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ABSTRACT: Objective
Using a simple simulation, we illustrate why associations estimated from studies restricted to preterm births cannot be interpreted causally.Design, setting and population
Data simulation involving a hypothetical cohort of fetuses who may be healthy or have one or more of four pathological factors (termed A through D, increasing in severity) with known effects on gestational length and risk of mortality. We focus on babies born at ≤32 weeks of gestation.Methods
We visually represent the simulated population and compare the association between A (which may represent pre-eclampsia) and neonatal death. We then repeat the exercise with D (standing in for chorioamnionitis) as the exposure of interest.Main outcome measures
Odds ratios of neonatal death in the simulated data.Results
In most weeks, and for both A and D, the calculated odds ratios are substantially biased and underestimate the true risk of neonatal death associated with each pathology. For example, factor A has a true causal odds ratio of 1.50, yet it appears protective among births ≤32 weeks (estimated crude odds ratio 0.39; gestational age-adjusted odds ratio 0.71).Conclusions
Among very preterm births, virtually all babies are born with pathologies that increase the risk of adverse outcomes. Hence, babies exposed to one factor (e.g. pre-eclampsia) are compared with babies who have a mix of other pathologies. Such selection bias affects studies carried out among very preterm births (e.g. where pre-eclampsia appears to reduce risk of adverse neonatal outcomes).Tweetable abstract
Selection bias affects studies of preterm births, complicating interpretation.
SUBMITTER: Snowden JM
PROVIDER: S-EPMC5862739 | biostudies-literature | 2018 May
REPOSITORIES: biostudies-literature
BJOG : an international journal of obstetrics and gynaecology 20171030 6
<h4>Objective</h4>Using a simple simulation, we illustrate why associations estimated from studies restricted to preterm births cannot be interpreted causally.<h4>Design, setting and population</h4>Data simulation involving a hypothetical cohort of fetuses who may be healthy or have one or more of four pathological factors (termed A through D, increasing in severity) with known effects on gestational length and risk of mortality. We focus on babies born at ≤32 weeks of gestation.<h4>Methods</h4> ...[more]