A nomogram to predict the risk of venous thromboembolism in patients with colon cancer in China

Abstract

Abstract Objective To create a nomogram for predicting the likelihood of venous thromboembolism (VTE) in colon cancer patients from China. Methods The data of colon cancer patients from Chongqing University Cancer Hospital between 2019 and 2022 were analyzed. Patients were divided into training set and internal validation set by random split‐sample method in a split ratio of 7:3. The univariable and multivariable logistic analysis gradually identified the independent risk factors for VTE. A nomogram was created using all the variables that had a significance level of p < 0.05 in the multivariable logistic analysis and those with clinical significance. Calibration curves and clinical decision curve analysis (DCA) were used to assess model's fitting performance and clinical value. Harrell's C‐index (concordance statistic) and the area under the receiver operating characteristic curves (AUC) were used to evaluate the predictive effectiveness of models. Results A total of 1996 patients were ultimately included. There were 1398 patients in the training set and 598 patients in the internal validation set. The nomogram included age, chemotherapy, targeted therapy, hypertension, activated partial thromboplastin time, prothrombin time, platelet, absolute lymphocyte count, and D‐dimer. The C‐index of nomogram and Khorana score were 0.754 (95% CI 0.711–0.798), 0.520 (95% CI 0.477–0.563) in the training cohort and 0.713 (95% CI 0.643–0.784), 0.542 (95% CI 0.473–0.612) in the internal validation cohort. Conclusions We have established and validated a nomogram to predict the VTE risk of colon cancer patients in China, which encompasses a diverse age range, a significant population size, and various clinical factors. It facilitates the identification of high‐risk groups and may enable the implementation of targeted preventive measures.

Keywords

• colon cancer
• nomogram
• predictive model
• venous thromboembolism