Jae Jin Lee1, Jongphil Kim2, Marina Sehovic1, Lu Chen3, Martine Extermann4. 1. Senior Adult Oncology Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, USA. 2. Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, USA; Department of Oncology Sciences, University of South Florida, Tampa, Florida, USA. 3. Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, USA. 4. Senior Adult Oncology Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, USA; Department of Oncology Sciences, University of South Florida, Tampa, Florida, USA. Electronic address: martine.extermann@moffitt.org.
Abstract
OBJECTIVE: To date, most comorbidity studies have analyzed either a subgroup of frequent diseases, or used summary instruments such as the Charlson score or the Cumulative Illness Rating Scale-Geriatric (CIRS-G). Yet, comorbidity is a multidimensional construct and impacts function, treatment tolerance, and survival. We assessed how heat maps can unveil specific patterns of comorbidities associated with overall survival (OS) in older cancer patients treated with chemotherapy. MATERIAL AND METHODS: We reviewed four trials that prospectively evaluated comorbidities using CIRS-G. Eligible patients were 65years or older and had solid tumors with 30 or more patients per tumor site. Heat maps were constructed based on CIRS-G scores and correlated with OS. RESULTS: Among 818 patients accrued, 399 were eligible: Median follow-up was 53.4months and median OS was 19.6months (95% CI: 16.5-24.2). In the univariate model for OS, patients with a severe CIRS-G score in 6 organ categories (3-4 in heart, hematopoietic, respiratory, and musculoskeletal-integument and 2-4 in upper GI and liver) had statistically worse OS than those with lower scores. According to a total risk score (TRS) based on hazard ratios for OS, OS of the low risk group (N=309, TRS<2) was significantly higher (24.3m vs. 10.8m, HR=2.05, 95% CI: 1.58-2.66). TRS was a predictor for OS independently from stage, primary site, prior chemotherapy, ECOG performance status, and IADL (HR=1.94, 95% CI: 1.47-2.57). CONCLUSIONS: High TRS was a predictor of poor survival. Comorbidity heat maps appear promising to identify diseases most affecting the OS of older cancer patients.
OBJECTIVE: To date, most comorbidity studies have analyzed either a subgroup of frequent diseases, or used summary instruments such as the Charlson score or the Cumulative Illness Rating Scale-Geriatric (CIRS-G). Yet, comorbidity is a multidimensional construct and impacts function, treatment tolerance, and survival. We assessed how heat maps can unveil specific patterns of comorbidities associated with overall survival (OS) in older cancerpatients treated with chemotherapy. MATERIAL AND METHODS: We reviewed four trials that prospectively evaluated comorbidities using CIRS-G. Eligible patients were 65years or older and had solid tumors with 30 or more patients per tumor site. Heat maps were constructed based on CIRS-G scores and correlated with OS. RESULTS: Among 818 patients accrued, 399 were eligible: Median follow-up was 53.4months and median OS was 19.6months (95% CI: 16.5-24.2). In the univariate model for OS, patients with a severe CIRS-G score in 6 organ categories (3-4 in heart, hematopoietic, respiratory, and musculoskeletal-integument and 2-4 in upper GI and liver) had statistically worse OS than those with lower scores. According to a total risk score (TRS) based on hazard ratios for OS, OS of the low risk group (N=309, TRS<2) was significantly higher (24.3m vs. 10.8m, HR=2.05, 95% CI: 1.58-2.66). TRS was a predictor for OS independently from stage, primary site, prior chemotherapy, ECOG performance status, and IADL (HR=1.94, 95% CI: 1.47-2.57). CONCLUSIONS: High TRS was a predictor of poor survival. Comorbidity heat maps appear promising to identify diseases most affecting the OS of older cancerpatients.
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