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A Non-inferiority Framework for Cost-Effectiveness Analysis
Published online by Cambridge University Press: 24 July 2019
Abstract
Traditional decision rules have limitations when a new technology is less effective and less costly than a comparator. We propose a new probabilistic decision framework to examine non-inferiority in effectiveness and net monetary benefit (NMB) simultaneously. We illustrate this framework using the example of repetitive transcranial magnetic stimulation (rTMS) and electroconvulsive therapy (ECT) for treatment-resistant depression.
We modeled the quality-adjusted life-years (QALYs) associated with the new intervention (rTMS), an active control (ECT), and a placebo control, and we estimated the fraction of effectiveness preserved by the new intervention through probabilistic sensitivity analysis (PSA). We then assessed the probability of cost-effectiveness using a traditional cost-effectiveness acceptability curve (CEAC) and our new decision-making framework. In our new framework, we considered the new intervention cost-effective in each simulation of the PSA if it preserved at least 75 percent of the effectiveness of the active control (thus demonstrating non-inferiority) and had a positive NMB at a given willingness-to-pay threshold (WTP).
rTMS was less effective (i.e., associated with fewer QALYs) and less costly than ECT. The traditional CEAC approach showed that the probabilities of rTMS being cost-effective were 100 percent, 39 percent, and 14 percent at WTPs of $0, $50,000, and $100,000 per QALY gained, respectively. In the new decision framework, the probabilities of rTMS being cost-effective were reduced to 23 percent, 21 percent, and 13 percent at WTPs of $0, $50,000, and $100,000 per QALY, respectively.
This new framework provides a different perspective for decision making with considerations of both non-inferiority and WTP thresholds.
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- Information
- International Journal of Technology Assessment in Health Care , Volume 35 , Issue 4 , 2019 , pp. 291 - 297
- Copyright
- Copyright © Cambridge University Press 2019
Footnotes
The opinions expressed in this publication do not necessarily represent the opinions of Health Quality Ontario. No endorsement is intended or should be inferred. We thank Kara Cowan from Health Quality Ontario for her help editing the manuscript and two anonymous reviewers for their valuable comments on the manuscript. Financial support: This research received no specific grant from any funding agency, commercial or not-for-profit sectors.
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