Related Experiment Video
Updated: May 22, 2026

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Development and internal-external validation of a nomogram for predicting postoperative 30-day malnutrition risk in
Fanyan Wei1, Yuxia Du2, Haifeng Hu3
1The 3rd Department of Gynecology, Northwest Women's and Children's Hospital No. 1616, Yanxiang Road, Yanta District, Xi'an 710000, Shaanxi, China.
Abstract:
Malnutrition at 30 days after surgery is common in cervical cancer patients and may adversely affect long-term outcomes. This retrospective study developed and validated an interpretable predictive nomogram for early identification of postoperative malnutrition (NRS-2002 ≥3) in patients with FIGO stage IB-IIA cervical cancer undergoing radical surgery. A total of 784 patients were included and divided into a training cohort (n=431), an internal validation cohort (n=180), and an independent external cohort (n=173). Clinical, sociodemographic, treatment-related, and laboratory variables were collected, and predictors were screened using univariate and multivariate logistic regression. Model discrimination, calibration, and clinical utility were assessed using the area under the receiver operating characteristic curve (AUC), Brier score, calibration analysis, decision curve analysis, and DeLong testing against albumin (ALB) alone. The final model incorporated eight independent predictors: age, body mass index (BMI), marital status, presence of a caregiver, parenteral nutrition support, lymph node metastasis, FIGO stage, and ALB. The nomogram achieved AUCs of 0.756, 0.742, and 0.807 in the training, internal validation, and external validation cohorts, respectively, with Brier scores ranging from 0.1859 to 0.2143, and showed stable net benefit across a wide threshold probability range (0.04-0.99). In the pooled sample, the nomogram significantly outperformed ALB alone (P<0.001). SHapley Additive exPlanations (SHAP) analysis enhanced interpretability and identified ALB, age, and lymph node metastasis as the most influential features driving predictions. Among 725 patients (92.5%) with follow-up data, 77 deaths (10.6%) occurred, and survival analyses demonstrated that unmarried status (HR=2.21), lymph node metastasis (HR=4.74), higher FIGO stage (HR=5.15), poor differentiation (HR=2.12), and higher risk scores (HR=1.88) were independently associated with worse overall survival, whereas human papillomavirus positivity was protective (HR=0.63). These findings suggest that the proposed nomogram provides accurate and explainable prediction of postoperative malnutrition and may support early risk stratification as well as long-term prognostic assessment in cervical cancer patients.
