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A novel nomogram predicting cancer-specific survival in small cell lung cancer patients with brain metastasis
Yu-Ting Rong1, Ying-Chun Zhu2, Yang Wu3
1Division of Life Sciences and Medicine, Department of Neurology, The First Affiliated Hospital, University of Science and Technology of China, Hefei, China.
Background:
Brain metastasis (BM) is one of the most common metastatic sites in patients with small cell lung cancer (SCLC), and the prognosis remains very poor. This study aimed to establish a novel nomogram for predicting the cancer-specific survival (CSS) in SCLC patients with BM.
Methods:
SCLC patients with BM from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015 were retrospectively collected. Univariate and multivariate Cox regression analyses were performed to identify independent prognostic factors, which were further used to construct the prognostic nomogram. The discrimination and calibration of nomogram were evaluated by concordance index (C-index), receiver operating characteristic (ROC) curve, the area under ROC curve (AUC) and calibration plot. Decision curve analysis (DCA) was used to assess the clinical usefulness. Kaplan-Meier survival curve was applied to analyze the survival outcome.
Results:
A total of 2,462 patients were enrolled in this study, and randomly assigned into training cohort (n=1,723) and validation cohort (n=739). Age, N stage, surgery, radiation, chemotherapy, bone metastasis, liver metastasis and lung metastasis were identified as independent prognostic factors of CSS. The C-indexes of nomogram was 0.683 [95% confidence interval (CI): 0.667-0.699] in the training cohort, and 0.659 (95% CI: 0.634-0.684) in the validation cohort. The AUC values of 6-, 9- and 12-month CSS were 0.723, 0.742 and 0.737 respectively in the training cohort, while 0.715, 0.737 and 0.739 in the validation cohort. The ROC, calibration and DCA curves showed good discrimination, calibration and clinical applicability of this nomogram in predicting prognosis. Moreover, patients in high-risk group had a worse survival outcome than patients in medium-risk and low-risk groups.
Conclusions:
A novel nomogram was constructed and validated for predicting individual prognosis in SCLC patients with BM. This nomogram could help clinicians make effective treatment strategies for patients.
