Department of Respiratory and Critical Care Medicine, Maoming People's Hospital, Maoming, China.
Department of Otolaryngology, Maoming People's Hospital, Maoming, China.
Sci Rep. 2023 Sep 11;13(1):14947. doi: 10.1038/s41598-023-41972-y.
Small-cell lung cancer (SCLC) is an aggressive lung cancer subtype with an extremely poor prognosis. The 5-year survival rate for limited-stage (LS)-SCLC cancer is 10-13%, while the rate for extensive-stage SCLC cancer is only 1-2%. Given the crucial role of the tumor stage in the disease course, a well-constructed prognostic model is warranted for patients with LS-SCLC. The LS-SCLC patients' clinical data extracted from the Surveillance, Epidemiology, and End Results (SEER) database between 2000 and 2018 were reviewed. A multivariable Cox regression approach was utilized to identify and integrate significant prognostic factors. Bootstrap resampling was used to validate the model internally. The Area Under Curve (AUC) and calibration curve evaluated the model's performance. A total of 5463 LS-SCLC patients' clinical data was collected from the database. Eight clinical parameters were identified as significant prognostic factors for LS-SCLC patients' OS. The predictive model achieved satisfactory discrimination capacity, with 1-, 2-, and 3-year AUC values of 0.91, 0.88, and 0.87 in the training cohort; and 0.87, 0.87, and 0.85 in the validation cohort. The calibration curve showed a good agreement with actual observations in survival rate probability. Further, substantial differences between survival curves of the different risk groups stratified by prognostic scores were observed. The nomogram was then deployed into a website server for ease of access. This study developed a nomogram and a web-based predictor for predicting the overall survival of patients with LS-SCLC, which may help physicians make personalized clinical decisions and treatment strategies.
小细胞肺癌（SCLC）是一种侵袭性肺癌亚型，预后极差。局限期（LS）-SCLC 癌症的 5 年生存率为 10-13%，而广泛期 SCLC 癌症的生存率仅为 1-2%。鉴于肿瘤分期在疾病过程中的重要作用，LS-SCLC 患者需要构建一个良好的预后模型。本研究回顾了 2000 年至 2018 年期间从监测、流行病学和最终结果（SEER）数据库中提取的 LS-SCLC 患者的临床数据。采用多变量 Cox 回归方法识别并整合显著的预后因素。使用 Bootstrap 重采样对内进行模型验证。曲线下面积（AUC）和校准曲线评估模型性能。共从数据库中收集了 5463 例 LS-SCLC 患者的临床资料。确定了 8 个临床参数为 LS-SCLC 患者 OS 的显著预后因素。预测模型具有良好的区分能力，在训练队列中，1、2 和 3 年 AUC 值分别为 0.91、0.88 和 0.87；在验证队列中，1、2 和 3 年 AUC 值分别为 0.87、0.87 和 0.85。校准曲线显示，在生存率概率方面与实际观察结果吻合良好。进一步观察到，根据预后评分分层的不同风险组之间的生存曲线存在显著差异。然后将列线图部署到一个网站服务器中，以便于访问。本研究开发了一个列线图和一个基于网络的预测器，用于预测 LS-SCLC 患者的总生存率，这可能有助于医生做出个性化的临床决策和治疗策略。
