The aim of the work reported in this thesis was to develop a scoring algorithm that converts ratings from a validated disease-specific quality of life questionnaire called the Utility-Based Questionnaire-Cancer (UBQ-C) into a utility index that is designed for evaluating clinical trials to inform clinical decisions about cancer treatments.
The UBQ-C includes a scale for global health status (1 item); and subscales for physical function (3 items), social/usual activities (4 items), self-care (1 item), and distresses due to physical and psychological symptoms (21 items). Data from three studies was used. A valuation survey consisted of patients with advanced cancer (n=204) who completed the UBQ-C and assigned time-trade-off utilities about their own health state. Clinical trials were of chemotherapy for advanced (n=325) and early (n=126) breast cancer. A scoring algorithm was derived to convert the subscales into a subset index, and combine it with the global scale into an overall quality of life index, which was converted to a utility index with a power transformation. Optimal weights were assigned to the subscales that reflected their correlations with a global scale in each study. The derived utilities were validated by comparison with other patient characteristics. Each trial was evaluated in terms of differences in utility between treatment groups.
In the valuation survey, the weights (range 0 to 1) for the subset index were: physical function 0.28, social/usual activities 0.06, self-care 0.01, and distresses 0.64. Weights for the overall quality of life index were health status 0.65 and subset index 0.35. The mean of the utility index scores was similar to the mean of the time trade-off utilities (0.92 vs. 0.91, p=0.6). The weights were adjusted in each clinical trial. The utility index was substantially correlated with other measures of quality of life, discriminated between breast cancer that was advanced rather than early (means 0.88 vs 0.94, p<0.0001), and was responsive to toxic effects of chemotherapy in early breast cancer (mean change 0.07, p<0.0001). There were trends to better mean scores on the utility index for patients allocated to standard-dose versus high-dose chemotherapy in the early cancer trial (p=0.1), and oral versus intravenous chemotherapy in the advanced cancer trial (p=0.2).
In conclusion, data from a simple, self-rated, disease-specific questionnaire can be converted into a utility index based on cancer patients’ preferences. The index can be optimised in different clinical contexts to reflect the relative importance of different aspects of quality of life to the patients in a trial. The index can be used to generate utility scores and quality-adjusted life-years in clinical trials. It enables the evaluation of the net effect of treatments on health-related quality of life (accounting for trade-offs between disparate aspects); the evaluation of the net benefit of treatments (accounting for trade-offs between quality of life and survival); and an alternate perspective for comparing the incremental cost-effectiveness of treatments (accounting for trade-offs between net benefit and costs).
The practical significance of this work is to facilitate the integration of data about health-related quality of life with traditional trial endpoints such as survival and tumour response. This will better inform clinical decision-making, and provide an alternate viewpoint for economic decision-making. Broadly, it will help patients, clinicians and health funders make better decisions about cancer treatments, by considering potential trade-offs between effects on survival and health-related quality of life.