Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Beijing International Science and Technology Cooperation Base for Cancer Metabolism and Nutrition, Beijing, China.
J Cachexia Sarcopenia Muscle. 2023 Apr;14(2):869-878. doi: 10.1002/jcsm.13199. Epub 2023 Feb 28.
Systemic inflammation, the most representative tumour-host interaction, plays a crucial role in disease progression and prognosis in patients with non-small cell lung cancer (NSCLC). Few studies have compared the performance of existing haematological systemic inflammation biomarkers in predicting the prognosis of NSCLC patients. The purpose of this study was to compare the prognostic value of existing systemic inflammation biomarkers and determine the optimal systemic inflammation biomarker in patients with NSCLC through a multicentre prospective study.
The predictive accuracy of systemic inflammation biomarkers for prognostic assessment in NSCLC was assessed using C-statistics. Inter-group differences in survival were assessed using the log-rank test and visualized using the Kaplan-Meier method. A restricted cubic spline (RCS) curve was used to explore the association between the biomarkers and survival. Independent prognostic biomarkers for overall survival were determined using multivariable Cox proportional hazards regression analysis. Logistic regression analysis was used to determine independent predictors of 90-day outcomes, length of hospitalization, hospitalization expenses and cachexia.
The inflammatory burden index (IBI) had the highest C-statistic for predicting the prognosis of patients with NSCLC, reaching 0.640 (0.617, 0.663). Patients with a high IBI had significantly worse outcomes than those with a low IBI (35.46% vs. 57.22%; log-rank P < 0.001). The IBI was also able to differentiate the prognosis of patients with NSCLC with the same pathological stage. The RCS curve showed an inverted L-shaped dose-response relationship between the IBI and survival of patients with NSCLC. Multivariable Cox proportional hazards regression analysis showed that a high IBI was an independent risk factor for death of patients with NSCLC (hazard ratio = 1.229, 95% confidence interval [CI]: 1.131-1.335, P < 0.001). A high IBI was an independent predictor of 90-day outcomes (odds ratio [OR] = 1.789, 95% CI: 1.489-2.151, P < 0.001), prolonged hospital stays (OR = 1.560, 95% CI: 1.256-1.938, P < 0.001), high hospitalization expenses (OR = 1.476, 95% CI: 1.195-1.822, P < 0.001) and cachexia (OR = 1.741, 95%CI = 1.374-2.207, P < 0.001) in patients with NSCLC.
The IBI was independently associated with overall survival, 90-day outcomes, length of hospitalization, hospitalization expenses and cachexia in NSCLC patients. As an optimal systemic inflammation biomarker, the IBI has broad clinical application prospects in predicting the prognosis of patients with NSCLC.
全身性炎症是最具代表性的肿瘤-宿主相互作用，在非小细胞肺癌（NSCLC）患者的疾病进展和预后中起着关键作用。很少有研究比较现有的血液系统炎症生物标志物在预测 NSCLC 患者预后方面的性能。本研究旨在通过多中心前瞻性研究比较现有的全身性炎症生物标志物的预后价值，并确定 NSCLC 患者最佳的全身性炎症生物标志物。
使用 C 统计量评估全身性炎症生物标志物对 NSCLC 预后评估的预测准确性。使用对数秩检验比较生存组间差异，并使用 Kaplan-Meier 方法可视化。限制性立方样条（RCS）曲线用于探索生物标志物与生存之间的关联。使用多变量 Cox 比例风险回归分析确定总生存期的独立预后生物标志物。使用逻辑回归分析确定 NSCLC 患者 90 天结局、住院时间、住院费用和恶病质的独立预测因素。
炎症负担指数（IBI）预测 NSCLC 患者预后的 C 统计量最高，达到 0.640（0.617，0.663）。高 IBI 患者的结局明显差于低 IBI 患者（35.46%比 57.22%；对数秩 P<0.001）。IBI 还能够区分具有相同病理分期的 NSCLC 患者的预后。RCS 曲线显示 IBI 与 NSCLC 患者生存之间呈倒 L 形剂量反应关系。多变量 Cox 比例风险回归分析显示，高 IBI 是 NSCLC 患者死亡的独立危险因素（风险比=1.229，95%置信区间[CI]：1.131-1.335，P<0.001）。高 IBI 是 90 天结局（比值比[OR]：1.789，95%CI：1.489-2.151，P<0.001）、延长住院时间（OR：1.560，95%CI：1.256-1.938，P<0.001）、高住院费用（OR：1.476，95%CI：1.195-1.822，P<0.001）和恶病质（OR：1.741，95%CI：1.374-2.207，P<0.001）的独立预测因素。
IBI 与 NSCLC 患者的总生存期、90 天结局、住院时间、住院费用和恶病质独立相关。作为一种最佳的全身性炎症生物标志物，IBI 在预测 NSCLC 患者预后方面具有广阔的临床应用前景。
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