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Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
A nomogram for predicting good response after neoadjuvant chemoradiotherapy for locally advanced rectal cancer: a
Guancong Wang1, Zhifang Zheng2, Jinhua Chen3
1Department of Colorectal and Anal Surgery, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, 363000, China.
Aim:
The purpose of this study was to explore the clinical factors associated with achieving good response after neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC) and to develop and validate a nomogram.
Methods:
A total of 1724 consecutive LARC patients treated at Fujian Medical University Union Hospital from January 2010 to December 2021 were retrospectively evaluated as the training cohort; 267 consecutive LARC patients treated at Zhangzhou Affiliated Hospital of Fujian Medical University during the same period were evaluated as the external 2 cohorts. Based on the pathological results after radical surgery, treatment response was defined as follows: good response, stage ypT0∼2N0M0 and poor response, ypT3∼4N0M0 and/or N positive. Independent influencing factors were analyzed by logistic regression, a nomogram was developed and validated, and the model was evaluated using internal and external data cohorts for validation.
Results:
In the training cohort, 46.6% of patients achieved good response after nCRT combined with radical surgery. The rate of the retained anus was higher in the good response group (93.5% vs. 90.7%, P < 0.001). Cox regression analysis showed that the risk of overall survival and disease-free survival was significantly lower among good response patients than poor response patients, HR = 0.204 (95%CI: 0.146-0.287). Multivariate logistic regression analysis showed an independent association with 9 clinical factors, including histopathology, and a nomogram with an excellent predictive response was developed accordingly. The C-index of the predictive accuracy of the nomogram was 0.764 (95%CI: 0.742-0.786), the internal validation of the 200 bootstrap replication mean C-index was 0.764, and the external validation cohort showed an accuracy C-index of 0.789 (95%CI: 0.734-0.844), with good accuracy of the model.
Conclusion:
We identified factors associated with achieving good response in LARC after treatment with nCRT and developed a nomogram to contribute to clinical decision-making.
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