Poster Presentation 2025 National Cancer Survivorship Conference

Are rural cancer survivors receiving optimal care? A comparison of time from diagnosis to treatment with the Optimal Care Pathways (#115)

Susannah Ayre 1 2 , Michael Ireland 3 , Alyssa Taglieri-Sclocchi 1 , Xanthia E Bourdaniotis 1 4 , Sonja March 3 , Fiona Crawford-Williams 5 , Jeff Dunn 1 3 6 7 8 9 , Suzanne Chambers 6 7 10 , Belinda C Goodwin 1 3 11 , Lizzy A Johnston 1 2 12
  1. Cancer Council Queensland, Brisbane, QLD, Australia
  2. School of Exercise and Nutrition Sciences, Queensland University of Technology, Brisbane, QLD, Australia
  3. Centre for Health Research, University of Southern Queensland, Springfield, QLD, Australia
  4. School of Psychology, The University of Queensland, Brisbane, QLD, Australia
  5. Caring Futures Institute, Flinders Institute, Adelaide, SA, Australia
  6. Faculty of Health Sciences, Australian Catholic University, Brisbane, QLD, Australia
  7. Menzies Health Institute Queensland, Griffith University, Brisbane, QLD, Australia
  8. Prostate Cancer Foundation of Australia, Sydney, NSW, Australia
  9. Exercise Medicine Research Institute, Edith Cowan University, Joondalup, WA, Australia
  10. St Vincent's Health Network Sydney, Sydney, NSW, Australia
  11. School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia
  12. Population Health Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia

Objective: To determine the prevalence and characteristics of rural cancer survivors who experienced a delay between receiving their cancer diagnosis and commencing primary treatment using the recommendations in the Optimal Care Pathways (OCPs).

Methods: This analysis used baseline data from a longitudinal study of adults in Queensland, Australia, who travelled from rural areas to receive cancer care in a major city centre (n=640). In an interview at study recruitment, data were collected on dates of diagnosis and primary treatment. To determine whether participants experienced a treatment delay, the number of weeks between diagnosis and primary treatment were compared to OCP recommendations for the relevant cancer type. A multiple logistic regression model was developed to determine the sociodemographic, health, and clinical factors associated with experiencing a treatment delay.

Results: The median number of weeks between diagnosis and primary treatment was 4.4 (IQR: 2.0-8.9 weeks). Of the 494 participants whose data could be assessed against the OCPs, 199 (40%) were identified as having experienced a delay between diagnosis and primary treatment. No associations were found between treatment delay and age, gender, geographic remoteness, number of comorbidities, and primary treatment modality. After accounting for these factors, participants without access to private health insurance were more likely to experience a treatment delay compared to those with access (adjusted OR: 1.68, 95% CI: 1.02-2.78), and participants with breast (adjusted OR: 0.32, 95% CI: 0.14-0.74) and skin cancer (adjusted OR: 0.23, 95% CI: 0.09-0.61) were less likely to experience a treatment delay compared to people with other cancer types.

Conclusions: A significant proportion of rural cancer survivors did not receive treatment within recommended timeframes from diagnosis. Along with inequities related to health insurance status and cancer type, this study identifies key areas for health system planning to reduce treatment delays for people living in rural areas.