Jeanne S Mandelblatt1, Ling Cai2, George Luta2, Gretchen Kimmick3, Jonathan Clapp2, Claudine Isaacs4, Brandeyln Pitcher5, William Barry6,7, Eric Winer8, Stephen Sugarman9, Clifford Hudis9, Hyman Muss10, Harvey J Cohen11, Arti Hurria12. 1. Cancer Prevention and Control Program, Department of Oncology, MedStar Georgetown University School of Medicine, Lombardi Comprehensive Cancer Center, 3300 Whitehaven Street, NW - Suite 4100, Washington, DC, 20007, USA. mandelbj@georgetown.edu. 2. Department of Biostatistics, Bioinformatics and Biomathematics, MedStar Georgetown University Medical Center, Georgetown University, Washington, DC, USA. 3. Division of Oncology, Department of Medicine, Duke Cancer Institute, Duke University Medical Center, Durham, NC, USA. 4. Breast Cancer Program, Departments of Medicine and Oncology, Georgetown University School of Medicine, Lombardi Comprehensive Cancer Center, Washington, DC, USA. 5. Alliance Statistics and Data Center, Duke University, Durham, NC, USA. 6. Department of Biostatistics, Dana Farber Cancer Institute, Boston, MA, USA. 7. Alliance Statistics and Data Center, Dana Farber Cancer Institute, Boston, MA, USA. 8. Department of Medicine, Dana-Farber/Partners CancerCare, Boston, MA, USA. 9. Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA. 10. UNC Lineberger Comprehensive Cancer Center and Department of Medicine, University of North Carolina, Chapel Hill, NC, USA. 11. Department of Medicine and Center for the Study of Aging and Human Development, Duke University Medical Center, Durham, NC, USA. 12. Department of Medical Oncology and Therapeutics Research, City of Hope Comprehensive Cancer Center, Duarte, CA, USA.
Abstract
PURPOSE: Breast cancer patients aged 65+ ("older") vary in frailty status. We tested whether a deficits accumulation frailty index predicted long-term mortality. METHODS: Older patients (n = 1280) with non-metastatic, invasive breast cancer were recruited from 78 Alliance sites from 2004 to 2011, with follow-up to 2015. Frailty categories (robust, pre-frail, and frail) were based on 35 baseline illness and function items. Cox proportional hazards and competing risk models were used to calculate all-cause and breast cancer-specific mortality for up to 7 years, respectively. Potential covariates included demographic, psychosocial, and clinical factors, diagnosis year, and care setting. RESULTS: Patients were 65-91 years old. Most (76.6%) were robust; 18.3% were pre-frail, and 5.1% frail. Robust patients tended to receive more chemotherapy ± hormonal therapy (vs. hormonal) than pre-frail or frail patients (45% vs. 37 and 36%, p = 0.06), and had the highest adherence to hormonal therapy. The adjusted hazard ratios for all-cause mortality (n = 209 deaths) were 1.7 (95% CI 1.2-2.4) and 2.4 (95% CI 1.5-4.0) for pre-frail and frail versus robust women, respectively, with an absolute mortality difference of 23.5%. The adjusted hazard of breast cancer death (n-99) was 3.1 (95% CI 1.6-5.8) times higher for frail versus robust patients (absolute difference of 14%). Treatment differences did not account for the relationships between frailty and mortality. CONCLUSIONS: Most older breast cancer patients are robust and could consider chemotherapy where otherwise indicated. Patients who are frail or pre-frail have elevated long-term all-cause and breast cancer mortality. Frailty indices could be useful for treatment decision-making and care planning with older patients.
PURPOSE: Breast cancer patients aged 65+ ("older") vary in frailty status. We tested whether a deficits accumulation frailty index predicted long-term mortality. METHODS: Older patients (n = 1280) with non-metastatic, invasive breast cancer were recruited from 78 Alliance sites from 2004 to 2011, with follow-up to 2015. Frailty categories (robust, pre-frail, and frail) were based on 35 baseline illness and function items. Cox proportional hazards and competing risk models were used to calculate all-cause and breast cancer-specific mortality for up to 7 years, respectively. Potential covariates included demographic, psychosocial, and clinical factors, diagnosis year, and care setting. RESULTS: Patients were 65-91 years old. Most (76.6%) were robust; 18.3% were pre-frail, and 5.1% frail. Robust patients tended to receive more chemotherapy ± hormonal therapy (vs. hormonal) than pre-frail or frail patients (45% vs. 37 and 36%, p = 0.06), and had the highest adherence to hormonal therapy. The adjusted hazard ratios for all-cause mortality (n = 209 deaths) were 1.7 (95% CI 1.2-2.4) and 2.4 (95% CI 1.5-4.0) for pre-frail and frail versus robust women, respectively, with an absolute mortality difference of 23.5%. The adjusted hazard of breast cancer death (n-99) was 3.1 (95% CI 1.6-5.8) times higher for frail versus robust patients (absolute difference of 14%). Treatment differences did not account for the relationships between frailty and mortality. CONCLUSIONS: Most older breast cancer patients are robust and could consider chemotherapy where otherwise indicated. Patients who are frail or pre-frail have elevated long-term all-cause and breast cancer mortality. Frailty indices could be useful for treatment decision-making and care planning with older patients.
Entities:
Keywords:
Breast cancer; Frailty; Mortality; Older; Survival
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