Development and validation of a nomogram for predicting moderate-to-severe complications following primary tumor resection in metastatic colorectal cancer

Background: Colorectal 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). Method: A 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. Results: A 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. Conclusion: This 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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Publication Details

Journal
Frontiers in Oncology
Published
2026-03-31
DOI
https://doi.org/10.3389/fonc.2026.1745535
Primary Topic
Colorectal Cancer Treatments and Studies
Type
article
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article

Development and validation of a nomogram for predicting moderate-to-severe complications following primary tumor resection in metastatic colorectal cancer

Yunlong Zhang, Junjie Xiong, Mi Yang, Kun Qian et al.
Frontiers in Oncology
Colorectal Cancer Treatments and Studies
article

Development and validation of a nomogram for predicting moderate-to-severe complications following primary tumor resection in metastatic colorectal cancer

Yunlong Zhang, Junjie Xiong, Mi Yang, Kun Qian, Jiaze Li, Yu Zou, Kemei Zhong, Hui Li
article en

Abstract

Background: Colorectal 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). Method: A 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. Results: A 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. Conclusion: This 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.

Frontiers in OncologyVol. 16
The Affiliated Yongchuan Hospital of Chongqing Medical University (CN), Chongqing Medical University (CN)
Good health and well-being
Openalex Percentile: Top 33%
Colorectal Cancer Treatments and Studies
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