Department of Biochemistry and Molecular Biology, Basic Medical College, Qingdao University, Qingdao, China.
Department of Thoracic Surgery, The First Affiliated Hospital Shaoyang University, Shaoyang, China.
J Int Med Res. 2024 Sep;52(9):3000605241238689. doi: 10.1177/03000605241238689.
Combined small cell lung cancer (CSCLC) with distant metastasis (DM) is an aggressive disease with a poor prognosis. Effective nomograms are needed to predict DM and early death in patients with CSCLC and DM.
This retrospective study included patients with CSCLC from the Surveillance, Epidemiology, and End Results database between 2004 and 2015. Risk factors for DM and early death were analyzed by univariate and multivariate logistic regression. Nomograms were constructed based on the results in a training cohort and confirmed in a validation cohort, and their performances were assessed by concordance index (C-index), receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA).
A total of 788 patients with CSCLC were selected, including 364 patients with metastatic CSCLC. Sex, tumor site, T stage, and N stage were independent risk factors for DM, while age, surgery, chemotherapy, and liver metastasis were independent risk factors for early death. C-index, ROC, calibration, and DCA curve analyses all showed good predictive performances for both nomograms.
These nomograms could reliably predict DM risk in CSCLC patients and early death in CSCLC patients with DM, and may thus help clinicians to assess these risks and implement individualized therapies.
广泛期小细胞肺癌(CSCLC)伴远处转移(DM)是一种侵袭性疾病,预后较差。需要有效的列线图来预测 CSCLC 伴 DM 患者的 DM 和早期死亡风险。
本回顾性研究纳入了 2004 年至 2015 年监测、流行病学和最终结果数据库中的 CSCLC 患者。通过单因素和多因素逻辑回归分析 DM 和早期死亡的危险因素。基于训练队列的结果构建列线图,并在验证队列中进行验证,通过一致性指数(C 指数)、接受者操作特征曲线(ROC)、校准曲线和决策曲线分析(DCA)评估其性能。
共纳入 788 例 CSCLC 患者,其中 364 例为转移性 CSCLC 患者。性别、肿瘤部位、T 分期和 N 分期是 DM 的独立危险因素,而年龄、手术、化疗和肝转移是早期死亡的独立危险因素。C 指数、ROC、校准和 DCA 曲线分析均表明,这两个列线图对 DM 风险和 CSCLC 伴 DM 患者的早期死亡风险均具有良好的预测性能。
这些列线图可以可靠地预测 CSCLC 患者的 DM 风险和 CSCLC 伴 DM 患者的早期死亡风险,从而帮助临床医生评估这些风险并实施个体化治疗。