Department of Medical Oncology, ZNA Middelheim, Antwerp, Belgium.
Department of Geriatric Medicine, University Hospitals Leuven, Leuven, Belgium.
Cancer. 2018 Sep 15;124(18):3764-3775. doi: 10.1002/cncr.31580. Epub 2018 Oct 9.
The current study was performed to evaluate the prognostic value of laboratory parameters and geriatric assessment (GA) in addition to a baseline model with clinical information regarding overall survival (OS) in patients with cancer.
GA was systematically performed in patients aged ≥70 years. The baseline model consisted of age, tumor type, and stage of disease. The incremental prognostic values of the GA as a whole (10-item GA) and laboratory parameters were assessed separately and combined. The parameters included hemoglobin (Hb), albumin, C-reactive protein (CRP), and the Glasgow Prognostic Score (GPS). Analyses were conducted with continuous and dichotomized variables. Cox models were compared based on Akaike information criterion (ΔAIC) and their discriminatory ability was assessed using the concordance probability estimate (CPE).
A total of 328 patients were considered for this analysis. The baseline model had a CPE of 0.725. The addition of CRP, albumin, and Hb combined resulted in the best performing model (ΔAIC: 40.12 and CPE: 0.757) among the laboratory parameters. However, the 10-item GA improved the baseline model even more (ΔAIC: 46.03 and CPE: 0.769). Similar results were observed in the analysis with dichotomous variables. The addition of the 3 laboratory parameters (CRP, albumin, and Hb) improved the CPE by 1.4% compared with the baseline model already extended with the 10-item GA. The CPE increase (1.7%) was the highest with the GPS in the analysis with dichotomous variables.
GA appears to add slightly more prognostic information than laboratory parameters in addition to clinical information. The laboratory parameters have an additional prognostic value beyond clinical and geriatric information.
本研究旨在评估实验室参数和老年评估(GA)除了包含癌症患者总生存(OS)相关临床信息的基线模型以外的预后价值。
对年龄≥70 岁的患者进行系统的 GA 评估。基线模型包含年龄、肿瘤类型和疾病分期。整体 GA(10 项 GA)和实验室参数的单独和联合的增量预后价值分别进行评估。参数包括血红蛋白(Hb)、白蛋白、C 反应蛋白(CRP)和格拉斯哥预后评分(GPS)。分析采用连续和二分类变量。基于赤池信息量准则(ΔAIC)比较 Cox 模型,并使用一致性概率估计(CPE)评估其判别能力。
共有 328 例患者纳入本分析。基线模型的 CPE 为 0.725。CRP、白蛋白和 Hb 联合检测可使模型的性能最佳(ΔAIC:40.12,CPE:0.757),在实验室参数中表现最佳。然而,10 项 GA 甚至可以进一步改善基线模型(ΔAIC:46.03,CPE:0.769)。二分类变量分析也观察到类似的结果。与已扩展包含 10 项 GA 的基线模型相比,添加 3 项实验室参数(CRP、白蛋白和 Hb)可使 CPE 提高 1.4%。在二分类变量分析中,GPS 的 CPE 增加(1.7%)最高。
GA 似乎比实验室参数在提供更多的预后信息,除了临床信息外。实验室参数在临床和老年信息之外具有额外的预后价值。