Comorbidity patterns and health-related quality of life in a cohort of Australian women cancer survivors

Abstract

Purpose: This study aimed to identify dominant comorbidity patterns among women cancer survivors and examine how these patterns relate to health-related quality of life (HRQL). Methods: 1544 participants (born 1946–1951) from the Australian Longitudinal Study on Women’s Health diagnosed with cancer during the follow-up period from 1993 to 2019 were included. HRQL is measured with Short Form-36 included in the survey. Latent class analysis was applied to identify comorbidity patterns, and linear regression was used to assess their association with HRQL domains, adjusting for demographic factors. Results: Five distinct comorbidity classes were identified: relatively healthy (n = 880, 57%); hypertension and arthritis (n = 278, 18%); arthritis and osteoporosis (n = 139, 9%); respiratory conditions (n = 170, 11%); and complex multimorbidity (n = 93, 6%). Compared to the relatively healthy class, women in all other classes had significantly lower average HRQL (p < 0.01). For example, the classes’ adjusted mean score for general health domain varied: relatively healthy (mean = 70.8, reference), hypertension and arthritis (mean = 63.1, 95% CI = 59.9, 66.3), arthritis and osteoporosis (mean = 60.0, 95% CI = 55.8, 64.1), respiratory conditions (mean = 60.9, 95% CI = 57.2, 64.7), and complex multimorbidity (mean = 48.6, 95% CI = 43.4, 53.8). Women in the complex multimorbidity class had the lowest HRQL across all domains: physical functioning [adjusted mean difference from relatively healthy (AMD=− 22.2 and 95% CI − 27.4, − 17.0)], mental health (AMD=-11.4, 95% CI=− 15.4, -7.5). Conclusion: Comorbidity patterns varied substantially among women cancer survivors and were strongly associated with differences in HRQL. Survivors with complex multimorbidity experienced the greatest impairments. Incorporating comorbidity profiling into survivorship care may help identify high-risk groups and support targeted interventions to optimise quality of life.