Poster Presentation 2025 National Cancer Survivorship Conference

Comorbidity Patterns and Health-Related Quality of Life in a Cohort of Australian Women Cancer Survivors: A Latent Class Analysis (#168)

Haoyu Zhang 1 , Xue Qin Yu 2 , Michael David 2 , Mei Ling Yap 3 , Julie Byles 4 , MD Mijanur Rahman 3
  1. School of Public Health, The University of Sydney, Sydney, NSW, Australia
  2. Faculty of Medicine and Health, The Daffodil Centre, the University of Sydney, A Joint Venture with Cancer Council, Sydney, NSW, Australia
  3. Collaboration for Cancer Outcomes, Research and Evaluation (CCORE), Ingham Institute for Applied Medical Research, West Sydney Clinical Campus, UNSW, Liverpool, NSW, Australia
  4. School of Public Health, Centre for Women’s Health Research, University of Newcastle, Newcastle, NSW, Australia

Background: Comorbid conditions are common among people with cancer. However, the comorbidity patterns and their associations with health-related quality of life (HRQL) remain unclear. This study aims to identify latent comorbidity patterns among women cancer survivors and examine how these patterns are associated with HRQL outcomes.


Methods: Data were taken from a large cohort (born: 1946-51) of the Australian Longitudinal Study on Women’s Health (ALSWH) and linked Australian Cancer Database. In total, 1,544 women diagnosed with cancer between 1993 and 2019 who completed at least one ALSWH survey within three years following their diagnosis were included. Latent class analysis was applied to identify comorbidity patterns based on nine major chronic conditions. HRQL was assessed using the SF-36 questionnaire. Multivariable linear regression models were used to examine associations between the comorbidity pattern and HRQL domains.

Results: Five distinct comorbidity patterns were identified, including a relatively healthy class (n = 880, 57%), likely hypertension and arthritis class (n = 278, 18%), likely arthritis and osteoporosis (n = 139, 9%), likely respiratory conditions (n = 170, 11%), and a higher comorbidities class (n = 93, 6%). Compared to those in the relatively health class, women in higher comorbidities group reported the poorest HRQL across all domains, including physical functioning (adjusted mean difference (AMD) = -22.2 & 95% confidence interval (CI): -27.4, -17.0), general health (AMD = -22.2, CI = -27.4, -17.0), mental health (AMD = -11.4, CI = -15.4, -7.5), bodily pain (AMD = -22.2, CI = -27.8, -16.6), and vitality (AMD = -16.9, CI = -22.0, -11.9). Women in all other classes also reported significantly lower HRQL than those in the relatively healthy class.


Conclusion: Our findings highlight that comprehensive survivorship care strategies, considering the unique challenges experienced by women with different comorbidity patterns, are needed to enhance their HRQL.