Oral Presentation Clinical Oncology Society of Australia Annual Scientific Meeting 2022

How would the choice of health-related quality of life measure affect the cost-effectiveness of oncology interventions? (#48)

Haitham Tuffaha 1 , Shiksha Arora 1 , Linda Denehy 2 , Lara Edbrooke 3
  1. Centre for the Business and Economics of Health, The University of Queensland, Brisbane, QLD, Australia
  2. Melbourne School of Health Sciences, The University of Melbourne, Melbourne, Victoria, Australia
  3. School of Physiotherapy, University of Melbourne, Melbourne, Victoria, Australia

OBJECTIVES

To compare the performance of the Functional Assessment of Cancer Therapy-Eight Dimension (FACT-8D), a cancer-specific multi-attribute utility instrument derived from the FACT-General (FACT-G) questionnaire, with the generic Assessment of Quality of Life (AQoL) instrument.

METHODS

Health-related quality of life (HRQoL) data were drawn from a randomised controlled trial of a home-based rehabilitation program compared to usual care in lung cancer (ANZCTRN 12614001268639). Both the AQoL and the FACT-Lung (FACT-L) were administered at baseline, 9 weeks and 6 months of the trial. The FACT-8D utility values were derived using the algorithm developed by King et al (2021). The utility values from the two instruments were compared and assessed for correlation and agreement at baseline, and the quality-adjusted life-years (QALYs) gained over time was calculated. A cost-utility analysis from an Australian health system perspective was conducted.

RESULTS

At baseline, mean utility values derived from the FACT-8D (0.68, 95% CI: 0.63-0.73) were higher and statistically different compared to the values from the AQoL (0.66, 95% CI: 0.61-0.71). The correlation between the two instruments was moderate (Pearson’s correlation = 0.69); but the agreement was low (Lin’s concordance correlation coefficient = 0.69). The intervention was found to be less effective but cost saving compared with usual care. There was a slight difference in the QALYs gained when using the FACT-8D over the AQoL (-0.009 vs -0.011), and a higher incremental net monetary benefit ($1,476 vs $1,388).

CONCLUSIONS

This is the first study to compare the FACT-8D and the AQoL. There was divergence in the utility values and QALYs estimated using the two instruments; however, the intervention was cost-effective irrespective of the instrument used. Deriving the FACT-8D from the FACT-G or related FACIT questionnaire may offer an alternative and efficient method to measure HRQL in cancer  trials; however, further testing of the instrument is required.