Hypothesis testing by simulation of a medical study model using the expected net benefits criteria

Abstract

This work investigates whether to conduct a medical study from the point of view of the expected net benefit taking into account statistical power, time and cost. The hypothesis of this paper is that the expected net benefit is equal to zero. Methods: Information were obtain- ed from a pilot medical study that investigates the effects of two diagnostic modalities, magne- tic resonance imaging (MRI) and computerized axial tomography scanner (CT), on patients with acute stroke. Statistical procedure was applied for planning and contrasting equivalence, non- inferiority and inequality hypotheses of the stu- dy for the effectiveness, health benefits and costs. A statistical simulation model was applied to test the hypothesis that conducting the study would or not result in overall net benefits. If the null hypothesis not rejected, no benefits would occurred and therefore the two arms-patterns of diagnostic and treatment are of equal net bene- fits. If the null hypothesis is rejected, net bene- fits would occur if patients are diagnosed with the more favourable diagnostic modality. Re- sults: For any hypothesis design, the expected net benefits are in the range of 366 to 1796 per patient at 80% of statistical power if conducting the study. The power depends on the monetary value available for a unit of health improvement. Conclusion: The statistical simulations suggest that diagnosing patients with CT will provide more favourable health outcomes showing sta- tistically significant expected net benefits in comparison with MRI.

Peer Reviewed

Postprint (published version)