A potential outcomes approach to defining and estimating gestational age-specific exposure effects during pregnancy.

Many studies seek to evaluate the effects of potentially harmful pregnancy exposures during specific gestational periods. We consider an observational pregnancy cohort where pregnant individuals can initiate medication usage or become exposed to a drug at various times during their pregnancy. An important statistical challenge involves how to define and estimate exposure effects when pregnancy loss or delivery can occur over time. Without proper consideration, the results of standard analysis may be vulnerable to selection bias, immortal time-bias, and time-dependent confounding. In this study, we apply the "target trials" framework of Hernán and Robins in order to define effects based on the counterfactual approach often used in causal inference. This effect is defined relative to a hypothetical randomized trial of timed pregnancy exposures where delivery may precede and thus potentially interrupt exposure initiation. We describe specific implementations of inverse probability weighting, G-computation, and Targeted Maximum Likelihood Estimation to estimate the effects of interest. We demonstrate the performance of all estimators using simulated data and show that a standard implementation of inverse probability weighting is biased. We then apply our proposed methods to a pharmacoepidemiology study to evaluate the potentially time-dependent effect of exposure to inhaled corticosteroids on birthweight in pregnant people with mild asthma.

Effectiveness and safety of tofacitinib in rheumatoid arthritis: a cohort study.

BACKGROUND: Tofacitinib is the first oral Janus kinase inhibitor approved for the treatment of rheumatoid arthritis (RA). We compared the effectiveness and safety of tofacitinib, disease-modifying antirheumatic drugs (DMARDs), tumor necrosis factor inhibitors (TNFi), and non-TNF biologics in patients with RA previously treated with methotrexate. METHODS: We used MarketScan® databases (2011-2014) to study methotrexate-exposed patients with RA who were newly prescribed tofacitinib, DMARDs other than methotrexate, and biologics. The date of first prescription was defined as the cohort entry. The therapy was considered effective if all of the following criteria from a claims-based algorithm were achieved at the first year of follow-up: high adherence, no biologic or tofacitinib switch or addition, no DMARD switch or addition, no increase in dose or frequency of index drug, no more than one glucocorticoid joint injection, and no new/increased oral glucocorticoid dose. The safety outcome was serious infections requiring hospitalization. Non-TNF biologics comprised the reference group. RESULTS: We included 21,832 patients with RA, including 0.8% treated with tofacitinib, 24.7% treated with other DMARDs, 61.2% who had started therapy with TNFi, and 13.3% treated with non-TNF biologics. The rates of therapy effectiveness were 15.4% for tofacitinib, 11.1% for DMARDs, 18.6% for TNFi, and 19.8% for non-TNF biologics. In adjusted analyses, tofacitinib and non-TNF biologics appeared to have similar effectiveness rates, whereas DMARD initiators were less effective than non-TNF biologics. We could not clearly establish if tofacitinib was associated with a higher rate of serious infections. CONCLUSIONS: In patients with RA previously treated with methotrexate, our comparisons of tofacitinib with non-TNF biologics, though not definitive, did not demonstrate differences with respect to hospitalized infections or effectiveness.