Abstract

Objective: Bayesian inference allows the revision of prior clinical estimates of treatment effectiveness based on current data. We apply it to a published dataset evaluating the effect of cerclage upon preterm delivery in twin gestations with a short cervix.Study design: Prior probability distributions for delivery <35 weeks gestation for the control group and the treatment (cerclage) group were constructed under assumptions ranging from treatment having no effect (prior A) to halving early deliveries (prior C). Likelihood functions were calculated based on a published meta-analysis. Posterior probability densities were derived from which risk ratios for early delivery were computed, with 95% credible intervals and the probability of cerclage benefit.Results: Median posterior risk ratios (95% credible intervals) for delivery <35 weeks with cerclage are 1.51 (1.02–2.33) for prior A and 1.11 (0.72–1.77) for prior C. The probability of cerclage benefit ranged from 2.1% for prior A to 31.4% for prior C. By comparison, the conventional risk ratio (95% confidence interval) for early delivery, based on the data alone, is 2.08 (1.18–3.69).Conclusions: As might be anticipated, those with low expectation of cerclage benefit remain more convinced of the ineffectiveness (or harm) of the procedure than those with higher expectations.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call