The journals of gerontology. Series A, Biological sciences and medical sciences · 2015
Predictors of 1-Year Mortality in a Prospective Cohort of Elderly Patients With Cancer.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Ferrat Emilie, Paillaud Elena, Laurent Marie, Le Thuaut Aurélie, Caillet Philippe, Tournigand Christophe, Lagrange Jean-Léon, Canouï-Poitrine Florence, Bastuji-Garin Sylvie, ELPACA Study Group
Аннотация
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.
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.