 in the training set and 2,383 in the validation set. Multivariate Cox regression analysis showed that gender, marital status, race, AJCC stage, TNM stage, surgery and chemotherapy were independent risk factors for both OS and CSS. Based on the results of the multivariate Cox regression analysis, prognostic nomograms were constructed for OS and CSS. In the training set, the C-index was 0.754 (95% CI = 0.746-0.762) for the OS nomogram and 0.762 (95% CI: 0.753-0.771) for the CSS nomogram. In the internal validation, the C-index for the OS nomogram was 0.758 (95% CI: 0.746-0.770), while the C-index for the CSS nomogram was 0.762 (95% CI: 0.749-0.775). Compared with TNM stage and SEER stage, the nomogram had better predictive ability. In addition, the calibration curves also showed good consistency between the predicted and actual 3-year and 5-year OS and CSS. Conclusion: The nomogram can effectively predict OS and CSS in patients with GSRC, which may help clinicians to personalize prognostic assessments and clinical decisions.
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Affiliation(s)
- Qinping Guo
- Department of General Surgery, Shanxi Bethune Hospital, Taiyuan, Shanxi Province, China
| | - Yinquan Wang
- Department of General Surgery, Shanxi Bethune Hospital, Taiyuan, Shanxi Province, China
| | - Jie An
- Department of General Surgery, Shanxi Bethune Hospital, Taiyuan, Shanxi Province, China
| | - Siben Wang
- Department of Thoracic Surgery, Huainan First People's Hospital, Huainan, Anhui Province, China
| | - Xiushan Dong
- Department of General Surgery, Shanxi Bethune Hospital, Taiyuan, Shanxi Province, China
| | - Haoliang Zhao
- Department of General Surgery, Shanxi Bethune Hospital, Taiyuan, Shanxi Province, China
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14
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Balasubramanian D, Subramaniam N, Missale F, Marchi F, Dokhe Y, Vijayan S, Nambiar A, Mattavelli D, Calza S, Bresciani L, Piazza C, Nicolai P, Peretti G, Thankappan K, Iyer S. Predictive nomograms for oral tongue squamous cell carcinoma applying the American Joint Committee on Cancer/Union Internationale Contre le Cancer 8th edition staging system. Head Neck 2021; 43:1043-1055. [PMID: 33529403 DOI: 10.1002/hed.26554] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Revised: 10/13/2020] [Accepted: 11/10/2020] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Nomograms applying the 8th edition of the TNM staging system aimed at predicting overall (OS), disease-specific (DSS), locoregional recurrence-free (LRRFS) and distant recurrence-free survivals (DRFS) for oral tongue squamous cell carcinoma (OTSCC) are still lacking. METHODS A training cohort of 438 patients with OTSCC was retrospectively enrolled from a single institution. An external validation set of 287 patients was retrieved from two independent institutions. RESULTS Internal validation of the multivariable models for OS, DSS, DRFS and LRRFS showed a good calibration and discrimination results with optimism-corrected c-indices of 0.74, 0.75, 0.77 and 0.70, respectively. The external validation confirmed the good performance of OS, DSS and DRFS models (c-index 0.73 and 0.77, and 0.73, respectively) and a fair performance of the LRRFS model (c-index 0.58). CONCLUSIONS The nomograms herein presented can be implemented as useful tools for prediction of OS, DSS, DRFS and LRRFS in OTSCC.
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Affiliation(s)
- Deepak Balasubramanian
- Department of Head and Neck Oncology, Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham, Kochi, India
| | - Narayana Subramaniam
- Department of Head and Neck Oncology, Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham, Kochi, India
| | - Francesco Missale
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy.,Department of Otorhinolaryngology - Head and Neck Surgery, University of Genova, Genoa, Italy.,Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Filippo Marchi
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy.,Department of Plastic Surgery, Chang Gung Memorial Hospital, Chang Gung University and Medical College, Taoyuan, Taiwan
| | - Yogesh Dokhe
- Department of Head and Neck Oncology, Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham, Kochi, India
| | - Smitha Vijayan
- Department of Pathology, Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham, Kochi, India
| | - Ajit Nambiar
- Department of Pathology, Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham, Kochi, India
| | - Davide Mattavelli
- Unit of Otorhinolaryngology - Head and Neck Surgery, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy
| | - Stefano Calza
- Unit of Biostatistics, Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy.,Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.,Big & Open Data Innovation Laboratory, University of Brescia, Brescia, Italy
| | - Lorenzo Bresciani
- Department of Otorhinolaryngology, Maxillofacial and Thyroid Surgery, Fondazione IRCCS, National Cancer Institute of Milan, Milan, Italy
| | - Cesare Piazza
- Department of Otorhinolaryngology, Maxillofacial and Thyroid Surgery, Fondazione IRCCS, National Cancer Institute of Milan, Milan, Italy.,Department of Oncology and Oncohematology, University of Milan, Milan, Italy
| | - Piero Nicolai
- Section of Otorhinolaryngology - Head and Neck Surgery, Department of Neurosciences, University of Padua, Padua, Italy
| | - Giorgio Peretti
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy.,Department of Otorhinolaryngology - Head and Neck Surgery, University of Genova, Genoa, Italy
| | - Krishnakumar Thankappan
- Department of Head and Neck Oncology, Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham, Kochi, India
| | - Subramania Iyer
- Department of Head and Neck Oncology, Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham, Kochi, India
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Zhang Z, Jin Z, Liu D, Zhang Y, Li C, Miao Y, Chi X, Feng J, Wang Y, Hao S, Ji N. A Nomogram Predicts Individual Prognosis in Patients With Newly Diagnosed Glioblastoma by Integrating the Extent of Resection of Non-Enhancing Tumors. Front Oncol 2020; 10:598965. [PMID: 33344248 PMCID: PMC7739947 DOI: 10.3389/fonc.2020.598965] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Accepted: 10/21/2020] [Indexed: 11/22/2022] Open
Abstract
Background The extent of resection of non-contrast enhancing tumors (EOR-NCEs) has been shown to be associated with prognosis in patients with newly diagnosed glioblastoma (nGBM). This study aimed to develop and independently validate a nomogram integrated with EOR-NCE to assess individual prognosis. Methods Data for this nomogram were based on 301 patients hospitalized for nGBM from October 2011 to April 2019 at the Beijing Tiantan Hospital, Capital Medical University. These patients were randomly divided into derivation (n=181) and validation (n=120) cohorts at a ratio of 6:4. To evaluate predictive accuracy, discriminative ability, and clinical net benefit, concordance index (C-index), receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were calculated for the extent of resection of contrast enhancing tumor (EOR-CE) and EOR-NCE nomograms. Comparison between these two models was performed as well. Results The Cox proportional hazards model was used to establish nomograms for this study. Older age at diagnosis, Karnofsky performance status (KPS)<70, unmethylated O6-methylguanine-DNA methyltransferase (MGMT) status, wild-type isocitrate dehydrogenase enzyme (IDH), and lower EOR-CE and EOR-NCE were independent factors associated with shorter survival. The EOR-NCE nomogram had a higher C-index than the EOR-CE nomogram. Its calibration curve for the probability of survival exhibited good agreement between the identical and actual probabilities. The EOR-NCE nomogram showed superior net benefits and improved performance over the EOR-CE nomogram with respect to DCA and ROC for survival probability. These results were also confirmed in the validation cohort. Conclusions An EOR-NCE nomogram assessing individualized survival probabilities (12-, 18-, and 24-month) for patients with nGBM could be useful to provide patients and their relatives with health care consultations on optimizing therapeutic approaches and prognosis.
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Affiliation(s)
- Zhe Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,National Clinical Research Center for Neurological Diseases (China), Beijing, China
| | - Zeping Jin
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,National Clinical Research Center for Neurological Diseases (China), Beijing, China
| | - Dayuan Liu
- Department of Neurosurgery, The Second Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Yang Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,National Clinical Research Center for Neurological Diseases (China), Beijing, China
| | - Chunzhao Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,National Clinical Research Center for Neurological Diseases (China), Beijing, China
| | - Yazhou Miao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,National Clinical Research Center for Neurological Diseases (China), Beijing, China
| | - Xiaohan Chi
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,National Clinical Research Center for Neurological Diseases (China), Beijing, China
| | - Jie Feng
- National Clinical Research Center for Neurological Diseases (China), Beijing, China.,Beijing Neurosurgical Institute, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Cancer Institute, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
| | - Yaming Wang
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Shuyu Hao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,National Clinical Research Center for Neurological Diseases (China), Beijing, China
| | - Nan Ji
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,National Clinical Research Center for Neurological Diseases (China), Beijing, China.,Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing, China
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16
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Seo N, Han K, Hyung WJ, Chung YE, Park CH, Kim JH, Lee SK, Kim MJ, Noh SH, Lim JS. Stratification of Postsurgical Computed Tomography Surveillance Based on the Extragastric Recurrence of Early Gastric Cancer. Ann Surg 2020; 272:319-325. [PMID: 32675545 DOI: 10.1097/sla.0000000000003238] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
OBJECTIVE To stratify the postsurgical computed tomography (CT) surveillance based on a risk-scoring system for predicting extragastric recurrence after surgical resection of early gastric cancer (EGC). SUMMARY OF BACKGROUND DATA Postsurgical CT surveillance should not be routinely performed in all patients because of the low incidence of extragastric recurrence and potential risk of radiation exposure. METHODS Data from 3162 patients who underwent surgical resection for EGC were reviewed to develop a risk-scoring system to predict extragastric recurrence. Risk scores were based on the predictive factors for extragastric recurrence, which were determined using Cox proportional hazard regression model. The risk-scoring system was validated by Uno censoring adjusted C-index. External validation was performed using an independent dataset (n = 430). RESULTS The overall incidence of extragastric recurrence was 1.4% (44/3162). Five risk factors (lymph node metastasis, indications for endoscopic resection, male sex, positive lymphovascular invasion, and elevated macroscopic type), which were significantly associated with extragastric recurrence, were incorporated into the risk-scoring system, and the patients were categorized into 2 risk groups. The 10-year extragastric recurrence-free survival differed significantly between low- and high-risk groups (99.7% vs 96.5%; P < 0.001). The predictive accuracy of the risk-scoring system in the development cohort was 0.870 [Uno C-index; 95% confidence interval (95% CI), 0.800-0.939]. Discrimination was good after internal (0.859) and external validation (0.782, 0.549-1.000). CONCLUSION This risk-scoring system might be useful to predict extragastric recurrence of EGC after curative surgical resection. We suggest that postsurgical CT surveillance to detect extragastric recurrence should be avoided in the low-risk group.
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Affiliation(s)
- Nieun Seo
- Department of Radiology, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Kyunghwa Han
- Department of Radiology, Yonsei Biomedical Research Institute, Research Institute of Radiological Science, Seoul, Korea
| | - Woo Jin Hyung
- Department of Surgery, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Yong Eun Chung
- Department of Radiology, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Chan Hyuk Park
- Department of Internal Medicine, Guri Hospital, Hanyang University College of Medicine, Guri, Korea
| | - Jie-Hyun Kim
- Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Sang Kil Lee
- Department of Internal Medicine, Severance Hospital, Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, Korea
| | - Myeong-Jin Kim
- Department of Radiology, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Sung Hoon Noh
- Department of Surgery, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Joon Seok Lim
- Department of Radiology, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
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17
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Li Z, Wu X, Gao X, Shan F, Ying X, Zhang Y, Ji J. Development and validation of an artificial neural network prognostic model after gastrectomy for gastric carcinoma: An international multicenter cohort study. Cancer Med 2020; 9:6205-6215. [PMID: 32666682 PMCID: PMC7476835 DOI: 10.1002/cam4.3245] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 06/01/2020] [Accepted: 06/01/2020] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Recently, artificial neural network (ANN) methods have also been adopted to deal with the complex multidimensional nonlinear relationship between clinicopathologic variables and survival for patients with gastric cancer. Using a multinational cohort, this study aimed to develop and validate an ANN-based survival prediction model for patients with gastric cancer. METHODS Patients with gastric cancer who underwent gastrectomy in a Chinese center, a Japanese center, and recorded in the Surveillance, Epidemiology, and End Results database, respectively, were included in this study. Multilayer perceptron neural network was used to develop the prediction model. Time-dependent receiver operating characteristic (ROC) curves, area under the curves (AUCs), and decision curve analysis (DCA) were used to compare the ANN model with previous prediction models. RESULTS An ANN model with nine input nodes, nine hidden nodes, and two output nodes was constructed. These three cohort's data showed that the AUC of the model was 0.795, 0.836, and 0.850 for 5-year survival prediction, respectively. In the calibration curve analysis, the ANN-predicted survival had a high consistency with the actual survival. Comparison of the DCA and time-dependent ROC between the ANN model and previous prediction models showed that the ANN model had good and stable prediction capability compared to the previous models in all cohorts. CONCLUSIONS The ANN model has significantly better discriminative capability and allows an individualized survival prediction. This model has good versatility in Eastern and Western data and has high clinical application value.
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Affiliation(s)
- Ziyu Li
- Gastrointestinal Cancer Center, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China
| | - Xiaolong Wu
- Gastrointestinal Cancer Center, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China
| | - Xiangyu Gao
- Gastrointestinal Cancer Center, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China
| | - Fei Shan
- Gastrointestinal Cancer Center, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China
| | - Xiangji Ying
- Gastrointestinal Cancer Center, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China
| | - Yan Zhang
- Gastrointestinal Cancer Center, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China
| | - Jiafu Ji
- Gastrointestinal Cancer Center, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China
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18
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Ding Y, Chen Y, Wu M, Li L, Huang Y, Wang H, Wang H, Yu X, Xu N, Teng L. Identification of genes associated with gastric cancer survival and construction of a nomogram to improve risk stratification for patients with gastric cancer. Oncol Lett 2020; 20:215-225. [PMID: 32537023 PMCID: PMC7291675 DOI: 10.3892/ol.2020.11543] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2019] [Accepted: 11/27/2019] [Indexed: 02/07/2023] Open
Abstract
The present study aimed to identify genes associated with gastric cancer survival and improve risk stratification for patients with gastric cancer. Transcriptomic and clinicopathological data from 443 gastric cancer samples were retrieved from The Cancer Genome Atlas database. The DESeq R package was applied to screen for differentially expressed genes between Tumor-Node-Metastasis (TNM) stage (I vs. IV) and histological grade (G3 vs. G1 and G2). A total of seven genes were common to both comparisons; spondin 1 (SPON1); thrombospondin 4 (THBS4); Sushi, Von Willebrand factor type A, EGF and pentraxin domain containing 1 (SVEP1); prickle planar cell polarity protein 1 (PRICKLE1); ATP binding cassette subfamily A member 8 (ABCA8); Slit guidance ligand 2 (SLIT2); and EGF containing fibulin extracellular matrix protein 1 (EFEMP1), were selected as candidate survival-associated genes for further analysis. The prognostic value of these genes was assessed according to a literature review and Kaplan-Meier survival analysis. In addition, a multivariate Cox regression analysis revealed PRICKLE1 expression to be an independent prognostic factor for patients with gastric cancer. Furthermore, a predictive nomogram was generated using PRICKLE1 expression, patient age and TNM stage to assess overall survival (OS) rate at 1, 3 and 5 years, with an internal concordance index of 0.65. External validation was conducted in an independent cohort of 59 patients with gastric cancer, and high consistency between the predicted and observed results for OS was exhibited. Overall, the current findings suggest that PRICKLE1 expression may serve as an independent prognostic factor that can be integrated with age and TNM stage in a nomogram able to predict OS rate in patients with gastric cancer.
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Affiliation(s)
- Yongfeng Ding
- Cancer Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310003, P.R. China.,Key Laboratory of Precision Diagnosis and Treatment for Hepatobiliary and Pancreatic Tumor of Zhejiang Province, Hangzhou, Zhejiang 310003, P.R. China
| | - Yanyan Chen
- Cancer Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310003, P.R. China.,Key Laboratory of Precision Diagnosis and Treatment for Hepatobiliary and Pancreatic Tumor of Zhejiang Province, Hangzhou, Zhejiang 310003, P.R. China
| | - Mengjie Wu
- Cancer Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310003, P.R. China.,Key Laboratory of Precision Diagnosis and Treatment for Hepatobiliary and Pancreatic Tumor of Zhejiang Province, Hangzhou, Zhejiang 310003, P.R. China
| | - Linrong Li
- Department of Otorhinolaryngology, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310000, P.R. China
| | - Yingying Huang
- Key Laboratory of Precision Diagnosis and Treatment for Hepatobiliary and Pancreatic Tumor of Zhejiang Province, Hangzhou, Zhejiang 310003, P.R. China
| | - Haiyong Wang
- Cancer Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310003, P.R. China.,Key Laboratory of Precision Diagnosis and Treatment for Hepatobiliary and Pancreatic Tumor of Zhejiang Province, Hangzhou, Zhejiang 310003, P.R. China
| | - Haohao Wang
- Cancer Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310003, P.R. China.,Key Laboratory of Precision Diagnosis and Treatment for Hepatobiliary and Pancreatic Tumor of Zhejiang Province, Hangzhou, Zhejiang 310003, P.R. China
| | - Xiongfei Yu
- Cancer Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310003, P.R. China.,Key Laboratory of Precision Diagnosis and Treatment for Hepatobiliary and Pancreatic Tumor of Zhejiang Province, Hangzhou, Zhejiang 310003, P.R. China
| | - Nong Xu
- Cancer Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310003, P.R. China
| | - Lisong Teng
- Cancer Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310003, P.R. China.,Key Laboratory of Precision Diagnosis and Treatment for Hepatobiliary and Pancreatic Tumor of Zhejiang Province, Hangzhou, Zhejiang 310003, P.R. China
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19
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Dynamic prediction of cancer-specific survival for primary hypopharyngeal squamous cell carcinoma. Int J Clin Oncol 2020; 25:1260-1269. [PMID: 32266595 DOI: 10.1007/s10147-020-01671-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Accepted: 03/30/2020] [Indexed: 02/07/2023]
Abstract
OBJECTIVES This study investigated a large cohort of patients to construct a predictive nomogram and a web-based survival rate calculator for dynamically predicting the cancer-specific survival of patients with primary hypopharyngeal squamous cell carcinoma (HSCC). METHODS Patients (n = 2007) initially diagnosed with primary HSCC from 2004 to 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. All patients were randomly divided into the training and validation cohorts (1:1). The Lasso Cox regression model was applied to identify independent risk factors of cancer-specific survival for a predictive nomogram and a web-based calculator. The model was evaluated by concordance index, calibration, and decision curve analysis. RESULTS Cancer-specific survival rates decreased with time, while 3-year conditional survival increased. Cancer-specific deaths evolved from relatively high within the first 3 years to low thereafter. Age, race, T stage, N stage, M stage, surgery, radiotherapy, chemotherapy, and marital status were identified as independent risk factors. We constructed a predictive nomogram for survival and a web-based calculator ( https://linzhongyang.shinyapps.io/Hypopharyngeal/ ). Additionally, a prognostic risk stratification was developed according to nomogram total points. CONCLUSIONS Patients with primary HSCC were found at a high risk of cancer-specific death during the first 3 years, indicating that additional effective follow-up strategies should be implemented over the period. This is the first study to construct a predictive nomogram and a web-based calculator for all patients with HSCC.
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Zhao C, Wei Y, Chen D, Jin J, Chen H. Prognostic value of an inflammatory biomarker-based clinical algorithm in septic patients in the emergency department: An observational study. Int Immunopharmacol 2020; 80:106145. [PMID: 31955067 DOI: 10.1016/j.intimp.2019.106145] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Revised: 12/02/2019] [Accepted: 12/20/2019] [Indexed: 01/08/2023]
Abstract
BACKGROUND To develop an inflammatory biomarker-based, simple-to-use nomogram for the early identification of septic patients at high risk of mortality in the emergency department (ED). METHODS All patients diagnosed with sepsis admitted to the intensive care unit (ICU) from the ED were screened from the Medical Information Mart for Intensive Care III database and divided into two cohorts: the primary cohort and the validation cohort. We used bivariate logistic regression analysis to determine independent risk factors and to construct a predictive nomogram and subsequently evaluated the calibration, discrimination and clinical usefulness of the nomogram. The gradient boosting machine (GBM) model was used to more accurately evaluate these variables. RESULTS A total of 5663 admissions were enrolled, of which 3964 comprised the primary cohort and 1699 comprised the validation group, with 28-day mortality rates of 21.2% and 20.4%, respectively. Age > 69, neutrophil-to-lymphocyte ratio (NLR) > 9.8, platelet-to-lymphocyte ratio (PLR) > 249.89, lymphocyte-to-monocyte ratio (LMR) ≤ 2.18, and red cell distribution width (RDW) were detected as important determinants of 28-day mortality and included in the nomogram. The calibration plot revealed an adequate fit of the nomogram for predicting the risk of 28-day mortality. Regarding discriminative ability, receiver operating characteristic curve analysis showed that the nomogram had an area under the curve (AUC) of 0.826 (95% CI: 0.811-0.841, P < 0.001) in the primary cohort, which was greater than that of all individual parameters and other scores. Decision curve analysis also indicated that our nomogram was feasible in clinical practice, as the threshold probabilities were 0-0.62 for the primary cohort. The GBM model yielded a significantly greater AUC of up to 0.867. CONCLUSIONS This proposed simple-to-use nomogram based on age, NLR, PLR, LMR and RDW provides a relatively accurate mortality prediction for septic patients in the ED.
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Affiliation(s)
- Chenyan Zhao
- Department of Intensive Care Medicine, The First Affiliated Hospital of Soochow University, Suzhou 215000, Jiangsu, China
| | - Yao Wei
- Department of Intensive Care Medicine, The First Affiliated Hospital of Soochow University, Suzhou 215000, Jiangsu, China
| | - Dongyu Chen
- Department of Intensive Care Medicine, Yancheng City No. 1 People's Hospital, Yancheng 224000, Jiangsu, China
| | - Jun Jin
- Department of Intensive Care Medicine, The First Affiliated Hospital of Soochow University, Suzhou 215000, Jiangsu, China
| | - Hui Chen
- Department of Intensive Care Medicine, The First Affiliated Hospital of Soochow University, Suzhou 215000, Jiangsu, China.
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21
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Jeong SH, Kim RB, Park SY, Park J, Jung EJ, Ju YT, Jeong CY, Park M, Ko GH, Song DH, Koh HM, Kim WH, Yang HK, Lee YJ, Hong SC. Nomogram for predicting gastric cancer recurrence using biomarker gene expression. Eur J Surg Oncol 2020; 46:195-201. [DOI: 10.1016/j.ejso.2019.09.143] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2019] [Accepted: 09/17/2019] [Indexed: 02/07/2023] Open
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22
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Ma M, Xiao H, Li L, Yin X, Zhou H, Quan H, Ouyang Y, Huang G, Li X, Xiao H. Development and validation of a prognostic nomogram for predicting early recurrence after curative resection of stage II/III gastric cancer. World J Surg Oncol 2019; 17:223. [PMID: 31856828 PMCID: PMC6923869 DOI: 10.1186/s12957-019-1750-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Accepted: 11/14/2019] [Indexed: 12/24/2022] Open
Abstract
Background The biological behavior of early recurrence is more invasive and the prognosis is worse in gastric cancer (GC). The risk of early recurrence (ER) for GC in stage II/III has not been reported of which the majority of GC patients are in China. Therefore, it is necessary to analyze the ER of gastric cancer in stage II/III. Methods The medical records of 1511 consecutive stage II/III GC patients who received resections were retrospectively reviewed. They were randomly classified into either a development or validation group at a ratio of 7:3. The nomogram was constructed based on prognostic factors using logistic regression analysis and was validated by bootstrap resampling and validation dataset, respectively. Concordance index (C-index) values and calibration curves were used to evaluate the predictive accuracy and discriminatory capability. Results Three hundred eleven patients experienced ER, accounting for 20.58% of the GC patients investigated. Multivariate logistic regression analysis identified tumors located at upper, middle third, or mixed, a positive lymph node ratio ≥ 0.335, pTNM stage III, lymphocyte count < 1.5 × 109/L, postoperative infection complications and adjuvant chemotherapy < 6 cycles were all independent predictors for ER after curative resection of stage II/III GC. The C-index value obtained for the model was 0.780 (95% CI, 0.747–0.813), and the calibration curves of validation group yielded a C-index value of 0.739 (95% CI, 0.684–0.794), suggesting the practicability of the model. Conclusions The nomogram which was developed for predicting ER of stage II/III GC after surgery had good accuracy and was verified through both internal and external validation. The nomogram established can assist clinicians in determining the optimal therapy strategies in counseling, adjuvant treatments, and subsequent follow-up planning.
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Affiliation(s)
- Min Ma
- Postdoctoral Research Station of Clinical Medicine, The Third Xiangya Hospital of Central South University, Changsha, 410013, China.,Department of Gastrointestinal Surgery, The Third Xiangya Hospital of Central South University, Changsha, 410013, China
| | - Haifan Xiao
- Department of Cancer Prevention and Control, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, 410013, China
| | - Liang Li
- Clinical school of medicine, University of South China, Hengyang, 421000, China
| | - Xianli Yin
- Department of Gastroenterology and Urology, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, 410013, China
| | - Huijun Zhou
- Department of Gastroenterology and Urology, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, 410013, China
| | - Hu Quan
- Department of Gastroduodenal and Pancreatic Surgery, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, 283 Tongzipo Road, Changsha, 410013, China
| | - Yongzhong Ouyang
- Department of Gastroduodenal and Pancreatic Surgery, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, 283 Tongzipo Road, Changsha, 410013, China
| | - Gang Huang
- Department of Gastroduodenal and Pancreatic Surgery, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, 283 Tongzipo Road, Changsha, 410013, China
| | - Xiaorong Li
- Department of Gastrointestinal Surgery, The Third Xiangya Hospital of Central South University, Changsha, 410013, China.
| | - Hua Xiao
- Department of Gastroduodenal and Pancreatic Surgery, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, 283 Tongzipo Road, Changsha, 410013, China.
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Que SJ, Chen QY, Qing-Zhong, Liu ZY, Wang JB, Lin JX, Lu J, Cao LL, Lin M, Tu RH, Huang ZN, Lin JL, Zheng HL, Li P, Zheng CH, Huang CM, Xie JW. Application of preoperative artificial neural network based on blood biomarkers and clinicopathological parameters for predicting long-term survival of patients with gastric cancer. World J Gastroenterol 2019; 25:6451-6464. [PMID: 31798281 PMCID: PMC6881508 DOI: 10.3748/wjg.v25.i43.6451] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Revised: 09/17/2019] [Accepted: 10/17/2019] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Because of the powerful abilities of self-learning and handling complex biological information, artificial neural network (ANN) models have been widely applied to disease diagnosis, imaging analysis, and prognosis prediction. However, there has been no trained preoperative ANN (preope-ANN) model to preoperatively predict the prognosis of patients with gastric cancer (GC). AIM To establish a neural network model that can predict long-term survival of GC patients before surgery to evaluate the tumor condition before the operation. METHODS The clinicopathological data of 1608 GC patients treated from January 2011 to April 2015 at the Department of Gastric Surgery, Fujian Medical University Union Hospital were analyzed retrospectively. The patients were randomly divided into a training set (70%) for establishing a preope-ANN model and a testing set (30%). The prognostic evaluation ability of the preope-ANN model was compared with that of the American Joint Commission on Cancer (8th edition) clinical TNM (cTNM) and pathological TNM (pTNM) staging through the receiver operating characteristic curve, Akaike information criterion index, Harrell's C index, and likelihood ratio chi-square. RESULTS We used the variables that were statistically significant factors for the 3-year overall survival as input-layer variables to develop a preope-ANN in the training set. The survival curves within each score of the preope-ANN had good discrimination (P < 0.05). Comparing the preope-ANN model, cTNM, and pTNM in both the training and testing sets, the preope-ANN model was superior to cTNM in predictive discrimination (C index), predictive homogeneity (likelihood ratio chi-square), and prediction accuracy (area under the curve). The prediction efficiency of the preope-ANN model is similar to that of pTNM. CONCLUSION The preope-ANN model can accurately predict the long-term survival of GC patients, and its predictive efficiency is not inferior to that of pTNM stage.
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Affiliation(s)
- Si-Jin Que
- Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
- Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou 350108, Fujian Province, China
- Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou 350108, Fujian Province, China
| | - Qi-Yue Chen
- Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
- Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou 350108, Fujian Province, China
- Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou 350108, Fujian Province, China
| | - Qing-Zhong
- Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
- Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou 350108, Fujian Province, China
- Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou 350108, Fujian Province, China
| | - Zhi-Yu Liu
- Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
- Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou 350108, Fujian Province, China
- Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou 350108, Fujian Province, China
| | - Jia-Bin Wang
- Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
- Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou 350108, Fujian Province, China
- Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou 350108, Fujian Province, China
| | - Jian-Xian Lin
- Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
- Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou 350108, Fujian Province, China
- Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou 350108, Fujian Province, China
| | - Jun Lu
- Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
- Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou 350108, Fujian Province, China
- Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou 350108, Fujian Province, China
| | - Long-Long Cao
- Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
- Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou 350108, Fujian Province, China
- Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou 350108, Fujian Province, China
| | - Mi Lin
- Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
- Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou 350108, Fujian Province, China
- Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou 350108, Fujian Province, China
| | - Ru-Hong Tu
- Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
- Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou 350108, Fujian Province, China
- Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou 350108, Fujian Province, China
| | - Ze-Ning Huang
- Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
- Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou 350108, Fujian Province, China
- Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou 350108, Fujian Province, China
| | - Ju-Li Lin
- Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
- Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou 350108, Fujian Province, China
- Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou 350108, Fujian Province, China
| | - Hua-Long Zheng
- Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
- Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou 350108, Fujian Province, China
- Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou 350108, Fujian Province, China
| | - Ping Li
- Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
- Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou 350108, Fujian Province, China
- Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou 350108, Fujian Province, China
| | - Chao-Hui Zheng
- Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
- Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou 350108, Fujian Province, China
- Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou 350108, Fujian Province, China
| | - Chang-Ming Huang
- Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
- Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou 350108, Fujian Province, China
- Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou 350108, Fujian Province, China
| | - Jian-Wei Xie
- Department of Gastric Surgery and Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
- Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou 350108, Fujian Province, China
- Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou 350108, Fujian Province, China
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Sun W, Cheng M, Zhuang S, Chen H, Yang S, Qiu Z. Nomograms to predict survival of stage IV tongue squamous cell carcinoma after surgery. Medicine (Baltimore) 2019; 98:e16206. [PMID: 31261568 PMCID: PMC6616315 DOI: 10.1097/md.0000000000016206] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
To develop clinical nomograms for prediction of overall survival (OS) and cancer-specific survival (CSS) in patients with stage IV tongue squamous cell carcinoma (TSCC) after surgery based on the Surveillance, Epidemiology, and End Results (SEER) program database.We collected data of resected stage IV TSCC patients from the SEER database, and divided them into the training set and validation set by 7:3 randomly. Kaplan-Meier analysis and Cox regression analysis were adopted to distinguish independent risk factors for OS and CSS. Clinical nomograms were constructed to predict the 3-year and 5-year probabilities of OS and CSS for individual patients. Calibration curves and Harrell C-indices were used for internal and external validation.A total of 1550 patients with resected stage IV TSCC were identified. No statistical differences were detected between the training and validation sets. Age, race, marital status, tumor site, AJCC T/N/M status, and radiotherapy were recognized as independent prognostic factors associated with OS as well as CSS. Then nomograms were developed based on these variables. The calibration curves displayed a good agreement between the predicted and actual values of 3-year and 5-year probabilities for OS and CSS. The C-indices predicting OS were corrected as 0.705 in the training set, and 0.664 in the validation set. As for CSS, corrected C-indices were 0.708 in the training set and 0.663 in the validation set.The established nomograms in this study exhibited good accuracy and effectiveness to predict 3-year and 5-year probabilities of OS and CSS in resected stage IV TSCC patients. They are useful tools to evaluate survival outcomes and helped choose appropriate treatment strategies.
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Affiliation(s)
- Wei Sun
- Department of Anesthesiology, The First Affiliated Hospital of Shantou University Medical College
| | - Minghua Cheng
- Department of Anesthesiology, The First Affiliated Hospital of Shantou University Medical College
| | - Shaohui Zhuang
- Department of Anesthesiology, The First Affiliated Hospital of Shantou University Medical College
| | - Huimin Chen
- Department of Stomatology, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, People's Republic of China
| | - Shaohui Yang
- Department of Anesthesiology, The First Affiliated Hospital of Shantou University Medical College
| | - Zeting Qiu
- Department of Anesthesiology, The First Affiliated Hospital of Shantou University Medical College
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25
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Manouchehrinia A, Zhu F, Piani-Meier D, Lange M, Silva DG, Carruthers R, Glaser A, Kingwell E, Tremlett H, Hillert J. Predicting risk of secondary progression in multiple sclerosis: A nomogram. Mult Scler 2018; 25:1102-1112. [PMID: 29911467 DOI: 10.1177/1352458518783667] [Citation(s) in RCA: 55] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
OBJECTIVES We aimed at designing a nomogram, a prediction tool, to predict the individual's risk of conversion to secondary progressive multiple sclerosis (SPMS) at the time of multiple sclerosis (MS) onset. METHODS One derivation and three validation cohorts were established. The derivation cohort included 8825 relapsing-onset MS patients in Sweden. A nomogram was built based on a survival model with the best statistical fit and prediction accuracy. The nomogram was validated using data from 3967 patients in the British Columbia cohort, 176 patients in the ACROSS and 2355 patients in FREEDOMS/FREEDOMS II extension studies. RESULTS Sex, calendar year of birth, first-recorded Expanded Disability Status Scale (EDSS) score, age at the first EDSS and age at disease onset showed significant predictive ability to estimate the risk of SPMS conversion at 10, 15 and 20 years. The nomogram reached 84% (95% confidence intervals (CIs): 83-85) internal and 77% (95% CI: 76-78), 77% (95% CI: 70-85) and 87% (95% CI: 84-89) external accuracy. CONCLUSIONS The SPMS nomogram represents a much-needed complementary tool designed to assist in decision-making and patient counselling in the early phase of MS. The SPMS nomogram may improve outcomes by prompting timely and more efficacious treatment for those with a worse prognosis.
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Affiliation(s)
- Ali Manouchehrinia
- Department of Clinical Neuroscience (CNS), Karolinska Institutet, Stockholm, Sweden
| | - Feng Zhu
- Division of Neurology, UBC Hospital, Faculty of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | | | | | | | - Robert Carruthers
- Division of Neurology, UBC Hospital, Faculty of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Anna Glaser
- Department of Clinical Neuroscience (CNS), Karolinska Institutet, Stockholm, Sweden
| | - Elaine Kingwell
- Division of Neurology, UBC Hospital, Faculty of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Helen Tremlett
- Division of Neurology, UBC Hospital, Faculty of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Jan Hillert
- Department of Clinical Neuroscience (CNS), Karolinska Institutet, Stockholm, Sweden
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26
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Chen S, Rao H, Liu J, Geng Q, Guo J, Kong P, Li S, Liu X, Sun X, Zhan Y, Xu D. Lymph nodes ratio based nomogram predicts survival of resectable gastric cancer regardless of the number of examined lymph nodes. Oncotarget 2018; 8:45585-45596. [PMID: 28489596 PMCID: PMC5542210 DOI: 10.18632/oncotarget.17276] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2017] [Accepted: 03/27/2017] [Indexed: 12/14/2022] Open
Abstract
To develop a nomogram to predict the prognosis of gastric cancer patients on the basis of metastatic lymph nodes ratio (mLNR), especially in the patients with total number of examined lymph nodes (TLN) less than 15. The nomogram was constructed based on a retrospective database that included 2,205 patients underwent curative resection in Cancer Center, Sun Yat-sen University (SYSUCC). Resectable gastric cancer (RGC) patients underwent curative resection before December 31, 2008 were assigned as the training set (n=1,470) and those between January 1, 2009 and December 31, 2012 were selected as the internal validation set (n=735). Additional external validations were also performed separately by an independent data set (n=602) from Jiangxi Provincial Cancer Hospital (JXCH) in Jiangxi, China and a data set (n=3,317) from the Surveillance, Epidemiology, and End Results (SEER) database. The Independent risk factors were identified by Multivariate Cox Regression. In the SYSUCC set, TNM (Tumor-node-metastasis) and TRM-based (Tumor-Positive Nodes Ratio-Metastasis) nomograms were constructed respectively. The TNM-based nomogram showed better discrimination than the AJCC-TNM staging system (C-index: 0.73 versus 0.69, p<0.01). When the mLNR was included in the nomogram, the C-index increased to 0.76. Furthermore, the C-index in the TRM-based nomogram was similar between TLN ≥16 (C-index: 0.77) and TLN ≤15 (C-index: 0.75). The discrimination was further ascertained by internal and external validations. We developed and validated a novel TRM-based nomogram that provided more accurate prediction of survival for gastric cancer patients who underwent curative resection, regardless of the number of examined lymph nodes.
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Affiliation(s)
- Shangxiang Chen
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Gastric and Pancreatic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Huamin Rao
- Department of Abdominal Surgery, Jiangxi Cancer Hospital, Nanchang, China
| | - Jianjun Liu
- Department of Breast Surgery, Anhui Provincial Cancer Hospital, West branch of Anhui Provincial Hospital, Hefei, China
| | - Qirong Geng
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Hematology Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Jing Guo
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Gastric and Pancreatic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Pengfei Kong
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Gastric and Pancreatic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Shun Li
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Gastric and Pancreatic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Xuechao Liu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Gastric and Pancreatic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Xiaowei Sun
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Gastric and Pancreatic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Youqing Zhan
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Gastric and Pancreatic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Dazhi Xu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Gastric and Pancreatic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
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27
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Ó Hartaigh B, Gransar H, Callister T, Shaw LJ, Schulman-Marcus J, Stuijfzand WJ, Valenti V, Cho I, Szymonifka J, Lin FY, Berman DS, Chang HJ, Min JK. Development and Validation of a Simple-to-Use Nomogram for Predicting 5-, 10-, and 15-Year Survival in Asymptomatic Adults Undergoing Coronary Artery Calcium Scoring. JACC Cardiovasc Imaging 2018; 11:450-458. [PMID: 28624402 PMCID: PMC5723248 DOI: 10.1016/j.jcmg.2017.03.018] [Citation(s) in RCA: 63] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2016] [Revised: 02/28/2017] [Accepted: 03/07/2017] [Indexed: 12/12/2022]
Abstract
OBJECTIVES The purpose of this study was to develop and validate a simple-to-use nomogram for prediction of 5-, 10-, and 15-year survival among asymptomatic adults. BACKGROUND Simple-to-use prognostication tools that incorporate robust methods such as coronary artery calcium scoring (CACS) for predicting near-, intermediate- and long-term mortality are warranted. METHODS In a consecutive series of 9,715 persons (mean age: 53.4 ± 10.5 years; 59.3% male) undergoing CACS, we developed a nomogram using Cox proportional hazards regression modeling that included: age, sex, smoking, hypertension, dyslipidemia, diabetes, family history of coronary artery disease, and CACS. We developed a prognostic index (PI) summing the number of risk points corresponding to weighted covariates, which was used to configure the nomogram. Validation of the nomogram was assessed by discrimination and calibration applied to a separate cohort of 7,824 adults who also underwent CACS. RESULTS A total of 936 and 294 deaths occurred in the derivation and validation sets at a median follow-up of 14.6 years (interquartile range: 13.7 to 15.5 years) and 9.4 years (interquartile range: 6.8 to 11.5 years), respectively. The developed model effectively predicted 5-, 10-, and 15-year probability of survival. The PI displayed high discrimination in the derivation and validation sets (C-index 0.74 and 0.76, respectively), indicating suitable external performance of our nomogram model. The predicted and actual estimates of survival in each dataset according to PI quartiles were similar (though not identical), demonstrating improved model calibration. CONCLUSIONS A simple-to-use nomogram effectively predicts 5-, 10- and 15-year survival for asymptomatic adults undergoing screening for cardiac risk factors. This nomogram may be considered for use in clinical care.
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Affiliation(s)
- Bríain Ó Hartaigh
- Dalio Institute of Cardiovascular Imaging, New York-Presbyterian Hospital and the Weill Cornell Medical College, New York, New York
| | - Heidi Gransar
- Dalio Institute of Cardiovascular Imaging, New York-Presbyterian Hospital and the Weill Cornell Medical College, New York, New York
| | - Tracy Callister
- Tennessee Heart and Vascular Institute, Hendersonville, Nashville, Tennessee
| | - Leslee J Shaw
- Division of Cardiology, Emory University School of Medicine, Atlanta, Georgia
| | - Joshua Schulman-Marcus
- Dalio Institute of Cardiovascular Imaging, New York-Presbyterian Hospital and the Weill Cornell Medical College, New York, New York
| | - Wijnand J Stuijfzand
- Dalio Institute of Cardiovascular Imaging, New York-Presbyterian Hospital and the Weill Cornell Medical College, New York, New York
| | - Valentina Valenti
- Dalio Institute of Cardiovascular Imaging, New York-Presbyterian Hospital and the Weill Cornell Medical College, New York, New York
| | - Iksung Cho
- Dalio Institute of Cardiovascular Imaging, New York-Presbyterian Hospital and the Weill Cornell Medical College, New York, New York
| | - Jackie Szymonifka
- Dalio Institute of Cardiovascular Imaging, New York-Presbyterian Hospital and the Weill Cornell Medical College, New York, New York
| | - Fay Y Lin
- Dalio Institute of Cardiovascular Imaging, New York-Presbyterian Hospital and the Weill Cornell Medical College, New York, New York
| | - Daniel S Berman
- Department of Imaging, Cedars Sinai Medical Center, Los Angeles, California
| | - Hyuk-Jae Chang
- Division of Cardiology, Severance Cardiovascular Hospital, Seoul, South Korea
| | - James K Min
- Dalio Institute of Cardiovascular Imaging, New York-Presbyterian Hospital and the Weill Cornell Medical College, New York, New York.
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Oh SE, Seo SW, Choi MG, Sohn TS, Bae JM, Kim S. Prediction of Overall Survival and Novel Classification of Patients with Gastric Cancer Using the Survival Recurrent Network. Ann Surg Oncol 2018; 25:1153-1159. [PMID: 29497908 DOI: 10.1245/s10434-018-6343-7] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2017] [Indexed: 12/15/2022]
Abstract
BACKGROUND Artificial neural networks (ANNs) have been applied to many prediction and classification problems, and could also be used to develop a prediction model of survival outcomes for cancer patients. OBJECTIVE The aim of this study is to develop a prediction model of survival outcomes for patients with gastric cancer using an ANN. METHODS This study enrolled 1243 patients with stage IIA-IV gastric cancer who underwent D2 gastrectomy from January 2007 to June 2010. We used a recurrent neural network (RNN) to make the survival recurrent network (SRN), and patients were randomly sorted into a training set (80%) and a test set (20%). Fivefold cross-validation was performed with the training set, and the optimized model was evaluated with the test set. Receiver operating characteristic (ROC) curves and area under the curves (AUCs) were evaluated, and we compared the survival curves of the American Joint Committee on Cancer (AJCC) 8th stage groups with those of the groups classified by the SRN-predicted survival probability. RESULTS The test data showed that the ROC AUC of the SRN was 0.81 at the fifth year. The SRN-predicted survival corresponded closely with the actual survival in the calibration curve, and the survival outcome could be more discriminately classified by using the SRN than by using the AJCC staging system. CONCLUSION SRN was a more powerful tool for predicting the survival rates of gastric cancer patients than conventional TNM staging, and may also provide a more flexible and expandable method when compared with fixed prediction models such as nomograms.
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Affiliation(s)
- Sung Eun Oh
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Sung Wook Seo
- Department of Orthopedic Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
| | - Min-Gew Choi
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
| | - Tae Sung Sohn
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Jae Moon Bae
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Sung Kim
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
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van den Boorn HG, Engelhardt EG, van Kleef J, Sprangers MAG, van Oijen MGH, Abu-Hanna A, Zwinderman AH, Coupé VMH, van Laarhoven HWM. Prediction models for patients with esophageal or gastric cancer: A systematic review and meta-analysis. PLoS One 2018; 13:e0192310. [PMID: 29420636 PMCID: PMC5805284 DOI: 10.1371/journal.pone.0192310] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2017] [Accepted: 01/22/2018] [Indexed: 02/06/2023] Open
Abstract
Background Clinical prediction models are increasingly used to predict outcomes such as survival in cancer patients. The aim of this study was threefold. First, to perform a systematic review to identify available clinical prediction models for patients with esophageal and/or gastric cancer. Second, to evaluate sources of bias in the included studies. Third, to investigate the predictive performance of the prediction models using meta-analysis. Methods MEDLINE, EMBASE, PsycINFO, CINAHL, and The Cochrane Library were searched for publications from the year 2000 onwards. Studies describing models predicting survival, adverse events and/or health-related quality of life (HRQoL) for esophageal or gastric cancer patients were included. Potential sources of bias were assessed and a meta-analysis, pooled per prediction model, was performed on the discriminative abilities (c-indices). Results A total of 61 studies were included (45 development and 16 validation studies), describing 47 prediction models. Most models predicted survival after a curative resection. Nearly 75% of the studies exhibited bias in at least 3 areas and model calibration was rarely reported. The meta-analysis showed that the averaged c-index of the models is fair (0.75) and ranges from 0.65 to 0.85. Conclusion Most available prediction models only focus on survival after a curative resection, which is only relevant to a limited patient population. Few models predicted adverse events after resection, and none focused on patient’s HRQoL, despite its relevance. Generally, the quality of reporting is poor and external model validation is limited. We conclude that there is a need for prediction models that better meet patients’ information needs, and provide information on both the benefits and harms of the various treatment options in terms of survival, adverse events and HRQoL.
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Affiliation(s)
- H. G. van den Boorn
- Cancer Center Amsterdam, Amsterdam, The Netherlands
- Department of Medical Oncology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
- * E-mail:
| | - E. G. Engelhardt
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands
| | - J. van Kleef
- Cancer Center Amsterdam, Amsterdam, The Netherlands
- Department of Medical Oncology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - M. A. G. Sprangers
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Department of Medical Psychology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - M. G. H. van Oijen
- Cancer Center Amsterdam, Amsterdam, The Netherlands
- Department of Medical Oncology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - A. Abu-Hanna
- Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - A. H. Zwinderman
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - V. M. H. Coupé
- Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands
| | - H. W. M. van Laarhoven
- Cancer Center Amsterdam, Amsterdam, The Netherlands
- Department of Medical Oncology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
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30
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Liu J, Geng Q, Liu Z, Chen S, Guo J, Kong P, Chen Y, Li W, Zhou Z, Sun X, Zhan Y, Xu D. Development and external validation of a prognostic nomogram for gastric cancer using the national cancer registry. Oncotarget 2017; 7:35853-35864. [PMID: 27016409 PMCID: PMC5094968 DOI: 10.18632/oncotarget.8221] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2015] [Accepted: 02/28/2016] [Indexed: 02/06/2023] Open
Abstract
A nomogram based on both western and eastern populations to estimate the Disease Specific Survival (DSS) of resectable gastric cancer (RGC) has not been established. In current study, we retrospectively analyzed 4,379 RGC patients who underwent curative resection from the Surveillance, Epidemiology, and End Results (SEER) database. Patients diagnosed between 1998 and 2009 were assigned as training set (n= 2,770), and the rest were selected as SEER validation set (n= 1,609). An external validation was performed by a set of independent 1,358 RGC patients after D2 resection from Sun Yat–sen University Cancer Center (SYSUCC) in China. The nomogram was constructed based on the training set. The multivariate analysis identified that patient's age at diagnosis, race, tumor location, grade, depth of invasion, metastatic lymph node stage (mLNS) and total number of examined lymph node (TLN) were associated with patient's DSS. The discrimination of this nomogram was superior to that of the 7th edition of AJCC staging system in SEER validation set and SYSUCC validation set (0.73 versus 0.70, p=0.005; 0.76 versus 0.72, p=0.005; respectively). Calibration plots of the nomogram showed that the probability of DSS corresponded to actual observation closely. In conclusion, our nomogram resulted in more–reliable prognostic prediction for RGC patients in general population.
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Affiliation(s)
- Jianjun Liu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Gastric and Pancreatic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Qirong Geng
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Hematology Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Zhimin Liu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Gastric and Pancreatic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Shangxiang Chen
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Gastric and Pancreatic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Jing Guo
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Gastric and Pancreatic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Pengfei Kong
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Gastric and Pancreatic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - YingBo Chen
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Gastric and Pancreatic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Wei Li
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Gastric and Pancreatic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Zhiwei Zhou
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Gastric and Pancreatic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Xiaowei Sun
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Gastric and Pancreatic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Youqing Zhan
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Gastric and Pancreatic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Dazhi Xu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Gastric and Pancreatic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
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A calculator for mortality following emergency general surgery based on the American College of Surgeons National Surgical Quality Improvement Program database. J Trauma Acute Care Surg 2017; 82:1094-1099. [PMID: 28328681 DOI: 10.1097/ta.0000000000001451] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND The complex nature of current morbidity and mortality predictor models do not lend themselves to clinical application at the bedside of patients undergoing emergency general surgery (EGS). Our aim was to develop a simplified risk calculator for prediction of early postoperative mortality after EGS. METHODS EGS cases other than appendectomy and cholecystectomy were identified within the American College of Surgeons National Surgery Quality Improvement Program database from 2005 to 2014. Seventy-five percent of the cases were selected at random for model development, whereas 25% of the cases were used for model testing. Stepwise logistic regression was performed for creation of a 30-day mortality risk calculator. Model accuracy and reproducibility was investigated using the concordance index (c statistic) and Pearson correlations. RESULTS A total of 79,835 patients met inclusion criteria. Overall, 30-day mortality was 12.6%. A simplified risk model formula was derived from five readily available preoperative variables as follows: 0.034*age + 0.8*nonindependent status + 0.88*sepsis + 1.1 (if bun ≥ 29) or 0.57 (if bun ≥18 and < 29) + 1.16 (if albumin < 2.7), or 0.61 (if albumin ≥ 2.7 and < 3.4). The risk of 30-day mortality was stratified into deciles. The risk of 30-day mortality ranged from 2% for patients in the lowest risk level to 31% for patients in the highest risk level. The c statistic was 0.83 in both the derivation and testing samples. CONCLUSION Five readily available preoperative variables can be used to predict the 30-day mortality risk for patients undergoing EGS. Further studies are needed to validate this risk calculator and to determine its bedside applicability. LEVEL OF EVIDENCE Prognostic/epidemiological study, level III.
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32
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Jiang Y, Li T, Liang X, Hu Y, Huang L, Liao Z, Zhao L, Han Z, Zhu S, Wang M, Xu Y, Qi X, Liu H, Yang Y, Yu J, Liu W, Cai S, Li G. Association of Adjuvant Chemotherapy With Survival in Patients With Stage II or III Gastric Cancer. JAMA Surg 2017; 152:e171087. [PMID: 28538950 PMCID: PMC5831463 DOI: 10.1001/jamasurg.2017.1087] [Citation(s) in RCA: 106] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2016] [Accepted: 03/08/2017] [Indexed: 12/12/2022]
Abstract
IMPORTANCE The current staging system of gastric cancer is not adequate for defining a prognosis and predicting the patients most likely to benefit from chemotherapy. OBJECTIVE To construct a survival prediction model based on specific tumor and patient characteristics that enables individualized predictions of the net survival benefit of adjuvant chemotherapy for patients with stage II or stage III gastric cancer. DESIGN, SETTING, AND PARTICIPANTS In this multicenter retrospective analysis, a survival prediction model was constructed using data from a training cohort of 746 patients with stage II or stage III gastric cancer who satisfied the study's inclusion criteria and underwent surgery between January 1, 2004, and December 31, 2012, at Nanfang Hospital in Guangzhou, China. Patient and tumor characteristics were included as covariates, and their association with overall survival and disease-free survival with and without adjuvant chemotherapy was assessed. The model was internally validated for discrimination and calibration using bootstrap resampling. To externally validate the model, data were included from a validation cohort of 973 patients with stage II or stage III gastric cancer who met the inclusion criteria and underwent surgery at First Affiliated Hospital in Guangzhou, China, and at West China Hospital of Sichuan Hospital in Chendu, China, between January 1, 2000, and June 30, 2009. Data were analyzed from July 10, 2016, to September 1, 2016. MAIN OUTCOMES AND MEASURES Concordance index and decision curve analysis for each measure associated with postoperative overall survival and disease-free survival. RESULTS Of the 1719 patients analyzed, 1183 (68.8%) were men and 536 (31.2%) were women and the median (interquartile range) age was 57 (49-66) years. Age, location, differentiation, carcinoembryonic antigen, cancer antigen 19-9, depth of invasion, lymph node metastasis, and adjuvant chemotherapy were significantly associated with overall survival and disease-free survival, with P < .05. The survival prediction model demonstrated good calibration and discrimination, with relatively high bootstrap-corrected concordance indexes in the training and validation cohorts. In the validation cohort, the concordance index for overall survival was 0.693 (95% CI, 0.671-0.715) and for disease-free survival was 0.704 (95% CI, 0.681-0.728). Two nomograms and a calculating tool were built on the basis of specific input variables to estimate an individual's net survival gain attributable to adjuvant chemotherapy. CONCLUSIONS AND RELEVANCE The survival prediction model can be used to make individualized predictions of the expected survival benefit from the addition of adjuvant chemotherapy for patients with stage II or stage III gastric cancer.
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Affiliation(s)
- Yuming Jiang
- Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China
- Guangdong Key Laboratory of Liver Disease Research, Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Tuanjie Li
- Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China
- Guangdong Key Laboratory of Liver Disease Research, Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xiaoling Liang
- Department of Pharmacy, Nanfang Hospital, Southern Medical University, Guangzhou, China
- School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, China
| | - Yanfeng Hu
- Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Lei Huang
- German Cancer Research Center (Deutsches Krebsforschungszentrum), Heidelberg, Germany
| | - Zhenchen Liao
- Department of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Liying Zhao
- Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Zhen Han
- Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Shuguang Zhu
- Guangdong Key Laboratory of Liver Disease Research, Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Department of Hepatic Surgery, Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Menglan Wang
- Guangdong Key Laboratory of Liver Disease Research, Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Department of Infectious Disease, Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yangwei Xu
- Department of Pathology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
| | - Xiaolong Qi
- Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Hao Liu
- Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yang Yang
- Guangdong Key Laboratory of Liver Disease Research, Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Department of Hepatic Surgery, Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Jiang Yu
- Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Wei Liu
- Guangdong Key Laboratory of Liver Disease Research, Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Department of Hepatic Surgery, Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Shirong Cai
- Department of Gastrointestinal Surgery, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Guoxin Li
- Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China
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A Novel Prediction Model of Prognosis After Gastrectomy for Gastric Carcinoma: Development and Validation Using Asian Databases. Ann Surg 2017; 264:114-20. [PMID: 26945155 DOI: 10.1097/sla.0000000000001523] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
OBJECTIVE The prognoses of gastric cancer patients vary greatly among countries. Meanwhile, tumor-node-metastasis (TNM) staging system shows limited accuracy in predicting patient-specific survival for gastric cancer. The objective of this study was to create a simple, yet universally applicable survival prediction model for surgically treated gastric cancer patients. SUMMARY BACKGROUND DATA A prediction model of 5-year overall survival for surgically treated gastric cancer patients regardless of curability was developed using a test data set of 11,851 consecutive patients. METHODS The model's coefficients were selected based on univariate and multivariate analysis of patient, tumor, and surgical factors shown to significantly impact survival using a Cox proportional hazards model. For internal validation, discrimination was calculated with the concordance index (C-statistic) using the bootstrap method and calibration assessed. The model was externally validated using 4 data sets from 3 countries. RESULTS Our model's C-statistic (0.824) showed better discrimination power than current tumor-node-metastasis staging (0.788) (P < 0.0001). Bootstrap internal validation demonstrated that coefficients remained largely unchanged between iterations, with an average C-statistic of 0.822. The model calibration was accurate in predicting 5-year survival. In the external validation, C-statistics showed good discrimination (range: 0.798-0.868) in patient data sets from 4 participating institutions in 3 different countries. CONCLUSIONS Utilizing clinically practical patient, tumor, and surgical information, we developed a universally applicable prediction model for accurately determining the 5-year overall survival of gastric cancer patients after gastrectomy. Our predictive model was also valid in patients who underwent noncurative resection or inadequate lymphadenectomy.
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Haskins IN, Prabhu AS, Krpata DM, Perez AJ, Tastaldi L, Tu C, Rosenblatt S, Poulose BK, Rosen MJ. Is there an association between surgeon hat type and 30-day wound events following ventral hernia repair? Hernia 2017. [DOI: 10.1007/s10029-017-1626-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Muneoka Y, Akazawa K, Ishikawa T, Ichikawa H, Nashimoto A, Yabusaki H, Tanaka N, Kosugi SI, Wakai T. Nomogram for 5-year relapse-free survival of a patient with advanced gastric cancer after surgery. Int J Surg 2016; 35:153-159. [PMID: 27664559 DOI: 10.1016/j.ijsu.2016.09.080] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2016] [Accepted: 09/19/2016] [Indexed: 11/30/2022]
Abstract
BACKGROUND Prognoses vary substantially among patients with advanced gastric cancer following curative surgery. The aim of the current study was to develop and verify the validity of a novel nomogram that predicts the probability of 5-year relapse-free survival (RFS) in patients who underwent curative resection for stage II/III gastric cancer. MATERIALS AND METHODS A nomogram to predict 5-year RFS following surgical resection of gastric cancer was constructed based on the data of patients who underwent surgery for primary gastric carcinoma at three institutions in Japan in January 2001-December 2006. Multivariate analysis using a Cox proportional hazards regression model was performed, and the nomogram's predictive accuracy (discrimination) and the agreement between observed outcomes and predictions (calibration) were evaluated by internal validation. RESULTS Multivariate analyses revealed that age at operation, depth of tumor, tumor location, lymph node classification, and presence of combined resection were significant prognostic factors for RFS. In the internal validation, discrimination of the developed nomogram for 5-year RFS was superior to that of the American Joint Committee on Cancer TNM classification (concordance indices of 0.80 versus 0.67; P < 0.001). Moreover, calibration appeared to be accurate. Based on these results, we have created free software to more easily predict 5-year RFS. CONCLUSION We developed and validated a nomogram to predict 5-year RFS after curative surgery for stage II/III gastric cancer. This tool will be useful for the assessing a patient's individual recurrence risk when considering additional therapy in clinical practice.
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Affiliation(s)
- Yusuke Muneoka
- Division of Digestive and General Surgery, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan; Department of Medical Informatics, Niigata University Medical and Dental Hospital, Niigata, Japan.
| | - Kohei Akazawa
- Department of Medical Informatics, Niigata University Medical and Dental Hospital, Niigata, Japan
| | - Takashi Ishikawa
- Division of Digestive and General Surgery, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan; Department of Medical Informatics, Niigata University Medical and Dental Hospital, Niigata, Japan
| | - Hiroshi Ichikawa
- Division of Digestive and General Surgery, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
| | | | - Hiroshi Yabusaki
- Department of Surgery, Niigata Cancer Center Hospital, Niigata, Japan
| | - Norio Tanaka
- Department of Surgery, Shibata Prefectural Hospital, Niigata, Japan
| | - Shin-Ichi Kosugi
- Department of Digestive and General Surgery, Uonuma Institute of Community Medicine, Niigata University Medical and Dental Hospital, Niigata, Japan
| | - Toshifumi Wakai
- Division of Digestive and General Surgery, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
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Cao L, Selby LV, Hu X, Zhang Y, Janjigian YY, Tang L, Coit DG, Brennan MF, Strong VE. Risk factors for recurrence in T1-2N0 gastric cancer in the United States and China. J Surg Oncol 2016; 113:745-9. [PMID: 27040753 DOI: 10.1002/jso.24228] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2016] [Accepted: 03/10/2016] [Indexed: 12/24/2022]
Abstract
INTRODUCTION Recurrence patterns after curative intent gastrectomy for T1-2N0 gastric adenocarcinoma are poorly defined. We sought to assess timing, patterns, and risk factors for recurrence in patients treated at two high-volume gastric cancer centers in the United States and China. METHODS Between 1995 and 2011, 1,058 patients underwent curative intent gastrectomy. Recurrences were classified as locoregional, distant, or peritoneal. Univariate and multivariate analyses were performed to identify risk factors for recurrence. RESULTS Overall, 7% (76) of our 1,058 patients from the United States (n = 414) and China (n = 644) recurred. Liver (43%) was the most common site of recurrence in both countries (US: 24%, China: 52%), followed by peritoneum (16%), lymph nodes (10%), and anastomosis (8%). Median time to recurrence was 23 months (US: 30 months, China: 23 months), which decreased with increasing T-stage (T1a: 27 months, T1b: 24 months, T2: 22 months). Tumor size (P = 0.001), depth of invasion (P = 0.010), histological type (P = 0.022) and lymphovascular invasion (P = 0.001) were independently associated with recurrence. CONCLUSION Patients infrequently recur following curative intent gastrectomy for T1-2N0 gastric adenocarcinoma. Almost all recurrences occur between six months and 3 years post-operatively, most frequently in distant anatomic locations; selective followup during this time period is recommended. J. Surg. Oncol. 2016;113:745-749. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Liang Cao
- Department of General Surgery, The First Affiliated Hospital, Dalian Medical University, Dalian, Liaoning, China
| | - Luke V Selby
- Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York City, New York
| | - Xiang Hu
- Department of General Surgery, The First Affiliated Hospital, Dalian Medical University, Dalian, Liaoning, China
| | - Yi Zhang
- Department of General Surgery, The First Affiliated Hospital, Dalian Medical University, Dalian, Liaoning, China
| | - Yelena Y Janjigian
- Department of Medical Oncology, Memorial Sloan-Kettering Cancer Center, New York City, New York
| | - Laura Tang
- Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York City, New York
| | - Daniel G Coit
- Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York City, New York
| | - Murray F Brennan
- Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York City, New York
| | - Vivian E Strong
- Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York City, New York
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Lee JW, Jo K, Cho A, Noh SH, Lee JD, Yun M. Relationship Between 18F-FDG Uptake on PET and Recurrence Patterns After Curative Surgical Resection in Patients with Advanced Gastric Cancer. J Nucl Med 2015; 56:1494-500. [PMID: 26251414 DOI: 10.2967/jnumed.115.160580] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2015] [Accepted: 07/30/2015] [Indexed: 02/07/2023] Open
Abstract
UNLABELLED This study evaluated the predictive value of 18F-FDG PET for distant metastasis-free survival and peritoneal recurrence-free survival as well as recurrence-free survival and overall survival after curative surgical resection in patients with advanced gastric cancer (AGC). METHODS Two hundred seventy-nine patients with AGC who underwent preoperative 18F-FDG PET and subsequent curative surgical resection were included. The tumor-to-normal liver uptake ratio (TLR) of cancer lesions was measured, and the prognostic significance of TLR and tumor factors for distant metastasis-free survival, peritoneal recurrence-free survival, recurrence-free survival, and overall survival was assessed. RESULTS The 5-y recurrence-free survival, peritoneal recurrence-free survival, distant metastasis-free survival, and overall survival rates were 46.9%, 68.5%, 76.0%, and 58.1%, respectively. Depth of tumor invasion, lymph node metastasis, lymphovascular invasion, and TLR were independent prognostic factors for both recurrence-free survival and overall survival (P<0.05). For distant metastasis-free survival, lymphovascular invasion and TLR were independent risk factors (P<0.05). In patients with a TLR of 2.0 or less, the 5-y distant metastasis-free survival rate was 95.5%; in patients with a TLR greater than 2.0, the 5-y distant metastasis-free survival rate was 68.8%. For peritoneal recurrence-free survival, TLR showed no statistical significance (P=0.7) whereas pT stage, lymph node metastasis, Lauren classification, and Bormann type were independent prognostic factors (P<0.05). CONCLUSION 18F-FDG uptake of AGC is an independent prognostic factor for distant metastasis-free survival, recurrence-free survival, and overall survival. The possibility of distant metastasis during follow-up should be considered in patients with high 18F-FDG uptake.
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Affiliation(s)
- Jeong Won Lee
- Department of Nuclear Medicine, International St. Mary's Hospital, Catholic Kwandong University College of Medicine, Incheon, Korea
| | - Kwanhyeong Jo
- Department of Nuclear Medicine, Yonsei University College of Medicine, Seoul, Korea
| | - Arthur Cho
- Department of Nuclear Medicine, Yonsei University College of Medicine, Seoul, Korea
| | - Sung Hoon Noh
- Departement of Surgery, Yonsei University College of Medicine, Seoul, Korea; and
| | - Jong Doo Lee
- Department of Radiology, International St. Mary's Hospital, Catholic Kwandong University College of Medicine, Incheon, Korea
| | - Mijin Yun
- Department of Nuclear Medicine, Yonsei University College of Medicine, Seoul, Korea
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Kim Y, Spolverato G, Ejaz A, Squires MH, Poultsides G, Fields RC, Bloomston M, Weber SM, Votanopoulos K, Acher AW, Jin LX, Hawkins WG, Schmidt C, Kooby D, Worhunsky D, Saunders N, Levine EA, Cho CS, Maithel SK, Pawlik TM. A nomogram to predict overall survival and disease-free survival after curative resection of gastric adenocarcinoma. Ann Surg Oncol 2014; 22:1828-35. [PMID: 25388061 DOI: 10.1245/s10434-014-4230-4] [Citation(s) in RCA: 51] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2014] [Indexed: 02/06/2023]
Abstract
BACKGROUND The American Cancer Society projects there will be over 22,000 new cases, resulting in nearly 11,000 deaths, related to gastric adenocarcinoma in the US in 2014. The aim of the current study was to find clinicopathologic variables associated with disease-free survival (DFS) and overall survival (OS) following curative resection of gastric adenocarcinoma, and create a nomogram for individual risk prediction. METHODS A nomogram to predict DFS and OS following surgical resection of gastric adenocarcinoma was constructed using a multi-institutional cohort of patients who underwent surgery for primary gastric adenocarcinoma at seven major institutions in the US between January 2000 and August 2013. Discrimination and calibration of the nomogram were tested by C-statistic, Kaplan-Meier curves, and calibration plots. RESULTS A total of 719 patients who underwent surgery for primary gastric adenocarcinoma were included in the study. Using the backward selection of clinically relevant variables with Akaike information criteria, age, sex, tumor site, depth of invasion, and lymph node ratio (LNR) were selected as factors predictive of OS, while age, tumor site, depth of invasion, and LNR were incorporated in the prediction of DFS. A nomogram was constructed to predict OS and DFS using these variables. Discrimination and calibration of the nomogram revealed good predictive abilities (C-index, DFS 0.711; OS 0.702). CONCLUSION Independent predictors of recurrence and death following surgery for primary gastric adenocarcinoma were used to create a nomogram to predict DFS and OS. The nomogram was able to stratify patients into prognostic groups, and performed well on internal validation.
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Affiliation(s)
- Yuhree Kim
- Department of Surgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Zheng Z, Liu Y, Bu Z, Zhang L, Li Z, Du H, Ji J. Prognostic role of lymph node metastasis in early gastric cancer. Chin J Cancer Res 2014; 26:192-9. [PMID: 24826060 DOI: 10.3978/j.issn.1000-9604.2014.04.06] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2014] [Accepted: 04/10/2014] [Indexed: 01/14/2023] Open
Abstract
OBJECTIVE To clarify the relationship between clinicopathological features and lymph node metastasis and to propose the potential indications of lymph node metastasis for prognosis in early gastric cancer (EGC) patients. METHODS We retrospectively observed 226 EGC patients with lymph node resection, and analyzed the associations between lymph node metastasis and clinicopathological parameters using the chi-square test in univariate analysis and logistic regression analysis in multivariate analysis. Overall survival analysis was determined using the Kaplan-Meier and log-rank test. We conducted multivariate prognosis analysis using the Cox proportional hazards model. RESULTS Of all the EGC patients, 7.5% (17/226) were histologically shown to have lymph node metastasis. The differentiation, lymphovascular invasion and depth of invasion were independent risk factors for lymph node metastasis in EGC. The 5- and 10-year survival rates were significantly lower in patients with lymph node metastasis than in those without and the patients also had shorter progress-free survival time. Lymph node metastasis and tumor size were independent prognostic factors for EGC. The status of the lymph nodes was a significant factor in predicting recurrence or metastasis after surgery. CONCLUSIONS The undifferentiated carcinoma and lymphovascular and/or submucosal invasion were associated with a higher incidence of lymph node metastasis in EGC patients, whom need to perform subsequent D2 lymphadenectomy or laparoscopic lymph node dissection and more rigorous follow-up or additional chemotherapy/radiation after D2 gastrectomy for poor prognosis and high recurrence/metastasis rate.
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Affiliation(s)
- Zhixue Zheng
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), 1 Department of Gastrointestinal Surgery, 2 Department of Pathology, 3 Clinical Gastric Cancer Translational Research Laboratory, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Yiqiang Liu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), 1 Department of Gastrointestinal Surgery, 2 Department of Pathology, 3 Clinical Gastric Cancer Translational Research Laboratory, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Zhaode Bu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), 1 Department of Gastrointestinal Surgery, 2 Department of Pathology, 3 Clinical Gastric Cancer Translational Research Laboratory, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Lianhai Zhang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), 1 Department of Gastrointestinal Surgery, 2 Department of Pathology, 3 Clinical Gastric Cancer Translational Research Laboratory, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Ziyu Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), 1 Department of Gastrointestinal Surgery, 2 Department of Pathology, 3 Clinical Gastric Cancer Translational Research Laboratory, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Hong Du
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), 1 Department of Gastrointestinal Surgery, 2 Department of Pathology, 3 Clinical Gastric Cancer Translational Research Laboratory, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Jiafu Ji
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), 1 Department of Gastrointestinal Surgery, 2 Department of Pathology, 3 Clinical Gastric Cancer Translational Research Laboratory, Peking University Cancer Hospital & Institute, Beijing 100142, China
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Hirabayashi S, Kosugi S, Isobe Y, Nashimoto A, Oda I, Hayashi K, Miyashiro I, Tsujitani S, Kodera Y, Seto Y, Furukawa H, Ono H, Tanabe S, Kaminishi M, Nunobe S, Fukagawa T, Matsuo R, Nagai T, Katai H, Wakai T, Akazawa K. Development and external validation of a nomogram for overall survival after curative resection in serosa-negative, locally advanced gastric cancer. Ann Oncol 2014; 25:1179-84. [PMID: 24669009 DOI: 10.1093/annonc/mdu125] [Citation(s) in RCA: 89] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Few nomograms can predict overall survival (OS) after curative resection of advanced gastric cancer (AGC), and these nomograms were developed using data from only a few large centers over a long time period. The aim of this study was to develop and externally validate an elaborative nomogram that predicts 5-year OS after curative resection for serosa-negative, locally AGC using a large amount of data from multiple centers in Japan over a short time period (2001-2003). PATIENTS AND METHODS Of 39 859 patients who underwent surgery for gastric cancer between 2001 and 2003 at multiple centers in Japan, we retrospectively analyzed 5196 patients with serosa-negative AGC who underwent Resection A according to the 13th Japanese Classification of Gastric Carcinoma. The data of 3085 patients who underwent surgery from 2001 to 2002 were used as a training set for the construction of a nomogram and Web software. The data of 2111 patients who underwent surgery in 2003 were used as an external validation set. RESULTS Age at operation, gender, tumor size and location, macroscopic type, histological type, depth of invasion, number of positive and examined lymph nodes, and lymphovascular invasion, but not the extent of lymphadenectomy, were associated with OS. Discrimination of the developed nomogram was superior to that of the TNM classification (concordance indices of 0.68 versus 0.61; P < 0.001). Moreover, calibration was accurate. CONCLUSIONS We have developed and externally validated an elaborative nomogram that predicts the 5-year OS of postoperative serosa-negative AGC. This nomogram would be helpful in the assessment of individual risks and in the consideration of additional therapy in clinical practice, and we have created freely available Web software to more easily and quickly predict OS and to draw a survival curve for these purposes.
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Affiliation(s)
- S Hirabayashi
- Department of Medical Informatics, Niigata University Medical and Dental Hospital, Niigata
| | - S Kosugi
- Division of Digestive and General Surgery, Niigata University Graduate School of Medical and Dental Sciences, Niigata
| | - Y Isobe
- Department of Surgery, National Hospital Organization Tokyo Medical Center, Tokyo
| | - A Nashimoto
- Department of Surgery, Niigata Cancer Center Hospital, Niigata
| | - I Oda
- Endoscopy Division, National Cancer Center Hospital, Tokyo
| | - K Hayashi
- Department of Surgery, Yamagata Prefectural Kahoku Hospital, Yamagata
| | - I Miyashiro
- Department of Surgery, Osaka Medical Center for Cancer and Cardiovascular Diseases, Osaka
| | - S Tsujitani
- Center for Clinical and Translational Research, National Center for Global Health and Medicine, Tokyo
| | - Y Kodera
- Department of Surgery II, Nagoya University School of Medicine, Nagoya
| | - Y Seto
- Department of Gastrointestinal Surgery, Graduate School of Medicine, University of Tokyo, Tokyo
| | - H Furukawa
- Department of Surgery, Kinki University Faculty of Medicine, Osaka
| | - H Ono
- Endoscopy Division, Shizuoka Cancer Center Hospital, Shizuoka
| | - S Tanabe
- Department of Gastroenterology, Kitasato University East Hospital, Sagamihara
| | - M Kaminishi
- Department of Surgery, Showa General Hospital, Tokyo
| | - S Nunobe
- Department of Gastroenterological Surgery, Cancer Institute Ariake Hospital, Tokyo
| | - T Fukagawa
- Gastric Surgery Division, National Cancer Center Hospital, Tokyo, Japan
| | - R Matsuo
- Department of Medical Informatics, Niigata University Medical and Dental Hospital, Niigata
| | - T Nagai
- Department of Medical Informatics, Niigata University Medical and Dental Hospital, Niigata
| | - H Katai
- Gastric Surgery Division, National Cancer Center Hospital, Tokyo, Japan
| | - T Wakai
- Division of Digestive and General Surgery, Niigata University Graduate School of Medical and Dental Sciences, Niigata
| | - K Akazawa
- Department of Medical Informatics, Niigata University Medical and Dental Hospital, Niigata
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Prediction of tumor recurrence after curative resection in gastric carcinoma based on bcl-2 expression. World J Surg Oncol 2014; 12:40. [PMID: 24555747 PMCID: PMC3996074 DOI: 10.1186/1477-7819-12-40] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2013] [Accepted: 02/10/2014] [Indexed: 12/27/2022] Open
Abstract
Background There are currently no reliable predictive factors for gastric cancer recurrence. The aim of this study was to evaluate the relationship between bcl-2 expression and risk of gastric cancer recurrence. Methods From January 1996 to December 2007, 449 gastric cancer patients who underwent curative resection were retrospectively studied. The expression levels of bcl-2 were examined by immunohistochemistry. Logistic regression was performed to identify independent risk factors for overall recurrence of gastric cancer. Results 151 patients (33.6%) experienced recurrences. The median time to recurrence was 17.0 months, 113 (74.8%) patients had recurrences within 2 years. Peritoneal recurrence was the most prevalent pattern, followed by hematogenous metastasis in which the liver was the most common site. Depth of invasion, lymph node metastases, and negative expression of bcl-2 were independent risk factors for overall recurrence. The overall survival time of recurrent patients was 22.7 months. The median survival time after recurrence was 6.7 months. Conclusion The depth of invasion, lymph node metastases and expression of bcl-2 are independent factors for predicting gastric cancer recurrence.
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