TITLE:
Hypothesis testing by simulation of a medical study model using the expected net benefits criteria
AUTHORS:
Ismail Abbas, Joan Rovira, Josep Casanovas
KEYWORDS:
Statistics; Simulation; Hypothesis Testing; Expected Net Benefits
JOURNAL NAME:
Health,
Vol.5 No.3,
March
7,
2013
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. The hypothesis of this paper is that the expected net benefit is equal
to zero. Methods: 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 study 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 benefits. If the null hypothesis is
rejected, net benefits would occur if patients are diagnosed with the more
favourable diagnostic modality. Results: 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.