Inclusion of health-related quality-of-life data in oncology drug reimbursement submissions in Canada: A review of submissions to the pan-Canadian Oncology Drug Review.

94 Background: For health technologies, and cancer treatments specifically, economic evaluation is often used to assess the value of new treatments. The preferred approach to economic evaluation is often cost-utility analysis (CUA). In CUA, incremental costs and benefits of a new treatment and a standard of care are calculated with benefits quantified using the quality-adjusted life-year (QALY); the QALY attempts to account for the quantity and quality of life (using a utility weight). The utility weight often comes from a generic, preference-based measure of health-related quality of life (HRQoL), such as the 5-dimension EuroQol measure (EQ-5D). Many submissions for reimbursement by manufacturers, and indeed many clinical trials, still do not include HRQoL data which may result in lower quality submissions and thus, sub-optimal decisions. Methods: We reviewed submissions to the pan-Canadian Oncology Drug Review (pCODR), the body charged with making reimbursement recommendations in Canada. We reviewed submissions from those first recorded (August 2012) to the present (June 2018). Only submissions that were completed (status listed as 'Notification to Implement Issued') were included. Upon completion, three documents are produced by pCODR: the final recommendation from the pCODR Expert Review Committee, the final clinical guidance report, and the final economic guidance report. All three documents were searched for how HRQoL was incorporated into the economic evaluation. Results: In total, 135 submissions were made to pCODR over the period. Of these, 107 (79.3%) had been completed and met the criteria for inclusion. In most studies, the incremental gain in QALYs from the new technology was small (in 2017 submissions the mean QALY gain was 1.1 QALYs). In addition, few studies reported an original measure of HRQoL, with most citing previously completed studies of variable relevance and quality. Conclusions: Our results indicate that manufacturers should improve the collection of HRQoL data of patients alongside clinical trials. This would enhance the focus on patients and improve decision-making around reimbursement of treatments.

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