Ling Xiao, Yu-Hang Yang, Shi-Chuan Zhang, Jia-Hua Lyu, Department of Radiation, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
Co-corresponding authors: Shi-Chuan Zhang and Jia-Hua Lyu.
Author contributions: Xiao L handled conceptualization, project administration, resources, and supervision; Xiao L and Yang YH managed data curation, oversaw software, and visualization, and they contributed equally to this article as co-first authors; Xiao L, Yang YH, and Zhang SC took charge of methodology; Lyu JH handled funding acquisition; Xiao L, Yang YH, Zhang SC, and Lyu JH contributed to investigation, validation, writing original draft, and writing review and editing; Zhang SC and Lyu JH contributed equally to this article as co-corresponding authors; and all authors thoroughly reviewed and endorsed the final manuscript.
AI contribution statement: Gemini 3 was used only for language polishing and improving academic English readability. It was not involved in study design, data analysis, result interpretation or conclusion generation. All scientific content was independently completed by the authors based on original clinical data.
Institutional review board statement: This study was approved by the Ethics Committee of Sichuan Cancer Hospital (Approval No. SCCHEC2015010).
Informed consent statement: The informed consent was waived by the Institutional Review Board.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
STROBE statement: The authors have read the STROBE Statement—checklist of items, and the manuscript was prepared and revised according to the STROBE Statement—checklist of items.
Data sharing statement: The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.
Corresponding author: Jia-Hua Lyu, PhD, Associate Chief Physician, Senior Researcher, Department of Radiation, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, No. 55 Section 4, Renmin South Road, Chengdu 610041, Sichuan Province, China. winlttljh@163.com
Received: May 18, 2026 Revised: June 8, 2026 Accepted: July 2, 2026 Published online: November 15, 2026 Processing time: 172 Days and 8.4 Hours
Abstract
BACKGROUND
Definitive chemoradiotherapy is the standard treatment for advanced esophageal squamous cell carcinoma (ESCC); however, marked prognostic heterogeneity exists and simple predictive biomarkers are lacking. Although skeletal muscle density (SMD) reflects muscle quality, its posttreatment prognostic value and age-dependent modifying effect in ESCC remain unclear.
AIM
To explore the prognostic significance of post-treatment SMD (post-SMD) and to clarify the age-related interaction in patients with ESCC undergoing definitive chemoradiotherapy.
METHODS
Altogether, 255 eligible ESCC patients were retrospectively enrolled. Post-SMD was calculated using L3 vertebral-level abdominal computed tomography images. Additionally, multivariate logistic regression and restricted cubic spline were utilized to analyze the influencing factors and nonlinear age-post-SMD correlation. Moreover, survival analyses and Cox regression were performed to assess the prognostic value, followed by the construction and validation of an age-subgroup prognostic model.
RESULTS
In the entire cohort, lower post-SMD was significantly associated with worse survival (P = 0.034). A nonlinear relationship was identified between age and post-SMD, with 64 years established as the inflection point (P = 0.016). Consequently, the prognostic impact of post-SMD was highly age-dependent. It served as a significant predictor of poor survival exclusively in patients aged < 64 years (P = 0.020) but not in those ≥ 64 years (P = 0.439). Multivariate analysis confirmed that higher post-SMD was an independent protective factor for survival (hazard ratio = 0.633, P = 0.006). Based on these findings, we developed a prognostic model incorporating post-SMD specifically for patients under 64 years. This model demonstrated excellent performance in distinguishing high-risk patients (P < 0.001), exhibiting high discriminatory power [12-month area under the curve (AUC) = 0.820; 36-month AUC = 0.867], good calibration, and providing a positive net clinical benefit in decision curve analysis.
CONCLUSION
In this study cohort, post-SMD is a vital prognostic biomarker, and age acts as a core effect modifier in evaluating its prognostic significance. This finding can provide references for precise risk stratification and individualized management of the corresponding population.
Core Tip: This study enrolled 255 esophageal squamous cell carcinoma (ESCC) patients treated with definitive chemoradiotherapy to explore the prognostic role of post-treatment skeletal muscle density (post-SMD). We innovatively identified a nonlinear correlation between age and post-SMD, with 64 years as the optimal cut-off inflection point. Post-SMD exhibited an age-dependent prognostic modifying effect: Reduced post-SMD independently predicted inferior survival exclusively in patients aged < 64 years, while no significant prognostic correlation was observed in elderly patients ( ≥ 64 years). A tailored prognostic model incorporating post-SMD was established for young ESCC patients, which presented favorable discrimination, calibration, and net clinical benefit.
Citation: Xiao L, Yang YH, Zhang SC, Lyu JH. Prognostic impact of post-chemoradiotherapy muscle quality in non-elderly adults with esophageal squamous cell carcinoma. World J Gastrointest Oncol 2026; 18(11): 123400
Esophageal cancer is a highly prevalent digestive malignancy with a poor global prognosis[1]. Esophageal squamous cell carcinoma (ESCC) is the predominant histological subtype in China and exhibits strong invasiveness[2,3]. Most patients are diagnosed at advanced stages and ineligible for radical surgery; thus, definitive chemoradiotherapy serves as the standard treatment[4,5]. Nevertheless, marked survival heterogeneity persists among patients receiving standardized treatment, and simple and reliable imaging biomarkers for prognostic prediction remain scarce[6,7]. Therefore, exploring objective predictive indicators is critical for risk stratification and individualized management.
Sarcopenia is characterized by progressive loss of skeletal muscle mass and quality and serves as an adverse prognostic indicator of malignancies[8,9]. Muscle depletion is commonly accompanied by intramuscular fat infiltration. Although baseline sarcopenia predicts poor survival in ESCC[10-13], most studies have primarily focused on pretreatment muscle reserves. Notably, tumor consumption and treatment toxicity jointly induce continuous metabolic disorders and body composition changes during chemoradiotherapy[14,15]. Compared with baseline indicators, post-treatment muscle parameters better reflect treatment tolerance and real metabolic alterations[16,17]. However, the prognostic value of post-treatment skeletal muscle density (post-SMD) in patients with ESCC undergoing definitive chemoradiotherapy remains poorly defined.
Age is a vital determinant of muscle status. Unlike age-related sarcopenia, cancer-related sarcopenia is mainly driven by systemic inflammation and tumor metabolism[18-20]. This distinction indicates that age may independently modulate muscle status and clinical outcomes in cancer patients. Currently, most esophageal cancer studies do not perform rigorous age stratification; hence, whether age modifies the prognostic efficacy of muscle biomarkers is unclear.
Accordingly, this retrospective study enrolled patients with ESCC receiving definitive chemoradiotherapy. We aimed to identify the influencing factors for post-SMD and explore their nonlinear correlation with age. Additionally, we sought to clarify the heterogeneous prognostic value of post-SMD through an age-stratified analysis and, subsequently, construct a tailored prognostic model. The present study intends to provide clinical evidence for precise risk stratification and individualized intervention in non-elderly ESCC populations.
MATERIALS AND METHODS
Study population
Altogether, 255 patients with ESCC who underwent definitive chemoradiotherapy at Sichuan Cancer Hospital from January 2012 to November 2018 were retrospectively enrolled.
Inclusion criteria: (1) Histopathologically confirmed ESCC; (2) Stage I-IV based on the 7th edition of the AJCC staging system, with unresectable tumors or patients refusing surgery; (3) Karnofsky Performance Status (KPS) score of ≥ 70; (4) Completion of definitive chemoradiotherapy with a radiotherapy dose of ≥ 50 Gy; (5) Availability of blood test results within 1 week before treatment and abdominal computed tomography (CT) obtained at approximately 2 weeks after definitive chemoradiotherapy; (6) No distant metastasis or other primary malignant tumors; and (7) CT images without obvious artifacts for the clear identification of skeletal muscle at the L3 vertebral level.
Exclusion criteria: (1) Patients with surgically resectable tumors; (2) A history of antitumor treatment; and (3) Incomplete medical records or follow-up data.
The present study was approved by the Ethics Committee of Sichuan Cancer Hospital (Approval No. SCCHEC2015010) and conducted in accordance with medical ethical guidelines.
Clinical data collection
The patients’ baseline data, including demographic characteristics, KPS score, smoking and drinking history, tumor features, treatment regimens, and laboratory nutritional indicators, were extracted from the electronic medical record system.
Body composition assessment
Post-treatment abdominal CT images at the L3 vertebral level were collected from routine short-term efficacy evaluation examinations at around 2 weeks after definitive chemoradiotherapy completion and extracted from the hospital picture archiving and communication system. No extra CT scans were arranged exclusively for this study. Two radiologists blinded to clinical outcomes independently delineated bilateral skeletal muscles at the L3 vertebral level using SliceOmatic 5.0 software, with an attenuation threshold ranging from -29 Hounsfield units (HU) to +150 HU. The measured muscles included the psoas major, quadratus lumborum, erector spinae, transversus abdominis, internal oblique abdominis, external oblique abdominis, and rectus abdominis. The cross-sectional area of the skeletal muscle (SMA, cm2) was automatically calculated. Skeletal muscle density (SMD; HU) was defined as the mean CT value of all pixels within the delineated muscle region. The relevant indicators were calculated as follows: Skeletal muscle index (SMI) = SMA/height2. Low SMI was defined as < 40.8 cm2/m2 for man and < 34.9 cm2/m2 for women. Myosteatosis was diagnosed as SMD of < 41 HU in patients with body mass index (BMI) of < 25 kg/m2 or SMD of < 33 HU in patients with BMI of ≥ 25 kg/m2[21,22].
Clinical follow-up
All patients were followed up regularly through outpatient visits and telephone interviews. Follow-up commenced after the completion of chemoradiotherapy, with an interval of every 3 months in the first year, every 6 months from the second to the third year, and annually thereafter. Follow-up evaluations included physical and imaging examinations and laboratory tests. Survival status and disease progression were continuously recorded. Overall survival (OS) was defined as the interval from confirmed diagnosis to death or the last follow-up.
Statistical analysis
Rstudio 4.3.1 software was used for data analyses and graph plotting. The significance level was set at α = 0.05, and P < 0.05 was considered statistically significant. For descriptive statistics, categorical variables were presented as n (%) and compared using the χ2 or Fisher’s exact test. Continuous variables were expressed as mean ± SD or median [interquartile range (IQR)] and compared via t-test. The Kaplan-Meier method was applied for survival curve plotting, and the log-rank test was used to analyze intergroup survival differences and to determine the optimal cut-off SMD value[23]. Multivariate logistic regression was performed to identify the independent factors correlated to low post-SMD. Restricted cubic spline (RCS) analysis was conducted to explore the nonlinear correlation between age and post-SMD and confirm the age inflection point. Univariate and multivariate Cox proportional hazard regression models were utilized to screen the independent prognostic factors and to construct the prognostic models. Receiver operating characteristic (ROC) curves were applied to evaluate model discrimination by calculating the area under the curve (AUC). Internal validationwas performed using the bootstrap method with 800 resamples. A decision curve analysis (DCA) was performed to verify the model’s clinical applicability for 1- and 3-year survival predictions.
RESULTS
Comparison of the baseline clinical characteristics among patients stratified by survival outcomes
Altogether, 255 patients with ESCC receiving definitive chemoradiotherapy were enrolled and divided into the survival (n = 90) and non-survival (n = 165) groups according to their follow-up outcomes. The patients’ baseline demographic characteristics, functional status, lifestyle habits, tumor features, treatment parameters, and laboratory indicators were analyzed (Figure 1 and Table 1). No significant differences in sex composition and age distribution were observed between the two groups (both P > 0.05). The cohort was predominantly male (78.4%), with a mean age of 63.9 ± 9.4 years. The survival and non-survival groups had similar ages (63.4 ± 7.9 years vs 64.1 ± 10.1 years). Significant inter-group differences were detected in the KPS scores (P = 0.028), and the survival group presented better functional status. Smoking and drinking history were not significantly different between the survival and non-survival groups (P = 0.445 and P = 0.091). The overall prevalence rates of smoking and drinking history were 57.6% and 54.9%, respectively. The non-survival group had non-significantly higher proportion of drinkers (58.8% vs 47.8%). Tumor location was comparable between the two groups (P = 0.428), with the middle thoracic (37.6%) and lower thoracic tumors (33.7%) being the most common.
Regarding the treatment and laboratory indicators, radiotherapy dose, post-treatment blood lipid indexes (total cholesterol and triglyceride), and post-treatment SMI (post-SMI) differed significantly between groups (all P < 0.05). The non-survival group had a slightly higher median radiotherapy dose (66 Gy vs 66 Gy, IQR: 64-66 Gy vs 60-66 Gy). Posttreatment total cholesterol and triglyceride levels were significantly lower in the non-survival group than in the survival group (median total cholesterol: 4.22 mmol/L vs 4.91 mmol/L, P = 0.002; median triglyceride: 1.23 mmol/L vs 1.44 mmol/L, P = 0.01). For the nutritional and skeletal muscle indicators, the non-survival group had a remarkably lower post-SMI (42.9 ± 7.5 vs 45.1 ± 7.8, P = 0.028) and marginally lower posttreatment BMI (20.9 ± 2.7 kg/m2 vs 21.5 ± 2.7 kg/m2, P = 0.072). No significant differences were found in the posttreatment hemoglobin and albumin levels and post-SMD between the two groups (all P > 0.05).
Distribution characteristics and correlative factors of post-SMD
The distribution characteristics, influencing factors, and post-SMD predictive model were systematically analyzed. Box plots are illustrated in Figure 2A-C to show the post-SMD distribution across different clinical subgroups: Patients aged < 64 years had significantly higher post-SMD than those aged ≥ 64 years (Figure 2A, P < 0.001); female patients presented higher post-SMD than male patients (Figure 2C, P < 0.001); and no significant difference in post-SMD was observed between the survival and non-survival groups (Figure 2B, P = 0.148). These results indicated potential correlations between post-SMD and clinical features, including age and sex.
Figure 2 Post-treatment skeletal muscle density and associated factors in esophageal cancer patients.
A-C: Boxplots of post-treatment skeletal muscle density (post-SMD) distribution across different clinical subgroups; D: Forest plot of multivariable logistic regression analysis for factors associated with post-SMD; E: The nonlinear association between age and post-SMD using restricted cubic spline analysis; F and G: The receiver operating characteristic curve and calibration curve of the age-based prediction model for post-SMD, respectively. OR: Odds ratio; 95%CI: 95% confidence interval; FPR: False positive rate; TPR: True positive rate; AUC: Area under the curve; Post-SMD: Post-treatment skeletal muscle density.
Multivariate logistic regression was performed to identify the independent correlated factors for low post-SMD. The forest plot (Figure 2D) demonstrated that male sex [odds ratio (OR) = 3.089, 95% confidence interval (95%CI): 1.374-6.942, P = 0.006], age ≥ 64 years (OR = 3.245, 95%CI: 1.893-5.565, P < 0.001), and presence of a lower thoracic tumor (OR = 2.249, 95%CI: 1.143-4.428, P = 0.019) were the independent risk factors for low post-SMD. Age exhibited the strongest correlation with post-SMD. The RCS analysis was further applied to verify the nonlinear association between age and post-SMD (Figure 2E). A significant nonlinear correlation was confirmed (P for nonlinear = 0.017), with the age of 64 years identified as the inflection point.
Binary assignment was performed with low post-SMD as the reference. In the subgroup aged < 64 years, the OR remained consistently higher than 1, indicating a higher probability of high post-SMD (OR = 3.529, 95%CI: 2.080-5.986, P < 0.001). The OR gradually decreased with aging. For patients aged ≥ 64 years, the OR decreased below 1, suggesting a higher risk of low post-SMD (OR = 0.283, 95%CI: 0.167-0.481, P < 0.001). We constructed an age-based post-SMD prediction model. The ROC curve (Figure 2F) showed an AUC value of 0.815 (95%CI: 0.763-0.867), indicating favorable discrimination. The calibration curve (Figure 2G) revealed high consistency between the predicted and actual probabilities with satisfactory calibration performance.
Correlation between post-SMD and prognosis in ESCC patients stratified by age
Based on the nonlinear correlation between age and post-SMD and the 64-year-old inflection point, an age stratification analysis was conducted to explore the age-dependent prognostic value of post-SMD (Figure 3). In the overall cohort, the low post-SMD subgroup had significantly worse survival than the high post-SMD subgroup based on the log-rank test results (P = 0.034, Figure 3A). Further stratified analysis was performed to verify the modifying effect of age: No significant survival difference was observed between low and high post-SMD subgroups in patients aged ≥ 64 years (P = 0.439, Figure 3B). Among patients aged < 64 years, the low post-SMD subgroup presented remarkably inferior survival outcomes (P = 0.020, Figure 3C). These findings confirmed that the prognostic value of post-SMD was age-dependent. Low post-SMD was tightly correlated with a poor prognosis only in non-elderly patients, which was consistent with the nonlinear age-post-SMD correlation.
Figure 3 Survival analysis by post-treatment skeletal muscle density status stratified by age in esophageal cancer patients.
A: The whole cohort; B: The ≥ 64 years cohort; C: The < 64 years cohort.
Construction and validation of a post-SMD-based prognostic model for non-elderly ESCC patients
Given the age-dependent prognostic effect of post-SMD, univariate and multivariate Cox regression analyses were performed to screen for the independent prognostic factors. Univariate analysis indicated that the KPS score, T stage, post-treatment blood lipids (postTC, postTG), post-treatment BMI, and post-SMD were significantly correlated with survival. After adjusting for confounding factors, multivariate analysis confirmed that the KPS score, T stage, postTC level, and post-SMD were the independent prognostic factors. Patients with high post-SMD had a lower mortality risk [hazard ratio (HR) = 0.654, 95%CI: 0.473-0.905, P = 0.010], proving post-SMD as an independent protective factor (Table 2). All patients were stratified by model-based risk scores. The Kaplan-Meier curves (Figure 4A) showed that the high-risk subgroup had a significantly lower survival probability (P < 0.001). Time-dependent ROC curves (Figure 4B) yielded AUC values of 0.820 and 0.867 for 12- and 36-month survival predictions, respectively. The predictive performance of the model was assessed using the C-index and calibration curves. Internal validation was performed via bootstrap resampling (B = 800), and the C-index was calculated as 0.746 (95%CI: 0.720-0.771). Calibration curves showed favorable consistency between the predicted and actual 12- (Figure 4C) and 36-month (Figure 4D) survival probabilities. A DCA was conducted to evaluate the model’s clinical applicability, which revealed superior net benefit for the model incorporating post-SMD across most threshold probability ranges (Figures 4E and F).
Figure 4 Prognostic model construction and validation based on post-treatment skeletal muscle density in patients aged < 64 years with esophageal squamous cell carcinoma.
A: Kaplan-Meier survival curves stratified by risk score; B: Time-dependent receiver operating characteristic curves of the model; C and D: Bootstrap-based calibration curves for 12-month and 36-month overall survival prediction; E and F: Calibration curves for 12- and 36-month survival prediction. FPR: False positive rate; TPR: True positive rate; AUC: Area under the curve; SMD: Skeletal muscle density.
Table 2 Univariate and multivariate Cox regression analyses of factors associated with overall survival.
Sarcopenia is a critical adverse prognostic risk factor for esophageal cancer patients and is characterized by the deterioration of skeletal muscle quantity, quality, and function. It can directly reflect the patients' nutritional reserve and physical performance and effectively predict antitumor treatment efficacy and risk of treatment-related adverse reactions. Therefore, sarcopenia serves as an essential reference indicator for clinical prognostic evaluation and patient management[21,24-26]. Notably, the rapid advancement of artificial intelligence and machine learning in oncology has highlighted the power of leveraging complex, high-dimensional data—including medical imaging features—to develop predictive models that may surpass the limitations of conventional univariate or linear approaches[27,28]. In contrast to artificial intelligence (AI) applications focused primarily on diagnostic classification of lesions, the objective of the current study aligns with the prognostic prediction paradigm: To utilize quantitative imaging biomarkers, specifically post-SMD, for risk stratification and outcome forecasting in a defined patient cohort following curative-intent therapy. The present study retrospectively enrolled 255 patients with ESCC who received definitive chemoradiotherapy and clarified the prognostic value of post-SMD and its age-specific correlation. A distinct age inflection point of 64 years was identified, with a significant nonlinear relationship observed between age and post-SMD. The results of the multivariate analysis confirmed that advanced age was an independent risk factor for low post-SMD. The stratified analysis further demonstrated that the prognostic value of post-SMD was strictly age-specific. Low post-SMD acted as an independent adverse prognostic factor only in patients aged < 64 years, and the prognostic model constructed for this subgroup exhibited favorable performance. Nevertheless, this correlation was markedly attenuated in patients aged ≥ 64 years. Accordingly, post-SMD-based prognostic evaluation for non-elderly patients with ESCC after chemoradiotherapy can facilitate precise clinical risk stratification.
Most current studies on sarcopenia and skeletal muscle in patients with esophageal cancer have focused on pre-treatment baseline skeletal muscle mass indicators, with prognostic analyses mainly centered on pretreatment sarcopenia-related survival outcomes. For instance, Onishi et al[11] reported that unresectable advanced ESCC patients with pretreatment sarcopenia suffered inferior 2-year OS, and sarcopenia was identified as an independent poor prognostic factor (HR = 1.48, 95%CI: 1.04-2.10, P = 0.03). Zhang et al[26] found that elderly esophageal cancer patients with preoperative sarcopenia achieved a lower 3-year OS rate. Moreover, Xu et al[29] verified that sarcopenia was correlated with inferior survival in ESCC patients receiving chemoradiotherapy after postoperative local recurrence. However, studies on static post-treatment skeletal muscle indices in ESCC patients remain limited, with most existing reports focusing on muscle status after surgery or neoadjuvant therapy. Takeoka et al[30] revealed that patients with severe skeletal muscle loss (≥ 10%) at 3 months after esophagectomy had a significantly lower 3-year OS rate than those with mild muscle loss (P = 0.035). Jogiat et al[14] further demonstrated that post-neoadjuvant sarcopenia was significantly associated with shortened OS and disease-free survival, whereas Onishi et al[31] also confirmed postoperative sarcopenia as an independent adverse prognostic factor for OS.
In the present study, post-SMD was identified as an independent protective factor for OS in multivariate analysis among ESCC patients undergoing definitive chemoradiotherapy (adjusted HR = 0.654, 95%CI: 0.473-0.905, P = 0.010). Deng et al[25] conducted a study on patients with gastric cancer and reported that sarcopenic obesity defined by low SMD was an independent predictor of progression-free survival and OS in patients treated with immune checkpoint inhibitors. Zeuge et al[32] suggested that the prognostic significance of sarcopenia varied by histological type in patients with metastatic esophageal cancer; sarcopenia was correlated with inferior survival in adenocarcinoma patients, whereas no significant association was observed in squamous cell carcinoma patients. Additionally, Kanemura et al[10] indicated that preoperative sarcopenia diagnosed based on integrated muscle mass, muscle strength, and physical function affected the long-term survival of esophageal cancer patients, and low gait speed was significantly associated with poor prognosis.
This study verified that post-SMD has independent, age-modified prognostic value, and this imaging biomarker reflects integrated pathophysiological alterations of skeletal muscle at the critical post-chemoradiotherapy time point. Reduced SMD serves as the morphological manifestation of persistent systemic catabolic disturbance, featured by ectopic lipid deposition in the interstitial space and around muscle fibers. The relevant pathological processes originate from three primary causes: (1) Combined tumor burden and anticancer treatment induce systemic inflammatory response and metabolic stress[33,34]; (2) Persistent inflammatory stimuli abnormally activate cachexia-associated pathways and trigger whole-body metabolic reprogramming[8,35]; (3) Combined inflammation and metabolic disorders drive committed adipogenic differentiation of fibro-adipogenic progenitors, resulting in interstitial lipid infiltration, myosteatosis and subsequent decline in SMD[36]; and (4) Multi-omics-based pan-cancer analysis identifies core oncogenic mutations as key initiators of tumor-derived inflammatory and metabolic perturbations[37].
Age is a core physiological factor affecting skeletal muscle status. Pathophysiologically, age-related sarcopenia differs distinctly from cancer-related sarcopenia. The former is mainly attributed to disuse, malnutrition, and degeneration, whereas the latter is predominantly driven by systemic inflammation and tumor-secreted factors[18]. This indicates that, in cancer patients, age exerts complex effects on the skeletal muscle. An increasing number of studies have focused on the modifying effect of age. For example, in postoperative colorectal cancer patients, myosteatosis (reflecting muscle quality) had the greatest prominent prognostic value in patients aged 51-74 years, whereas sarcopenia was more strongly associated with prognosis in patients aged ≥ 75 years[38]. Another study demonstrated that the age of ≥ 52 years was an independent risk factor for sarcopenia in patients undergoing continuous ambulatory peritoneal dialysis[39]. Regarding esophageal cancer treatment decision-making, age is closely correlated with the patients’ body composition. Patients aged > 75 years or those with low skeletal muscle indicator measurements were significantly less likely to undergo radical surgery[20]. In the present study focusing on patients with ESCC treated with definitive chemoradiotherapy, a nonlinear correlation between age and post-SMD was verified with a clear inflection point at 64 years of age. Specifically, patients aged < 64 years tended to have higher post-SMD with increasing age; conversely, advanced age was correlated with a lower risk of low post-SMD in patients aged > 64 years.
Several limitations of this study should be acknowledged. As a single-center retrospective study, the generalizability of the study findings requires further validation through multicenter prospective studies involving large sample sizes. Without pretreatment baseline CT data for comparison, post-SMD can only act as a static prognostic marker rather than a treatment response biomarker and cannot reflect dynamic muscular changes. Additionally, although the prognostic value of post-SMD and its correlation with lipid metabolism were clarified, confounding factors, including grip strength and nutritional status, were not incorporated into the analysis. The underlying biological mechanisms also need to be further explored in basic and clinical research studies.
CONCLUSION
In conclusion, post-SMD is influenced by age, presenting a nonlinear correlation with age. Its prognostic value is age-specific, serving as an independent prognostic factor only in non-elderly patients. The established prognostic model provides credible evidence for risk stratification and individualized clinical intervention in this population. Future work may explore AI-assisted multimodal integration of imaging, body composition, and multiomics data to further refine ESCC prognostic modeling.
ACKNOWLEDGEMENTS
We appreciate everyone who participated in the study.
Kanemura T, Takeoka T, Sugase T, Urakawa S, Masuike Y, Shinno N, Hara H, Kitakaze M, Kubo M, Mukai Y, Sueda T, Hasegawa S, Akita H, Nishimura J, Wada H, Yasui M, Omori T, Miyata H. Significance of Comprehensive Analysis of Preoperative Sarcopenia Based on Muscle Mass, Muscle Strength, and Physical Function for the Prognosis of Patients with Esophageal Cancer.Ann Surg Oncol. 2024;31:818-826.
[RCA] [PubMed] [DOI] [Full Text][Cited by in Crossref: 1][Cited by in RCA: 13][Article Influence: 6.5][Reference Citation Analysis (0)]
Anconina R, Ortega C, Metser U, Liu ZA, Suzuki C, McInnis M, Darling GE, Wong R, Taylor K, Yeung J, Chen EX, Swallow CJ, Bajwa J, Jang RW, Elimova E, Veit-Haibach P. Influence of sarcopenia, clinical data, and 2-[(18)F] FDG PET/CT in outcome prediction of patients with early-stage adenocarcinoma esophageal cancer.Eur J Nucl Med Mol Imaging. 2022;49:1012-1020.
[RCA] [PubMed] [DOI] [Full Text][Cited by in Crossref: 1][Cited by in RCA: 16][Article Influence: 3.2][Reference Citation Analysis (0)]
Dong QT, Cai HY, Zhang Z, Zou HB, Dong WX, Wang WB, Song HN, Luo X, Chen XL, Huang DD. Influence of body composition, muscle strength, and physical performance on the postoperative complications and survival after radical gastrectomy for gastric cancer: A comprehensive analysis from a large-scale prospective study.Clin Nutr. 2021;40:3360-3369.
[RCA] [PubMed] [DOI] [Full Text][Cited by in Crossref: 9][Cited by in RCA: 61][Article Influence: 12.2][Reference Citation Analysis (0)]
Ricker AB, Robinson J, Shea R, Cockerham K, Simpson M, Squires MH, Salo JC. Age and body composition of patients receiving treatment for locally advanced esophageal cancer.J Clin Oncol. 2024;42:e16094.
[PubMed] [DOI] [Full Text]
Takeoka T, Kanemura T, Sugase T, Matsuura N, Sugimura K, Yamamoto M, Shinno N, Hara H, Mukai Y, Hasegawa S, Nishimura J, Akita H, Wada H, Matsuda C, Omori T, Yasui M, Ohue M, Miyata H. Clinical impact of postoperative changes in body composition on long-term outcomes in patients with esophageal cancer.Clin Nutr. 2024;43:2188-2194.
[RCA] [PubMed] [DOI] [Full Text][Cited by in Crossref: 1][Cited by in RCA: 6][Article Influence: 3.0][Reference Citation Analysis (1)]
Zeuge U, Fares AF, Soriano J, Hueniken K, Bajwa J, Wang W, Schmid S, Rudolph-Naiberg S, Brown MC, Yeung J, Chen EX, Jang RW, Xu W, Elimova E, Liu G, Rozenberg D, McInnis MC. Differential prognostic significance of sarcopenia in metastatic esophageal squamous and adenocarcinoma.Esophagus. 2023;20:557-566.
[RCA] [PubMed] [DOI] [Full Text][Cited by in RCA: 3][Reference Citation Analysis (0)]
Paiella S, Azzolina D, Trestini I, Malleo G, Nappo G, Ricci C, Ingaldi C, Vacca PG, De Pastena M, Secchettin E, Zamboni G, Maggino L, Corciulo MA, Sandini M, Cereda M, Capretti G, Casadei R, Bassi C, Mansueto G, Gregori D, Milella M, Zerbi A, Gianotti L, Salvia R. Body composition parameters, immunonutritional indexes, and surgical outcome of pancreatic cancer patients resected after neoadjuvant therapy: A retrospective, multicenter analysis.Front Nutr. 2023;10:1065294.
[RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)][Cited by in Crossref: 6][Cited by in RCA: 11][Article Influence: 3.7][Reference Citation Analysis (0)]
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P-Reviewer: Meng YQ, Associate Chief Physician, MD, China; Mukundan A, Assistant Professor, PhD, Taiwan; Wei X, Academic Fellow, Clinical Assistant Professor (Honorary), DDS, PhD, Professor, China S-Editor: Lin C L-Editor: A P-Editor: Yang YQ
