Shan Q, Shi J, Wang X, et al. - Herein, the focus was to build a nomogram integrated with some clinical parameters for survival prediction of small cell lung cancer (SCLC) patients with brain metastasis. Using the Surveillance, Epidemiology, and End Results database, a total of 3,522 eligible patients were identified and were randomly split into training and validation cohorts. Age, race, gender, T stage, N stage and marital status were revealed as independent prognostic factors in univariate and multivariate analysis, and were incorporated in the predictive model. Good discrimination ability of the predictive model was indicated by the receiver operating characteristic curves. Better prognosis of the low-risk group was evident in the total cohort, training cohort, as well as in validation cohort, compared with prognosis of the high-risk group. Overall, a nomogram as well as a corresponding risk classification system to predict overall survival in SCLC cases with brain metastasis was established herein, and clinical decision making as well as treatment stratification for patients could be aided by this model.