Emilie Ferrat1, Elena Paillaud2, Marie Laurent2, Aurélie Le Thuaut3, Philippe Caillet2, Christophe Tournigand4, Jean-Léon Lagrange5, Florence Canouï-Poitrine6, Sylvie Bastuji-Garin3. 1. Université Paris Est, A-TVB DHU, CEpiA (Clinical Epidemiology and Ageing) Unit EA 4393, UPEC, F-94010, Créteil, France. Primary Care Department, School of Medicine, Paris East Créteil University (UPEC), France. emilie.ferrat@u-pec.fr. 2. Université Paris Est, A-TVB DHU, CEpiA (Clinical Epidemiology and Ageing) Unit EA 4393, UPEC, F-94010, Créteil, France. Geriatric Oncology Coordination Unit (UCOG). 3. Université Paris Est, A-TVB DHU, CEpiA (Clinical Epidemiology and Ageing) Unit EA 4393, UPEC, F-94010, Créteil, France. Public Health Department, Clinical Research Unit (URC Mondor). 4. Medical Oncology Department, and. 5. Radiotherapy Department, Henri-Mondor Teaching Hospital, APHP, Créteil, France. 6. Université Paris Est, A-TVB DHU, CEpiA (Clinical Epidemiology and Ageing) Unit EA 4393, UPEC, F-94010, Créteil, France. Public Health Department.
Abstract
BACKGROUND: Mortality prediction is crucial to select the optimal treatment in elderly cancer patients. Our objective was to identify cancer-related factors and Comprehensive Geriatric Assessment (CGA) findings associated with 1-year mortality in elderly inpatients and outpatients with cancer. METHODS: We prospectively included patients aged ≥70 years who had solid or hematologic malignancies and in whom the CGA was performed by geriatricians in two French teaching hospitals. We identified independent predictors of 1-year mortality after study inclusion, using multivariate Cox models stratified on inpatient/outpatient status. We built three multivariate Cox models, since strong correlations linked activities of daily living (ADL), Eastern Cooperative Oncology Group Performance Status (ECOG-PS), and timed get-up-and-go test (GUG) results; and since physicians' preferences for these three assessments vary. A sensitivity analysis was performed using multiple imputation. RESULTS: Of the 993 patients (mean age, 80.2 years; 51.2% men), 58.2% were outpatients and 46% had metastatic disease. Colorectal cancer was the most common malignancy (21.4%). Mortality rates after 6 and 12 months were 30.1% and 41.2%, respectively. In all models, tumor site and metastatic status (p < .001), age >80 years (p < .05), higher number of severe comorbidities (p < .05), and malnutrition (p < .001) were associated with death independently from impaired ECOG-PS (p < .001), ADL (p < .001), and GUG (p < .001). The adverse effect of metastatic status differed significantly across tumor sites, being greatest for breast and prostate cancer (p < .001). Multiple imputation produced similar results. CONCLUSION: The predictors of 1-year mortality identified in our study may help physicians select the optimal cancer-treatment strategy in elderly patients.
BACKGROUND: Mortality prediction is crucial to select the optimal treatment in elderly cancerpatients. Our objective was to identify cancer-related factors and Comprehensive Geriatric Assessment (CGA) findings associated with 1-year mortality in elderly inpatients and outpatients with cancer. METHODS: We prospectively included patients aged ≥70 years who had solid or hematologic malignancies and in whom the CGA was performed by geriatricians in two French teaching hospitals. We identified independent predictors of 1-year mortality after study inclusion, using multivariate Cox models stratified on inpatient/outpatient status. We built three multivariate Cox models, since strong correlations linked activities of daily living (ADL), Eastern Cooperative Oncology Group Performance Status (ECOG-PS), and timed get-up-and-go test (GUG) results; and since physicians' preferences for these three assessments vary. A sensitivity analysis was performed using multiple imputation. RESULTS: Of the 993 patients (mean age, 80.2 years; 51.2% men), 58.2% were outpatients and 46% had metastatic disease. Colorectal cancer was the most common malignancy (21.4%). Mortality rates after 6 and 12 months were 30.1% and 41.2%, respectively. In all models, tumor site and metastatic status (p < .001), age >80 years (p < .05), higher number of severe comorbidities (p < .05), and malnutrition (p < .001) were associated with death independently from impaired ECOG-PS (p < .001), ADL (p < .001), and GUG (p < .001). The adverse effect of metastatic status differed significantly across tumor sites, being greatest for breast and prostate cancer (p < .001). Multiple imputation produced similar results. CONCLUSION: The predictors of 1-year mortality identified in our study may help physicians select the optimal cancer-treatment strategy in elderly patients.
Authors: K Boehm; M Duckheim; L Mizera; P Groga-Bada; N Malek; F Kreth; M Gawaz; C S Zuern; C Eick Journal: Support Care Cancer Date: 2018-04-12 Impact factor: 3.603
Authors: F Pamoukdjian; V Lévy; G Sebbane; M Boubaya; T Landre; C Bloch-Queyrat; E Paillaud; L Zelek Journal: J Nutr Health Aging Date: 2017 Impact factor: 4.075
Authors: Jason W Boland; Victoria Allgar; Elaine G Boland; Mike I Bennett; Stein Kaasa; Marianne Jensen Hjermstad; Miriam Johnson Journal: Eur J Clin Pharmacol Date: 2019-12-21 Impact factor: 2.953