Contributions of preeclampsia to preterm delivery: a hypothetical interventional cohort study using incremental propensity scores.
Preeclampsia remains a leading cause of preterm delivery (PTD). Conventional average causal effect estimands may not always be perfectly suited for assessing preeclampsia's contributions because they rely on uniform counterfactual scenarios, such as everyone suffering from preeclampsia. A complementary approach is the incremental propensity score intervention (IPSI), which can address a more action-oriented causal inquiry: How would the population average risk of PTD change from current observed levels if each individual's odds of preeclampsia were reduced by a given amount?
We applied IPSI to two US population cohorts of singleton pregnancies, separated by two decades (1998-2002, 16.7 million; 2020-2023, 14.2 million), to evaluate the causal effects of gestational hypertension/preeclampsia (GHTN/PE) on PTD within each cohort. We developed and implemented a sensitivity analysis procedure using bias formulas to gauge the impact of potential unmeasured confounding.
Between 1998 and 2002, halving the individual odds of GHTN/PE would reduce the population average risk of PTD from observed [risk ratio (RR) = 0.969, 95% confidence interval (CI) 0.969-0.970]. Between 2020 and 2023, when GHTN/PE was more prevalent, halving the odds of preeclampsia would lead to an even greater reduction in average PTD risk (RR = 0.948, 95% CI 0.947-0.948). Sensitivity analyses demonstrated that these conclusions held under assumptions encoding relatively strong unmeasured confounding.
The IPSI approach offers more nuanced understanding and clinically meaningful interpretations of causal effects, such as by how much partially reducing the odds of GHTN/PE, while allowing it to remain non-zero, can lower the average risk of PTD.
We applied IPSI to two US population cohorts of singleton pregnancies, separated by two decades (1998-2002, 16.7 million; 2020-2023, 14.2 million), to evaluate the causal effects of gestational hypertension/preeclampsia (GHTN/PE) on PTD within each cohort. We developed and implemented a sensitivity analysis procedure using bias formulas to gauge the impact of potential unmeasured confounding.
Between 1998 and 2002, halving the individual odds of GHTN/PE would reduce the population average risk of PTD from observed [risk ratio (RR) = 0.969, 95% confidence interval (CI) 0.969-0.970]. Between 2020 and 2023, when GHTN/PE was more prevalent, halving the odds of preeclampsia would lead to an even greater reduction in average PTD risk (RR = 0.948, 95% CI 0.947-0.948). Sensitivity analyses demonstrated that these conclusions held under assumptions encoding relatively strong unmeasured confounding.
The IPSI approach offers more nuanced understanding and clinically meaningful interpretations of causal effects, such as by how much partially reducing the odds of GHTN/PE, while allowing it to remain non-zero, can lower the average risk of PTD.