Prognostic Nomogram for Predicting Survival in Asian Patients With Small-Cell Lung Cancer: A Comprehensive Population-Based Study and External Verification

Abstract

Background: The incidence of small cell lung cancer (SCLC) among Asian patients is on the rise. Nevertheless, there remains a deficiency in precise prognostic models tailored to the specific needs of this patient population. It is imperative to develop a novel nomogram aimed at forecasting the prognosis of Asian SCLC patients.

Methods: The SEER database supplied data on 661 Asian SCLC patients, who were then divided into training and internal validation sets through a random selection process. In addition, we identified 212 patients from a Chinese medical institution for the purpose of creating an external validation cohort. To forecast survival, we employed both univariate and multivariate analyses. The performance of our nomogram was assessed through calibration plots, the concordance index (C-index), and decision curve analysis (DCA).

Results: Five independent prognostic factors were determined and integrated into the nomogram. C-index values for the training and internal validation cohorts were 0.774 (95% confidence interval [CI] = 0.751-0.797) and 0.731 (95%CI = 0.690-0.772), respectively. In the external validation cohort, the C-index is 0.712 (95% CI = 0.655-0.7692). Calibration curves demonstrated highly accurate predictions. When compared to the AJCC staging system, our model exhibited improved net benefits in DCA. Furthermore, the risk stratification system effectively differentiated patients with varying survival risks.

Conclusion: We have created a novel nomogram for predicting the survival of Asian patients with SCLC. This nomogram has been subjected to external validation and has shown its superiority over the conventional TNM staging system. It offers a more precise and reliable means of forecasting the prognosis of Asian SCLC patients.

Keywords: Asian patients; nomogram; small cell lung cancer; survival prediction.

FIGURE 1

The flow chart of SEER database (a) and external validation cohort (b).

FIGURE 2

Nomogram predicting 1‐, 3, and 5‐year OS of Asian patients with small cell lung cancer.

FIGURE 3

Nomogram by Receiver operating characteristic (ROC) analyses. (a–c) ROC curves for discrimination in the training cohort for 1‐year (a), 3‐year (b), and 5‐year (c) overall survival. (d–f) ROC curves for discrimination in the internal validation cohort for 1‐year (d), 3‐year (e), and 5‐year (f) overall survival. AUC area under the curve.

FIGURE 4

Calibration curves. (a–c) The calibration curves of the model for (a) 1‐year, (b) 3‐year, and 5‐year and (c) overall survival in the training cohort. (d–f) The calibration curves of the model for (d) 1‐year, (e) 3‐year, and 5‐year and (f) overall survival in the validation cohort. Y‐axis indicated the actual survival probability and x‐axis indicated the predicated survival probability. The gray line indicated that prediction agrees with actuality. Error bars represent 95% confidence intervals.

FIGURE 5

Decision curve analyses (DCA) of the nomogram and 7^th edition AJCC TNM staging system for 1‐year (a), 3‐year (b), and 5‐year and (c) overall survival. The x‐axis represents the threshold probabilities, and the y‐axis measures the net benefit. The horizontal line along the x‐axis assumes that overall death occurred in no patients, whereas the solid gray line assumes that all patients will have overall death at a specific threshold probability.

FIGURE 6

Nomogram by receiver operating characteristic (ROC) analyses. (a–c) ROC curves for discrimination in the external validation cohort for 1‐year (a), 3‐year (b), and 5‐year (c) overall survival. Calibration curves, the calibration curves of the model for (d) 1‐year, (e) 3‐year, overall survival in the external validation cohort.

FIGURE 7

Kaplan–Meier survival analyses to test the risk stratification system within the training (a) and the external validation cohort (b).