Sex differences in the risk of bronchopulmonary dysplasia and pulmonary hypertension: a Bayesian meta-analysis.

Abstract

Background: Bronchopulmonary dysplasia (BPD) is generally considered to be more frequent in males than in females. We conducted a Bayesian model-averaged (BMA) meta-analysis of studies addressing sex differences in the risk of developing different severities of BPD and BPD-associated pulmonary hypertension (BPD-PH).

Methods: We used BMA to calculate Bayes factors (BFs). The BF₁₀ is the ratio of the probability of the data under the alternative hypothesis (presence of sex differences) over the probability of the data under the null hypothesis (absence of sex differences). BPD was classified as BPD28 (Supplementary oxygen at or during 28 days), BPD36 (moderate-to-severe BPD; oxygen at 36 weeks postmenstrual age), mild, moderate, and severe BPD.

Results: We included 222 studies (541,826 infants). The BMA analysis showed evidence in favor of a male disadvantage in BPD28 (BF₁₀ > 10⁵), BPD36 (BF₁₀ > 10²¹), and severe BPD (BF₁₀ = 87.55), but not in mild BPD (BF₁₀ = 0.28), or BPD-PH (BF₁₀ = 0.54). The evidence for a male disadvantage in BPD decreased as the gestational age of the cohort decreased.

Conclusions: We confirmed the presence of a male disadvantage in moderate-to-severe BPD, but not in less severe forms of BPD or in BPD-PH. The male disadvantage in BPD is much less apparent in the more immature infants.

Impact: This Bayesian meta-analysis confirms that the risk of developing moderate to severe bronchopulmonary dysplasia (BPD) is approximately 20% higher in males than in females. Sex differences in BPD decrease with decreasing gestational age, are heterogeneous across geographic and sociodemographic settings, and have remained persistently stable over time. There is no evidence supporting sex differences in pulmonary hypertension associated with BPD. An important step in the process of individualizing the approach to BPD may be to consider the sex of the infant, as this information can be used to personalize care and potentially improve outcomes.