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

Abstract

Introduction: 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. T he hypothesis of this paper is that the expected net benefit is equal to zero . M ethods : Information were obtained from a pilot medical study that investigates the effects of two diagnostic modalities, magnetic 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 stud y for the effectiveness, health benefits and costs. A statistical simulation model was applied to test the hypothes i s 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 benefits. If the null hypothesis is rejected, net benefits would occur if patients are diagnosed with the more favourable diagnostic modality. R esults : 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 statistically significant expected net benefits in comparison with MRI.