Developing and validating a multi-criteria decision analytic tool to assess the value of cancer clinical trials
Gillett, P.; Mahar, R. K.; Tran, N. R.; Rosenthal, M.; IJzerman, M.
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BackgroundDemonstrating safety and efficacy of new medical treatments requires clinical trials. But clinical trials are costly and may not provide value proportionate to their costs. In health systems with limited resources, it is important to identify the trials with the highest value. Tools exist to assess elements of a clinical trial such as statistical validity but are not wholistic in their valuation of a clinical trial. This study aims to develop a measure of clinical trials value and provide an online tool for clinical trial prioritisation. MethodsA search of the academic and grey literature and expert consultation was undertaken to identify a set of metrics to aid clinical trial valuation using multi-criteria decision analysis. Swing weighting and ranking exercises were used to calculate appropriate weights of each of the included metrics and to estimate the partial-value function for each underlying metric. The set of metrics and their respective weights were applied to the results of six different clinical trials to calculate their value. ResultsSeven metrics were identified: unmet need, size of target population, eligible participants can access the trial, patient outcomes, total trial cost, academic impact and use of trial results. The survey had 80 complete sets of responses (51% response rate). A trial designed to address an Unmet Need was most commonly ranked as the most important with a weight of 24.4%, followed by trials demonstrating improved Patient Outcomes with a weight of 21.2%. The value calculated for each trial allowed for their clear delineation and thus a final value ranking for each of the six trials. ConclusionWe confirmed that the use of the decision tool for valuing clinical trials is feasible and that the results are face valid based on the evaluation of six trials. A proof-of-concept applying this tool to a larger set of trials with an external validation is currently underway.
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