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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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