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晚期肺癌炎症指数是肺癌患者总生存期的最佳炎症生物标志物。

The advanced lung cancer inflammation index is the optimal inflammatory biomarker of overall survival in patients with lung cancer.

机构信息

Department of Gastrointestinal Surgery/Clinical Nutrition, Capital Medical University Affiliated Beijing Shijitan Hospital, Beijing, China.

Key Laboratory of Cancer FSMP for State Market Regulation, Beijing, China.

出版信息

J Cachexia Sarcopenia Muscle. 2022 Oct;13(5):2504-2514. doi: 10.1002/jcsm.13032. Epub 2022 Jul 14.

DOI:10.1002/jcsm.13032
PMID:35833264
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9530543/
Abstract

BACKGROUNDS

Malnutrition and systemic inflammatory responses are associated with poor overall survival (OS) in lung cancer patients, but it remains unclear which biomarkers are better for predicting their prognosis. This study tried to determine the best one among the existing common nutrition/inflammation-based indicators of OS for patients with lung cancer.

MATERIALS AND METHODS

There were 16 nutrition or systemic inflammation-based indicators included in this study. The cut-off points for the indicators were calculated using maximally selected rank statistics. The OS was evaluated using the Kaplan-Meier estimator, and univariate and multivariate Cox proportional hazard models were used to determine the relationship between the indicators and OS. A time-dependent receiver operating characteristic curves (time-ROC) and C-index were calculated to assess the predictive ability of the different indicators.

RESULTS

There were 1772 patients with lung cancer included in this study. In univariate analysis, all 16 indicators were significantly associated with OS of the patients (all P < 0.001). Except for platelet-to-lymphocyte ratio, all other indicators were independent predictors of OS in multivariate analysis (all P < 0.05). Low advanced lung cancer inflammation index (ALI) was associated with higher mortality risk of lung cancer [hazard ratio, 1.30; 95% confidence interval (CI), 1.13-1.49]. The results of the time-AUC and C-index analyses indicated that the ALI (C-index: 0.611) had the best predictive ability on the OS in patients with lung cancer. In different sub-groups, the ALI was the best indicator for predicting the OS of lung cancer patients regardless of sex (C-index, 0.609 for men and 0.613 for women) or smoking status (C-index, 0.629 for non-smoker and 0.601 for smoker) and in patients aged <65 years (C-index, 0.613). However, the modified Glasgow prognostic score was superior to the other indicators in non-small cell lung cancer patients (C-index, 0.639) or patients aged ≥65 years (C-index, 0.610), and the glucose-to-lymphocyte ratio performed better prognostic ability in patients with small cell lung cancer (C-index, 0.601).

CONCLUSIONS

The prognostic ability of the ALI is superior to the other inflammation/nutrition-based indicators for all patients with lung cancer.

摘要

背景

营养不良和全身炎症反应与肺癌患者的总体生存(OS)不良相关,但目前尚不清楚哪种生物标志物更能预测其预后。本研究试图确定肺癌患者 OS 现有常用营养/炎症指标中最好的指标。

材料与方法

本研究共纳入 16 项营养或全身炎症指标。使用最大选择秩统计计算指标的截止值。使用 Kaplan-Meier 估计器评估 OS,并使用单变量和多变量 Cox 比例风险模型确定指标与 OS 之间的关系。计算时间依赖性接收者操作特征曲线(time-ROC)和 C 指数以评估不同指标的预测能力。

结果

本研究共纳入 1772 例肺癌患者。单因素分析中,所有 16 项指标均与患者 OS 显著相关(均 P<0.001)。除血小板与淋巴细胞比值外,多因素分析中所有其他指标均为 OS 的独立预测因子(均 P<0.05)。低高级肺癌炎症指数(ALI)与肺癌死亡率升高相关[风险比,1.30;95%置信区间(CI),1.13-1.49]。时间-AUC 和 C 指数分析结果表明,ALI(C 指数:0.611)对肺癌患者 OS 的预测能力最佳。在不同亚组中,无论性别(男性 C 指数为 0.609,女性为 0.613)或吸烟状态(非吸烟者 C 指数为 0.629,吸烟者为 0.601)如何,ALI 均是预测肺癌患者 OS 的最佳指标,并且在年龄<65 岁的患者中(C 指数为 0.613)也是如此。然而,改良格拉斯哥预后评分在非小细胞肺癌患者(C 指数为 0.639)或年龄≥65 岁的患者(C 指数为 0.610)中优于其他指标,而葡萄糖与淋巴细胞比值在小细胞肺癌患者中具有更好的预后能力(C 指数为 0.601)。

结论

ALI 的预后能力优于肺癌患者所有其他炎症/营养指标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d60/9530543/892c13f9a113/JCSM-13-2504-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d60/9530543/694b182fbc9a/JCSM-13-2504-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d60/9530543/78153504bc69/JCSM-13-2504-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d60/9530543/b9ae5a6f9df6/JCSM-13-2504-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d60/9530543/e5e7057d5327/JCSM-13-2504-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d60/9530543/892c13f9a113/JCSM-13-2504-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d60/9530543/694b182fbc9a/JCSM-13-2504-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d60/9530543/78153504bc69/JCSM-13-2504-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d60/9530543/b9ae5a6f9df6/JCSM-13-2504-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d60/9530543/e5e7057d5327/JCSM-13-2504-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d60/9530543/892c13f9a113/JCSM-13-2504-g002.jpg

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