In Reply:

In Reply: We thank Dr. Zekri for the Letter regarding our cost-effectiveness analysis published in the April 2024 issue and appreciate the attention to detail.1 The author points out that, in the recent CHAP (Chronic Hypertension and Pregnancy) trial, there was not a statistically significant difference in the rate of preeclampsia with severe features, yet we included a difference in our model.2 In decision-analytic analyses, one must use the best possible estimates from the literature to inform the model inputs. Preferably, model inputs are derived from large randomized controlled trials (RCTs) or systematic reviews of multiple RCTs.3 However, many clinical scenarios do not have such large RCTs, such as the management of placenta accreta spectrum, vasa previa, or prior uterine rupture,4 for example. Yet, there is still a need for a systematic, transparent way to evaluate possible management scenarios. Even in a large RCT, there may be limited power to demonstrate some outcomes. In the CHAP trial, although the development of preeclampsia overall was statistically different, preeclampsia with or without severe features was not, though the rates for both were lower in the group treated at a blood pressure of 140/90. In lieu of using point estimates from other cohort studies, we chose to use the point estimates from the CHAP trial, because we were already using data for overall risk of preeclampsia from the CHAP trial. Importantly, as with any decision-analytic model, we conducted sensitivity analyses including a Monte Carlo simulation.5 Such an analysis samples the distribution around each point estimate, then runs the model thousands of times to obtain a distribution of potential answers. When we did this, the model was cost effective in more than 95% of simulations. This reassured us that our findings were robust despite the potential variability of our point estimates. Just like Dr. Zekri, we encourage readers to examine all decision-analytic and cost-effectiveness analyses carefully and to ascertain whether these studies have used such multivariable analyses to examine the uncertainty in the models.