Health‐Related Quality of Life in a Predictive Model for Mortality in Older Breast Cancer Survivors

Objectives To develop a predictive model and risk score for 10‐year mortality using health‐related quality of life (HRQOL) in a cohort of older women with early‐stage breast cancer. Design Prospective cohort. Setting Community. Participants U.S. women aged 65 and older diagnosed with Stage I to IIIA primary breast cancer (N=660). Measurements We used medical variables (age, comorbidity), HRQOL measures (10‐item Physical Function Index and 5‐item Mental Health Index from the Medical Outcomes Study (MOS) 36‐item Short‐Form Survey; 8‐item Modified MOS Social Support Survey), and breast cancer variables (stage, surgery, chemotherapy, endocrine therapy) to develop a 10‐year mortality risk score using penalized logistic regression models. We assessed model discriminative performance using the area under the receiver operating characteristic curve (AUC), calibration performance using the Hosmer‐Lemeshow test, and overall model performance using Nagelkerke R2 (NR). Results Compared to a model including only age, comorbidity, and cancer stage and treatment variables, adding HRQOL variables improved discrimination (AUC 0.742 from 0.715) and overall performance (NR 0.221 from 0.190) with good calibration (p=0.96 from HL test). Conclusion In a cohort of older women with early‐stage breast cancer, HRQOL measures predict 10‐year mortality independently of traditional breast cancer prognostic variables. These findings suggest that interventions aimed at improving physical function, mental health, and social support might improve both HRQOL and survival.