Objective To investigate the influencing factors for aggravation of early infec-tion after radical resection of colorectal cancer, and construct and validate its prediction model.

Methods The retrospective cohort study was conducted. The clinical data of 226 patients with early infection after radical resection of colorectal cancer at Xinxiang Central Hospital between January 2020 and May 2025 were collecetd. There were 136 males and 90 females, aged (65±13)years. Observation indicators: (1) analysis of influencing factors for aggravation of early infection after radical resection of colorectal cancer; (2) construction and validation of prediction model for aggra-vation of early infection after radical resection of colorectal cancer. Logistic regression model was used for univariate and multivariate analyses.Variables with P<0.05 in univariate analysis, or variables with clinical predictive value for postoperative infection and P<0.10, were included for multivariate analysis. Rare‑event Logistic regression was applied to verify the robustness of multivariate analysis results.The performance of prediction model was evaluated using the area under the receiver opera-ting characteristic curve, Hosmer‑Lemeshow test, calibration curve, and decision curve analysis.

Results (1) Analysis of influencing factors for aggravation of early infection after radical resection of colorectal cancer. Among 226 patients with early infection after radical resection of colorectal cancer,20 cases progressed to severe infection within 72 h after diagnosis. Results of multivariate analysis showed that anastomosis type, turbid abdominal drainage at 72 h postoperatively, procalci-tonin, heart rate, and sequential organ failure assessment (SOFA) score on the first day after surgery were independent influencing factors for aggravation of early infection after radical resection of colo-rectal cancer patients (odds ratio=2.34, 2.59, 2.05, 2.18, 2.41, 95% confidence interval as 1.35-4.05, 1.44-4.66, 1.23-3.42, 1.29-3.70, 1.37-4.26, P<0.05).(2) Construction and validation of prediction model for aggravation of early infection after radical resection of colorectal cancer. Based on the results of multivariate analysis, a prediction model for aggravation of early infection after radical resection of colorectal cancer was constructed. Receiver operating characteristic curve showed the area under the curve of prediction model as 0.76 (95% confidence interval as 0.66-0.86), with sensitivity as 0.68 and specificity as 0.63. The Hosmer‑Lemeshow test showed a P‑value of 0.535, indicating that the prediction model had a good fit. The calibration curve of the prediction model exhibited high consistency with the actual curve. Decision curve analysis showed a net clinical benefit for threshold probabilities between 0 and 0.90.

Conclusions Anastomosis type, turbid abdominal drainage at 72 h postoperatively, procalcitonin, heart rate, and SOFA score on the first day after surgery are independent influencing factors for aggravation of early infection after radical resection of colorectal cancer patients. A nomogram prediction model based on these variables demonstrate good predictive performance.