关键词: 结肠癌, 术后并发症, 列线图

Abstract: Objective The aim of this study was to develop and validate a nomogram for predicting postoperative complications after radical resection of colon cancer. Methods Retrospective analysis was conducted based on the relevant data of patients who underwent radical resection of colon cancer at Sun Yat-sen Memorial Hospital of Sun Yat-sen University from January 2019 to June 2021 which was extracted from the electronic medical record system. The main outcome variables of the study were postoperative complications. Cases that meet the inclusion criteria were randomly divided into a model training cohort and an internal validation cohort in a ratio of 7∶3. Firstly, the LASSO regression was used to screen potential influencing factors with non-zero regression coefficients. Then, multiple factor stepwise regression was performed on the selected potential risk factors ad select variables with P<0.05 to further construct a prediction model and visualize it using nomogram. The discriminability, calibration, and clinical application value of the model were evaluated through receiver operating characteristic curve （ROC curve）, calibration curve, and decision curve analysis （DCA）. Results The final prediction model included four variables： age, duration of surgery, postoperative admission to ICU, and preoperative D-dimer level. The area under the operating characteristic curve （AUC） of the training set and the validation set were 0.791 and 0.889, respectively. The calibration curve and DCA curve indicate that the model has good calibration and clinical practicality. Conclusion We have developed and validated a new predictive model for postoperative complications after radical resection of colon cancer, which only has 4 predictive factors but has good predictive performance. This new tool may help reduce postoperative complications and accelerate patient recovery.

Key words: colon cancer, postoperative complications, nomogram