本研究旨在开发和验证一个预测小细胞肺癌（SCLC）脑转移（BM）的诊断曲线图（nomogram），探索危险因素并协助临床决策。我们回顾了2015年到2021年间SCLC患者的临床数据。选择2015年到2019年的患者作为开发组，2020年到2021年的患者作为外部验证组。使用最小绝对收缩和选择算子（LASSO）逻辑回归分析分析临床指标。通过自助重抽样构建和验证最终的诊断曲线图。总共包括了631名2015年至2019年的SCLC患者来构建模型。性别、T分期、N分期、东部协作肿瘤学组织（ECOG）、血红蛋白（HGB）、淋巴绝对值（LYMPH #）、血小板（PLT）、视黄醇结合蛋白（RBP）、癌胚抗原（CEA）和神经元特异性烯醇酶（NSE）被识别为危险因素并包括在模型中。内部验证的C指数为0.830和0.788，通过1000个自助重抽样得到。校准图表明预测概率与实际概率之间的协议非常好。决策曲线分析（DCA）显示，在更广泛的阈值概率范围内具有更好的净利益（净临床利益为1％-58％）。该模型在2020年和2021年的患者中又进行了外部验证，C指数为0.818。我们开发和验证了一个诊断曲线图，以预测SCLC患者BM的风险，有助于临床医生合理安排随访并及时实施干预。©2023作者。由John Wiley＆Sons Ltd.出版的临床呼吸杂志发表

The aim was to develop and validate a nomogram for the prediction of brain metastases (BM) in small cell lung cancer (SCLC), to explore the risk factors and assist clinical decision-making.We reviewed the clinical data of SCLC patients between 2015 and 2021. Patients between 2015 and 2019 were included to develop, whereas patients between 2020 and 2021 were used for external validation. Clinical indices were analysed by using the least absolute shrinkage and selection operator (LASSO) logistic regression analyses. The final nomogram was constructed and validated by bootstrap resampling.A total of 631 SCLC patients between 2015 and 2019 were included to construct model. Gender, T stage, N stage, Eastern Cooperative Oncology Group (ECOG), haemoglobin (HGB), the absolute value of lymphocyte (LYMPH #), platelet (PLT), retinol-binding protein (RBP), carcinoembryonic antigen (CEA) and neuron-specific enolase (NSE) were identified as risk factors and included into the model. The C-indices were 0.830 and 0.788 in the internal validation by 1000 bootstrap resamples. The calibration plot revealed excellent agreement between the predicted and the actual probability. Decision curve analysis (DCA) showed better net benefits with a wider range of threshold probability (net clinical benefit was 1%-58%). The model was further externally validated in patients between 2020 and 2021 with a C-index of 0.818.We developed and validated a nomogram to predict the risk of BM in SCLC patients, which could help clinicians to rationally schedule follow-ups and promptly implement interventions.© 2023 The Authors. The Clinical Respiratory Journal published by John Wiley & Sons Ltd.