686 HLVS and LPVS, combined with whether or not a Sen- precision (small studies) give different results from studies sormedics ventilator was used. The reported RRRs were with greater precision (larger studies). Asymmetry in the comparable to those in the ﬁrst model. Type of ventila- funnel plot may therefore result not from a systematic tor did not have a large effect compared with ventilation under-reporting of negative trials but from an essential strategies (RRR = 0.94 and RRR = 0.90). The HLVS was difference between smaller and larger studies that arises associated with a decrease of the RRs comparing HFV from inherent between-study heterogeneity [26]; thus, with CMV (RRR = 0.44 and RRR = 0.45), while LPVS in- if larger studies were also associated with changes in creased the RRs to the line of no effect (RRR = 2.06 and ventilation strategies and these strategies resulted in RRR = 1.59). changes in reported RRs, the assumed publication bias would be, in fact, a real association between ventilation strategy and study outcome; therefore, we conditioned the Discussion association between precision and effect size, presumably caused by publication bias, on ventilation strategies. This Our meta-regression analysis showed a clear trend of resulted in a lower p-value for publication bias and more decreasing differences in pulmonary outcome between symmetrical distribution of studies in subgroups in the HFV and CMV in randomized trials conducted in pre- funnel plots; therefore, what appeared to be publication mature neonates with IRDS over the years. The most bias could also be explained by differences in ventilation likely hypothesis for this trend was the application of strategies related to both study size and observed relative a LPVS in the most recent studies. Use of surfactant could risks. However, it should be pointed out that the strength also have a signiﬁcant contribution, but only one study of this evidence is difﬁcult to assess because fewer studies did not use surfactant [12]. In previous meta-analyses, in the subgroups automatically resulted in less power to subgroup analyses or cumulative methods were used detect publication bias. to explore heterogeneity [4, 5, 7]. Subgroup analysis is Other alternative hypotheses that have been formulated equivalent to meta-regression with a categorical trial-level to explain differences among studies were also less covariate. Considering subgroup analysis formally as compatible with the evidence [9]. The type of ventilator, a meta-regression has advantages, since it focuses on Sensormedics vs other types of high-frequency ventilators, differences between subgroups as is appropriate, rather displayed RRR close to one. In the crude analyses, prior than the effects in each subgroup separately. Furthermore, time on CMV before study initiation showed contradictory it is appropriate to use meta-regression to explore sources effects to what was hypothesized [10]. The adjusted of heterogeneity, even if an initial overall test for hetero- analyses showed conﬂicting results depending on the geneity is non-signiﬁcant. This test often has low power outcome. Gestational age and birth weight could also and therefore a non-signiﬁcant result does not reliably inﬂuence the magnitude of the effect of HFV compared identify lack of heterogeneity [25]. with CMV. In the adjusted analysis gestational age did not In this meta-regression analysis we evaluated in a quan- change the RR for CLD but showed an increase of the RR titative way a number of hypotheses that were raised to for less premature neonates. Finally, an increased risk of account for different results between randomized trials. CLD was not accompanied by a greater relative beneﬁt of A relatively large proportion of well-conducted trials HFV as compared with CMV. were available for the analyses. For most explanatory The observed effects of continuous variables, such as variables there were important differences among trials. time on CMV or gestational age, could be exaggerated by The effects of the two most important covariates, HLVS small studies with outlying results. For the covariate, time and LPVS, were consistent in the different models and on CMV, the two largest studies showed results that were were even increased in effect size by adjusting for other compatible with the hypothesis that this had no important covariates. None of the competing hypotheses were more impact on the results of these trials [2, 3]. The same fact likely to inﬂuence results as shown by calculating the applied to the effect of baseline incidence of CLD or death RRRs. Common pitfalls in meta-regression analysis can or CLD. Gestational age and weight were comparable be- occur, such as multiple or post-hoc analyses, and lead tween the two largest trials, which made it more difﬁcult to to data dredging and a high probability of false-positive ascertain the relevance of the hypothesis that in smaller and conclusions [25]. We, therefore, restricted our analyses to more premature infants HFV performed better than CMV a limited number of pre-speciﬁed explanatory covariates. treatment. The observed direction of the effect of gesta- Publication bias was considered unlikely as an explan- tional age and birth weight, however, was opposite to what ation of the apparent diminishing relative effect of HFV. the hypothesis predicted. If gestational age was to be inter- Publication bias is selection bias. If trials are selectively preted as a higher risk of acquiring CLD, one would expect published either because of their size or because of signif- that an increase in the incidence of CLD was associated icant results, this would result in an association between with a relatively lower incidence of CLD in HFV treated trial size and/or precision and the trial outcome. Strictly patients; however, linear regression analysis showed per- speaking, funnel plots probe whether studies with little fectly equal increase in both treatment groups. Still, the