Outcomes and Prognostic Factors of Extensive Stage Small Cell Lung Cancer: A Retrospective Study

Abstract

Introduction Small cell lung cancer (SCLC) represents about 15% of all lung cancers. Extensive stage (ES) SCLC represents around 60% of diagnosed SCLC cancers. The median survival in untreated ES SCLC is 2 to 4 months and that of treated cases is 8 to 13 months. Aim and Objectives This retrospective analysis aims to find out the clinical outcome of patients with ES SCLC and the prognostic factors affecting their survival. Methods Details of patients registered in the department of radiation oncology from January 1, 2010 to September 30, 2019 were retrieved from the hospital records. This includes the demographic characteristics, treatment received, toxicity, and follow-up details. Results Two-hundred eighty-three patients were included. Median age of presentation was 62 years. Around 97.5% of patients were men. Smokers constitute 94% of all cases. About 86.9% (246 patients) of cases were not alive at the end of the study period. The median estimated overall survival (OS) was 7 months ± 0.47 (95% confidence interval [CI]: 6.026–7.974) and progression-free survival (PFS) was 5 months ± 0.535 (95% CI: 3.952–6.048). Multivariate analysis showed that Eastern Cooperative Oncology Group performance status (ECOG PS), hyponatremia, number of chemotherapy cycles, consolidative radiotherapy (RT) and prophylactic cranial irradiation (PCI) were found to have prognostic effect on OS. Smoking, ECOG PS, number of chemotherapy cycles, consolidative RT, and PCI were found to have prognostic effects on PFS. Conclusion There is a difference in OS and PFS patterns of ES SCLC patients among various Indian studies even though the available data is scarce. Our study shows that the OS and PFS of our study population are comparable to other South Indian studies available. PS, serum sodium level, number of chemotherapy cycles, consolidative RT, and PCI were found to be independent prognostic factors for survival of ES SCLC. The identification of these factors will help physicians to tailor treatment.