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Updated: Jan 17, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Development and validation of a nomogram for predicting 90-day mortality in patients with advanced lung cancer based
Zanqin Wang1, Wenzhen Xun1, Xiangxing Ma1
1Department of Cardiothoracic Surgery, Sanmen People's Hospital Taizhou 317100, Zhejiang, China.
Abstract:
This retrospective study of 455 stage III/IV non-small cell lung cancer patients treated at Sanmen People's Hospital from January 2022 to January 2025 aimed to identify prognostic factors for short-term mortality and develop a validated nomogram for risk assessment. Patients were divided into training (n = 318) and validation (n = 137) cohorts, with clinical and laboratory variables - age, body mass index, Eastern Cooperative Oncology Group (ECOG) performance status, chronic obstructive pulmonary disease (COPD), C-reactive protein (CRP), interleukin-6 (IL-6), serum albumin (ALB), and lactate dehydrogenase (LDH) - analyzed using Kolmogorov-Smirnov tests for data distribution, and t-tests, Mann-Whitney U tests, and chi-square tests for comparisons. Logistic regression identified CRP ≥ 24.42 mg/L (odds ratio = 6.285, P = 0.002), IL-6 ≥ 28.705 pg/mL (odds ratio = 38.364, P < 0.001), and LDH ≥ 357 U/L (odds ratio = 10.132, P < 0.001) as predictors of increased mortality risk, while ALB ≥ 32.65 g/L (odds ratio = 0.073, P < 0.001) and ECOG score = 0 (odds ratio = 0.214, P = 0.040) were associated with reduced risk. Cox regression confirmed CRP, IL-6, ALB, LDH, and COPD as significant predictors. A nomogram constructed from these factors showed strong performance, with area under the curve values of 0.932, 0.930, and 0.962 for 30-, 60-, and 90-day mortality in the training cohort, and 0.894, 0.916, and 0.925 in the validation cohort, respectively, alongside concordance indices of 0.922 (training) and 0.877 (validation). Decision curve analysis and calibration plots confirmed robust clinical applicability and prognostic precision, establishing the nomogram as a reliable tool for personalized risk stratification in advanced lung cancer.
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