Meta-Analysis of Aspirin for the Prevention of Preeclampsia: Do the Main Randomized Controlled Trials Support an Association Between Low-Dose Aspirin and a Reduced Risk of Developing Preeclampsia?

Abstract

The meta-analysis by Ruano et al 1 evaluating 17 randomized controlled trials considering the pooled relative risk (RR) of 16,898 women at high-risk of preeclampsia receiving acetylsalicylic acid (8679 treatment and 8219 placebo) suggested that low-dose aspirin (50-150 mg/day) has a small but significant protective effect on the risk of preeclampsia: Pooled RR = 0.87; 95% confidence intervals (CI) = 0.79 to 0.96, P = 0.004). This conclusion relies uniquely on the estimate from the fixed-effects model using the Mantel-Haenszel method (MH).2 However, we would like to raise some issues that allow different interpretations from the same meta-analysis.First, results of a meta-analysis are model-dependent. 3There are potential differences between models in metaanalysis, since they have distinct properties and assumptions, 2,4 and can model for different effects. 3 Second, because the choice between fixed-and random-effect models remains a controversial issue, 5 results from both models should be considered when drawing conclusions from a meta-analysis, 6 especially in cases where heterogeneity among treatment effects is observed.7 Third, when evidence for publication bias is not properly considered, results from meta-analytic studies can be seriously overestimated, yielding misleading conclusions. 8 In this regard, we extended further the analysis by Ruano et al 1 and provide an alternative interpretation from the same data set, illustrating practical consequences of fitting different types of statistical modeling in meta-analysis. Furthermore, we illustrate that changes in model selection substantially affect the outcome of a meta-analysis, particularly when the null hypothesis of homogeneity among treatment effects is rejected.It is well established that in the fixed-effects model, the true treatment difference is often considered to be the same for all trials.2 In other words, fixed-effects models assume homogeneity among study estimates, whereas the variance of each trial estimate is based uniquely on sampling variation within the trial (within-study variance). In the randomeffects model, however, the true treatment difference in each trial is itself assumed to be a random variable with a normal distribution. 4 In addition, a second component of the total variance, the variance between-study, is estimated. Thus, in the random-effects model both within-study and between-study variances are taken into account in the assessment of the uncertainty (confidence intervals). While estimates based on fixed-effect models are specific to the particular trials included in the meta-analysis, results of the random-effects models are more amenable to generalization in terms of population. 6 When there is no heterogeneity between trials, both models tend to provide the same overall estimate and standard error.5 However, this is not true when heterogeneity is present.5 As the heterogeneity increases, the standard error of the common estimate from the random effects model becomes wider than that from the fixed-effects model. 4 Thus...

Is There Any Scientific Evidence for the Prevention of Preeclampsia With Low-Dose Aspirin? Meta-Analysis Versus Randomized Controlled Trial to Answer This Question.

“…From this point of view, we welcome the re-analysis of our data 4 , which reinforces what we had already shown 1 . Firstly, because Pereira et al 4 "found no convincing evidence for a protective effect of low-dose aspirin under this model (DL Common RR = 0.835; 95% CI = 0.697 to 1.001, P = 0.051)"; this they characterized as "surprising," since they probably lack adequate clinical experience on the issue, having only conducted a computer analysis of results from other researchers. Secondly, to re-analyze our data, they did not have to go back to each individual study which shows our report contained sufficient information.…”

“…Our second hypothesis, that meta-analysis is not the best scientific method to answer this question, as it is in fact unreliable in a few situations, has now been demonstrated by Pereira et al 4 As these authors concluded, "results of a meta-analysis are model-dependent" 5 and "results from meta-analytic studies can be seriously overestimated, yield-ing misleading conclusions." 6 As we are living in an era of "evidence-based medicine," meta-analysis has become one of the main scientific tools for researchers to arrive at conclusions regarding medicine.…”

“…For instance, are the relative reductions of vasodilator prostaglandins (protacyclin) and the increase of vasoconstricting prostaglandin (thromboxane) really responsible for the onset of preeclampsia? Here, we thank Pereira et al 4 for helping us to answer the first question.…”

“…In our clinical experience, we have not observed prevention of preeclampsia in patients that have used low-dose aspirin, which is also demonstrated by recent controlled (randomized) trials, with less bias of case selection. 3,4 These more recent results can be explained by the fact that secondary prevention is based on the pathophysiological concepts of preeclampsia, which have yet to be clarified. For instance, are the relative reductions of vasodilator prostaglandins (protacyclin) and the increase of vasoconstricting prostaglandin (thromboxane) really responsible for the onset of preeclampsia?…”

Aspirin for pre‐eclampsia: beware of subgroup meta‐analysis

“…Contradictory findings between large trials and systematic reviews led to the first contentious issue surrounding aspirin: should we believe results of large trials or systematic reviews? The difficulty in relying on RCTs alone is that they are often not large enough to allow detection of modest effects that may still be clinically meaningful.…”