Retrospective Cohort Study
Copyright ©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Nov 14, 2020; 26(42): 6638-6657
Published online Nov 14, 2020. doi: 10.3748/wjg.v26.i42.6638
Nomograms and risk score models for predicting survival in rectal cancer patients with neoadjuvant therapy
Fang-Ze Wei, Shi-Wen Mei, Jia-Nan Chen, Zhi-Jie Wang, Hai-Yu Shen, Juan Li, Fu-Qiang Zhao, Zheng Liu, Qian Liu
Fang-Ze Wei, Shi-Wen Mei, Jia-Nan Chen, Zhi-Jie Wang, Hai-Yu Shen, Juan Li, Fu-Qiang Zhao, Zheng Liu, Qian Liu, Department of Colorectal Surgery, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union College, Beijing 100021, China
Author contributions: Wei FZ and Chen JN designed the research; Mei SW, Wei FZ, Shen HY, Li J and Zhao FQ collected the data; Liu Z and Wei FZ analyzed the data; Wei FZ drafted the manuscript; Liu Q revised the manuscript.
Supported by The National Key Research and Development Plan "Research on Prevention and Control of Major Chronic Noncommunicable Diseases", No. 2019YFC1315705; and the Medicine and Health Technology Innovation Project of the Chinese Academy of Medical Sciences, No. 2017-12M-1-006.
Institutional review board statement: Our investigation received approval from the ethics committee of the National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College.
Informed consent statement: All patients signed informed consent forms.
Conflict-of-interest statement: The authors declare that they have no potential conflicts of interest.
Data sharing statement: No additional data are available.
STROBE statement: The authors have carefully read the STROBE Statement—checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Qian Liu, MD, Chief Doctor, Professor, Surgeon, Department of Colorectal Surgery, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China. fcwpumch@163.com
Received: August 18, 2020
Peer-review started: August 18, 2020
First decision: September 12, 2020
Revised: September 15, 2020
Accepted: September 25, 2020
Article in press: September 25, 2020
Published online: November 14, 2020
Processing time: 87 Days and 1 Hours
Abstract
BACKGROUND

Colorectal cancer is a common digestive cancer worldwide. As a comprehensive treatment for locally advanced rectal cancer (LARC), neoadjuvant therapy (NT) has been increasingly used as the standard treatment for clinical stage II/III rectal cancer. However, few patients achieve a complete pathological response, and most patients require surgical resection and adjuvant therapy. Therefore, identifying risk factors and developing accurate models to predict the prognosis of LARC patients are of great clinical significance.

AIM

To establish effective prognostic nomograms and risk score prediction models to predict overall survival (OS) and disease-free survival (DFS) for LARC treated with NT.

METHODS

Nomograms and risk factor score prediction models were based on patients who received NT at the Cancer Hospital from 2015 to 2017. The least absolute shrinkage and selection operator regression model were utilized to screen for prognostic risk factors, which were validated by the Cox regression method. Assessment of the performance of the two prediction models was conducted using receiver operating characteristic curves, and that of the two nomograms was conducted by calculating the concordance index (C-index) and calibration curves. The results were validated in a cohort of 65 patients from 2015 to 2017.

RESULTS

Seven features were significantly associated with OS and were included in the OS prediction nomogram and prediction model: Vascular_tumors_bolt, cancer nodules, yN, body mass index, matchmouth distance from the edge, nerve aggression and postoperative carcinoembryonic antigen. The nomogram showed good predictive value for OS, with a C-index of 0.91 (95%CI: 0.85, 0.97) and good calibration. In the validation cohort, the C-index was 0.69 (95%CI: 0.53, 0.84). The risk factor prediction model showed good predictive value. The areas under the curve for 3- and 5-year survival were 0.811 and 0.782. The nomogram for predicting DFS included ypTNM and nerve aggression and showed good calibration and a C-index of 0.77 (95%CI: 0.69, 0.85). In the validation cohort, the C-index was 0.71 (95%CI: 0.61, 0.81). The prediction model for DFS also had good predictive value, with an AUC for 3-year survival of 0.784 and an AUC for 5-year survival of 0.754.

CONCLUSION

We established accurate nomograms and prediction models for predicting OS and DFS in patients with LARC after undergoing NT.

Keywords: Neoadjuvant therapy; Rectal cancer; Nomogram; Overall survival; Disease-free survival; Risk factor score prediction model

Core Tip: The manuscript focuses on the risk factors after administration of neoadjuvant therapy for locally advanced rectal cancer. We utilized the least absolute shrinkage and selection operator and Cox regression to identify risk factors for overall survival and disease-free survival and explore their prognostic value. Based on the factors, we built two nomograms and two risk factor score prediction models to predict survival time. The nomograms were validated by calibration and the concordance index, and the prediction model was validated with receiver operating characteristic curves. The risk factors included in the model and nomograms are associated with survival and recurrence and can aid physicians to improve patient survival.