Development and Validation of a Nomogram for Predicting Survival in Patients With Resected Non–Small-Cell Lung Cancer

TLDR

A nomogram is a useful and convenient tool for individualized cancer prognoses. The study aimed to develop a clinical nomogram to predict survival in patients with resected non‑small‑cell lung cancer. Using data from a multi‑institutional Chinese registry of 6,111 resected NSCLC patients and an external IASLC cohort of 2,148, the authors constructed and internally bootstrapped‑validated the nomogram, evaluating its accuracy with concordance indices and risk‑group stratification. The final nomogram incorporated six independent prognostic factors, demonstrated excellent calibration for 1‑, 3‑, and 5‑year overall survival, achieved higher concordance indices than the 7th edition AJCC TNM staging system (0.71 vs 0.68 in the primary cohort, 0.67 vs 0.64 in the IASLC cohort), and allowed clear risk stratification within TNM categories, providing a practical tool for clinicians.

Abstract

A nomogram is a useful and convenient tool for individualized cancer prognoses. We sought to develop a clinical nomogram for predicting survival of patients with resected non-small-cell lung cancer (NSCLC).On the basis of data from a multi-institutional registry of 6,111 patients with resected NSCLC in China, we identified and integrated significant prognostic factors for survival to build a nomogram. The model was subjected to bootstrap internal validation and to external validation with a separate cohort of 2,148 patients from the International Association for the Study of Lung Cancer (IASLC) database. The predictive accuracy and discriminative ability were measured by concordance index (C-index) and risk group stratification.A total of 5,261 patients were included for analysis. Six independent prognostic factors were identified and entered into the nomogram. The calibration curves for probability of 1-, 3-, and 5-year overall survival (OS) showed optimal agreement between nomogram prediction and actual observation. The C-index of the nomogram was higher than that of the seventh edition American Joint Committee on Cancer TNM staging system for predicting OS (primary cohort, 0.71 v 0.68, respectively; P < .01; IASLC cohort, 0.67 v 0.64, respectively; P = .06). The stratification into different risk groups allowed significant distinction between survival curves within respective TNM categories.We established and validated a novel nomogram that can provide individual prediction of OS for patients with resected NSCLC. This practical prognostic model may help clinicians in decision making and design of clinical studies.