Background: Small cell lung cancer (SCLC) is a highly aggressive neuroendocrine cancer with a high risk of early mortality (i.e., survival time less than 1 month). This study aimed to identify relevant risk factors and predict early mortality in SCLC patients.
Methods: A total of 27,163 SCLC cases registered between 2010 and 2019 were extracted from the Surveillance, Epidemiology, and End Results (SEER) data. Significant independent risk factors were identified by univariate and multivariate logistic regression analyses. Nomograms for all-causes and cancer-specific early death were constructed and evaluated.
Results: Age, sex, clinical stage, presence of metastasis (liver and lung), and absence of treatment (surgery, radiotherapy and chemotherapy) were identified for significant association with all-causes and cancer-specific early death. Nomograms based on these predictors exhibited high accuracy (area under ROC curve > 0.850) and potential clinical practicality in the prediction of early mortality.
Conclusion: We identified a set of factors associated with early mortality from SCLC and developed a clinically useful nomogram to predict high-risk patients. This nomogram could aid oncologists in the administration of individualized treatment regimens, potentially improving clinical outcomes of SCLC patients.
Keywords: Early mortality; Logistic regression analysis; Nomogram; SEER database; Small cell lung cancer.
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.