Graduate School, Dalian Medical University, Dalian, 116000, Liaoning, China.
Department of Thoracic Surgery, Qingdao Municipal Hospital, No.5 Donghai Middle Road, Qingdao, 266071, Shandong, China.
World J Surg Oncol. 2024 Jun 14;22(1):158. doi: 10.1186/s12957-024-03432-3.
To investigate the prognostic significance of the advanced lung cancer inflammation index (ALI) in patients with operable non-small-cell lung carcinoma (NSCLC). By constructing the nomogram model, it can provide a reference for clinical work.
A total of 899 patients with non-small cell lung cancer who underwent surgery in our hospital between January 2017 and June 2021 were retrospectively included. ALI was calculated by body mass index (BMI) × serum albumin/neutrophil to lymphocyte ratio (NLR). The optimal truncation value of ALI was obtained using the receiver operating characteristic (ROC) curve and divided into two groups. Survival analysis was represented by the Kaplan-Meier curve. The predictors of Overall survival (OS) were evaluated by the Cox proportional risk model using single factor and stepwise regression multifactor analysis. Based on the results of multi-factor Cox proportional risk regression analysis, a nomogram model was established using the R survival package. The bootstrap method (repeated sampling 1 000 times) was used for internal verification of the nomogram model. The concordance index (C-index) was used to represent the prediction performance of the nomogram model, and the calibration graph method was used to visually represent its prediction conformity. The application value of the model was evaluated by decision curve analysis (DCA).
The optimal cut-off value of ALI was 70.06, and the low ALI group (ALI < 70.06) showed a poor survival prognosis. In multivariate analyses, tumor location, pathological stage, neuroaggression, and ALI were independently associated with operable NSCLC-specific survival. The C index of OS predicted by the nomogram model was 0.928 (95% CI: 0.904-0.952). The bootstrap self-sampling method (B = 1000) was used for internal validation of the prediction model, and the calibration curve showed good agreement between the prediction and observation results of 1-year, 2-year, and 3-year OS. The ROC curves for 1-year, 2-year, and 3-year survival were plotted according to independent factors, and the AUC was 0.952 (95% CI: 0.925-0.979), 0.951 (95% CI: 0.916-0.985), and 0.939 (95% CI: 0.913-0.965), respectively. DCA shows that this model has good clinical application value.
ALI can be used as a reliable indicator to evaluate the prognosis of patients with operable NSCLC, and through the construction of a nomogram model, it can facilitate better individualized treatment and prognosis assessment.
探讨可手术非小细胞肺癌(NSCLC)患者中晚期肺癌炎症指数(ALI)的预后意义。通过构建列线图模型,为临床工作提供参考。
回顾性纳入 2017 年 1 月至 2021 年 6 月在我院接受手术的 899 例非小细胞肺癌患者。通过体质量指数(BMI)×血清白蛋白/中性粒细胞与淋巴细胞比值(NLR)计算 ALI。使用受试者工作特征(ROC)曲线获得 ALI 的最佳截断值,并将其分为两组。采用 Kaplan-Meier 曲线表示总生存期(OS)的生存分析。使用单因素和逐步回归多因素分析评估影响 OS 的预测因素。基于多因素 Cox 比例风险回归分析的结果,使用 R 生存包建立列线图模型。使用 bootstrap 方法(重复采样 1000 次)对列线图模型进行内部验证。使用一致性指数(C-index)表示列线图模型的预测性能,并使用校准图方法直观表示其预测一致性。通过决策曲线分析(DCA)评估模型的应用价值。
ALI 的最佳截断值为 70.06,低 ALI 组(ALI<70.06)的生存预后较差。多因素分析显示,肿瘤部位、病理分期、神经侵袭和 ALI 与可手术 NSCLC 特异性生存独立相关。列线图模型预测 OS 的 C 指数为 0.928(95%CI:0.904-0.952)。使用 bootstrap 自抽样方法(B=1000)对预测模型进行内部验证,校准曲线显示 1 年、2 年和 3 年 OS 的预测结果与观察结果吻合良好。根据独立因素绘制 1 年、2 年和 3 年生存的 ROC 曲线,AUC 分别为 0.952(95%CI:0.925-0.979)、0.951(95%CI:0.916-0.985)和 0.939(95%CI:0.913-0.965)。DCA 显示该模型具有良好的临床应用价值。
ALI 可作为评估可手术 NSCLC 患者预后的可靠指标,通过构建列线图模型,可有助于更好地进行个体化治疗和预后评估。