A Nomogram for Predicting Survival in Patients With Colorectal Cancer Incorporating Cardiovascular Comorbidities

BackgroundCardiovascular comorbidities (CVCs) affect the overall survival (OS) of patients with colorectal cancer (CRC). However, a prognostic evaluation system for these patients is currently lacking. ObjectivesThis study aimed to develop and validate a nomogram, which takes CVCs into account, for predicting the survival of patients with CRC. MethodsIn total, 21,432 patients with CRC were recruited from four centers in China between January 2011 and December 2017. The nomogram was constructed, based on Cox regression, using a training cohort (19,102 patients), and validated using a validation cohort (2,330 patients). The discrimination and calibration of the model were assessed by the concordance index and calibration curve. The clinical utility of the model was measured by decision curve analysis (DCA). Based on the nomogram, we divided patients into three groups: low, middle, and high risk. ResultsIndependent risk factors selected into our nomogram for OS included age, metastasis, malignant ascites, heart failure, and venous thromboembolism, whereas dyslipidemia was found to be a protective factor. The c-index of our nomogram was 0.714 (95% CI: 0.708-0.720) in the training cohort and 0.742 (95% CI: 0.725-0.759) in the validation cohort. The calibration curve and DCA showed the reliability of the model. The cutoff values of the three groups were 68.19 and 145.44, which were also significant in the validation cohort (p < 0.001). ConclusionTaking CVCs into account, an easy-to-use nomogram was provided to estimate OS for patients with CRC, improving the prognostic evaluation ability.

Automated summary

A validated nomogram was developed to predict the survival of colorectal cancer patients, taking cardiovascular comorbidities into account. The nomogram includes independent risk factors such as age, metastasis, malignant ascites, heart failure, and venous thromboembolism. The nomogram showed reliable prognostic evaluation ability.