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Nomogram predicts moderate-to-severe complications after primary tumor resection in metastatic colorectal cancer

Nomogram predicts moderate-to-severe complications after primary tumor resection in metastatic color…
Photo by Alexander Grey / Unsplash
Key Takeaway
Consider preoperative albumin, age, tumor location, and operation duration as risk factors for complications after PTR in mCRC.

A retrospective cohort study at a single institution analyzed 404 patients with metastatic colorectal cancer who underwent primary tumor resection. The study aimed to develop and validate a nomogram to predict moderate-to-severe postoperative complications within 30 days. The comparator was not reported. The main outcome was moderate-to-severe complications, with rates of 90/282 (32%) in the development group and 47/122 (39%) in the validation group. The analysis identified four independent risk factors: age (OR=1.041, p=0.017), preoperative albumin level (OR=0.774, p<0.001), tumor location (OR=2.243, p=0.012), and operation duration (OR=1.007, p<0.001). Safety data were limited to reporting moderate-to-severe postoperative complications; serious adverse events, discontinuations, and tolerability were not reported. Key limitations include the retrospective design and single-institution setting, which limit generalizability. The study developed a predictive tool, but its clinical utility requires external validation in broader populations. For practice, this nomogram may help identify higher-risk patients preoperatively, but its predictions represent statistical associations from retrospective data and should not be overinterpreted as causal. Funding and conflicts of interest were not reported.

Study Details

Study typeCohort
EvidenceLevel 3
PublishedMar 2026
View Original Abstract ↓
BackgroundColorectal cancer has high incidence and mortality. Surgery is the primary curative treatment, but postoperative complications remain common. This study developed and validated a nomogram to predict moderate-to-severe complications after primary tumor resection(PTR) in metastatic colorectal cancer (mCRC).MethodA retrospective analysis of clinical data was conducted for mCRC patients undergoing PTR at our institution between January 2022 and December 2024. All patients were randomly divided into two groups: 70% for development and 30% for validation. Univariate and multivariate logistic regression analyses were conducted to identify the independent risk factors associated with moderate-to-severe complications occurring within 30 days postoperatively. Correlation heatmaps and Lasso regression analysis were employed to systematically screen and identify the most relevant variables. Subsequently, a nomogram was developed based on the significant predictors. The area under the curve (AUC) was determined based on the receiver operating characteristic (ROC) curve for assessing the predictive probability. A calibration curve was generated to contrast the predicted probability against the observed probability. The clinical utility of the nomogram was evaluated using decision curve analysis (DCA). Internal 10-fold cross-validation was performed using bootstrapping, and boxplots as well as the average calibration curve were generated to visualize the results.ResultsA total of 404 mCRC patients receiving PTR treatment were enrolled, including 282 in the development group and 122 in the validation group. Of these, 32% (90) in the development group and 39% (47) in the validation group experienced moderate-to-severe postoperative complications. Multivariate Logistic regression analysis identified age (p = 0.017, OR = 1.041, 95% CI: 1.007–1.076), preoperative albumin level (p < 0.001, OR = 0.774, 95% CI: 0.704–0.851), tumor location (p = 0.012, OR = 2.243, 95% CI: 1.216–4.906), and operation duration (p < 0.001, OR = 1.007, 95% CI: 1.003–1.011) as independent risk factors for moderate-to-severe complications after PTR surgery. Based on these findings, a nomogram was developed and validated.ConclusionThis study identified four independent risk factors for moderate-to-severe complications in mCRC patients after PTR surgery and developed a reliable predictive model to assist surgeons in optimizing perioperative management for high-risk cases.
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