Abdelbari Baitar1, Cindy Kenis2,3, Lore Decoster4, Jacques De Grève4, Jean-Pierre Lobelle5, Johan Flamaing2,6, Koen Milisen2,7, Hans Wildiers3,8. 1. Department of Medical Oncology, ZNA Middelheim, Antwerp, Belgium. 2. Department of Geriatric Medicine, University Hospitals Leuven, Leuven, Belgium. 3. Department of General Medical Oncology, University Hospitals Leuven, Leuven, Belgium. 4. Department of Medical Oncology, Oncologisch Centrum, Universitair Ziekenhuis Brussel, Vrije Universiteit Brussel, Brussels, Belgium. 5. Consultant in Statistics, Beernem, Belgium. 6. Department of Clinical and Experimental Medicine, KU Leuven, Leuven, Belgium. 7. Department of Public Health and Primary Care, Health Services and Nursing Research, KU Leuven, Leuven, Belgium. 8. Department of Oncology, KU Leuven, Leuven, Belgium.
Abstract
BACKGROUND: 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. METHODS: 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). RESULTS: 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. CONCLUSIONS: 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.
BACKGROUND: 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. METHODS: 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). RESULTS: 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. CONCLUSIONS: 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.