Real‐World Prognostic Analysis of Clinical Characteristics in Extensive‐Stage Small Cell Lung Cancer: A Nomogram for Survival Prediction in Patients Receiving First‐Line Immunochemotherapy With Serplulimab

BACKGROUND: Extensive-stage small cell lung cancer (ES-SCLC) has limited treatment options, with first-line immunochemotherapy providing modest survival benefits. OBJECTIVES: This single-center, retrospective study aimed to develop a prognostic nomogram using real-world data from ES-SCLC patients treated with serplulimab-based immunochemotherapy to identify key factors influencing overall survival (OS). MATERIALS AND METHODS: 109 ES-SCLC patients treated with first-line immunochemotherapy were analyzed. Baseline clinicopathological characteristics and hematological markers were assessed, and four prognostic factors - liver metastasis, maintenance therapy, albumin level, and neutrophil-to-lymphocyte ratio (NLR) - were identified by LASSO regression. A nomogram was constructed to predict 6-, 12-, and 24-month OS rates. The model's performance was validated with C-index, AUC, calibration curves, and decision curve analysis. RESULTS: The nomogram effectively stratified patients into low-, intermediate-, and high-risk groups with significant OS differences (log-rank p < 0.001). Patients with liver metastasis, no maintenance therapy, low albumin levels, and high NLR had worse outcomes. The C-index for the training and internal validation sets was 0.698 and 0.832, respectively, with AUC values exceeding 0.7 across most time points, suggesting favorable discrimination within this exploratory cohort. CONCLUSIONS: The identified nomogram provides an exploratory real-world tool for OS estimation in ES-SCLC patients receiving first-line serplulimab-based immunochemotherapy. By integrating baseline clinical factors and treatment-course information, the model may support dynamic risk stratification and help inform follow-up intensity, supportive care optimization, and prognostic counseling during routine clinical practice. Further prospective, multicenter external validation and time-dependent analyses are warranted to confirm and optimize its clinical applicability.