A Bayesian approach to net health benefits: an illustration and application to modeling HIV prevention.
OBJECTIVE
To conduct a cost-effectiveness analysis of HIV prevention when costs and effects cannot be measured directly. To quantify the total estimation of uncertainty due to sampling variability as well as inexact knowledge of HIV transmission parameters.


METHODS
The authors focus on estimating the incremental net health benefit (INHB) in a randomized trial of HIV prevention with intervention and control conditions. Using a Bernoulli model of HIV transmission, changes in the participants' risk behaviors are converted into the number of HIV infections averted. A sampling model is used to account for variation in the behavior measurements. Bayes's theorem and Monte Carlo methods are used to attain the stated objectives.


RESULTS
The authors obtained a positive mean INHB of 0.0008, indicating that advocacy training is just slightly favored over the control condition for men, assuming a $50,000 per quality-adjusted life year (QALY) threshold. To be confident of a positive INHB, the decision maker would need to spend more than $100,000 per QALY.
Johnson-Masotti
Ana P
AP
Clinical Epidemiology and Biostatistics Department, McMaster University, Hamilton, Ontario, Canada. johnmas@mcmaster.ca
Laud
Purushottam W
PW
Hoffmann
Raymond G
RG
Hayat
Matthew J
MJ
Pinkerton
Steven D
SD
D001499:Bayes Theorem; D003362:Cost-Benefit Analysis; D003661:Decision Support Techniques; D005260:Female; D015658:HIV Infections / Q000191:economics* / Q000517:prevention & control* / Q000635:transmission; D006801:Humans; D008297:Male; D009010:Monte Carlo Method; D010353:Patient Education as Topic; D019057:Quality-Adjusted Life Years; D016032:Randomized Controlled Trials as Topic; D012309:Risk-Taking; D035501:Uncertainty