Epidemiology最新文献

Background: Observational studies have reported strongly protective effects of bariatric surgery on cardiovascular disease, but with oversimplified definitions of the intervention, eligibility criteria, and follow-up, which deviate from those in a randomized trial. We describe an attempt to estimate the effect of bariatric surgery on cardiovascular disease without introducing these sources of bias, which may not be entirely possible with existing observational data.

Methods: We propose two target trials among persons with diabetes: (1) bariatric operation (vs. no operation) among individuals who have undergone preoperative preparation (lifestyle modifications and screening) and (2) preoperative preparation and a bariatric operation (vs. neither preoperative nor operative component). We emulated both target trials using observational data of US veterans.

Results: Comparing bariatric surgery with no surgery (target trial #1; 8,087 individuals), the 7-year cardiovascular risk was 18.0% (95% CI = 6.9, 32.7) in the surgery group and 18.9% (95% CI = 17.7, 20.1) in the no-surgery group (risk difference -0.9, 95% CI = -12.0, 14.0). Comparing preoperative components plus surgery vs. neither (target trial #2; 10,065 individuals), the 7-year cardiovascular risk was 17.4% (95% CI = 13.6, 22.0) in the surgery group and 18.8% (95% CI = 17.8, 19.9) in the no-surgery group (risk difference -1.4, 95% CI = -5.1, 3.2). Body mass index and hemoglobin A1c were reduced with bariatric interventions in both emulations.

Conclusions: Within limitations of available observational data, our estimates do not provide evidence that bariatric surgery reduces cardiovascular disease and support equipoise for a randomized trial of bariatric surgery for cardiovascular disease prevention.

Life course epidemiology is hampered by the absence of large studies with exposures and outcomes measured at different life stages in the same individuals. We describe when the effect of an exposure ( A ) on an outcome ( Y ) in a target population is identifiable in a combined ("synthetic") cohort created by pooling an early-life cohort including measures of A with a late-life cohort including measures of Y . We enumerate causal assumptions needed for unbiased effect estimation in the synthetic cohort and illustrate by simulating target populations under four causal models. From each target population, we randomly sampled early- and late-life cohorts and created a synthetic cohort by matching individuals from the two cohorts based on mediators and confounders. We estimated the effect of A on Y in the synthetic cohort, varying matching variables, the match ratio, and the strength of association between matching variables and A . Finally, we compared bias in the synthetic cohort estimates when matching variables did not d-separate A and Y to the bias expected in the original cohort. When the set of matching variables includes all variables d-connecting exposure and outcome (i.e., variables blocking all backdoor and front-door pathways), the synthetic cohort yields unbiased effect estimates. Even when matching variables did not fully account for confounders, the synthetic cohort estimate was sometimes less biased than comparable estimates in the original cohort. Methods based on merging cohorts may hasten the evaluation of early- and mid-life determinants of late-life health but rely on available measures of both confounders and mediators.

This tutorial discusses a methodology for causal inference using longitudinal modified treatment policies. This method facilitates the mathematical formalization, identification, and estimation of many novel parameters and mathematically generalizes many commonly used parameters, such as the average treatment effect. Longitudinal modified treatment policies apply to a wide variety of exposures, including binary, multivariate, and continuous, and can accommodate time-varying treatments and confounders, competing risks, loss to follow-up, as well as survival, binary, or continuous outcomes. Longitudinal modified treatment policies can be seen as an extension of static and dynamic interventions to involve the natural value of treatment and, like dynamic interventions, can be used to define alternative estimands with a positivity assumption that is more likely to be satisfied than estimands corresponding to static interventions. This tutorial aims to illustrate several practical uses of the longitudinal modified treatment policy methodology, including describing different estimation strategies and their corresponding advantages and disadvantages. We provide numerous examples of types of research questions that can be answered using longitudinal modified treatment policies. We go into more depth with one of these examples, specifically, estimating the effect of delaying intubation on critically ill COVID-19 patients' mortality. We demonstrate the use of the open-source R package lmtp to estimate the effects, and we provide code on https://github.com/kathoffman/lmtp-tutorial.

Background: Prenatal ethylene oxide exposure may have adverse effects on fetal development. We examined the relationships between ethylene oxide hemoglobin (Hb) adduct levels and offspring's size at birth in a prospective European mother-child study.

Methods: This study included 1106 singletons from the NewGeneris project (2006-2010) with ethylene oxide Hb adducts measured in cord blood. We examined the relationships between adduct levels and offspring's size at birth among all infants and separately among infants of nonsmokers, using linear regression models for birth weight and birth head circumference and logarithmic binomial regression models for small for gestational age. We examined potential interactions between CYP2E1 single nucleotide polymorphisms in cord blood and the effects of ethylene oxide Hb adduct levels on offspring birth size.

Results: Higher quartiles of adduct levels as a measure of exposure were associated with decreasing birth weight and head circumference in the overall population. Compared to infants in the lowest quartile, those in the highest quartile exhibited lower birth weight (-70.73 g, 95% confidence interval = -141.16, -0.30) and reduced head circumference (-0.30 cm, 95% confidence interval = -0.58, -0.02). We observed similar, albeit less pronounced, patterns among infants of nonsmokers. There was no evidence of an association between ethylene oxide Hb adducts and risk of small for gestational age, nor consistent evidence of an interaction with CYP2E1 polymorphisms on the association between EO Hb adduct levels and offspring's size at birth.

Conclusion: Results suggest that higher ethylene oxide Hb adduct levels in cord blood are associated with a reduction in offspring birth size.

Purpose: Breast cancer has an average 10-year relative survival reaching 84%. This favorable survival is due, in part, to the introduction of biomarker-guided therapies. We estimated the population-level effect of the introduction of two adjuvant therapies-tamoxifen and trastuzumab-on recurrence using the trend-in-trend pharmacoepidemiologic study design.

Methods: We ascertained data on women diagnosed with nonmetastatic breast cancer who were registered in the Danish Breast Cancer Group clinical database. We used the trend-in-trend design to estimate the population-level effect of the introduction of (1) tamoxifen for postmenopausal women with estrogen receptor (ER)-positive breast cancer in 1982, (2) tamoxifen for premenopausal women diagnosed with ER-positive breast cancer in 1999, and (3) trastuzumab for women <60 years diagnosed with human epidermal growth factor receptor 2-positive breast cancer in 2007.

Results: For the population-level effect of the introduction of tamoxifen among premenopausal women diagnosed with ER-positive breast cancer in 1999, the risk of recurrence decreased by nearly one-half (OR = 0.52), consistent with evidence from clinical trials; however, the estimate was imprecise (95% confidence interval [CI] = 0.25, 1.85). We observed an imprecise association between tamoxifen use and recurrence from the time it was introduced in 1982 (OR = 1.24 95% CI = 0.46, 5.11), inconsistent with prior knowledge from clinical trials. For the introduction of trastuzumab in 2007, the estimate was also consistent with trial evidence, though imprecise (OR = 0.51; 95% CI = 0.21, 22.4).

Conclusions: We demonstrated how novel pharmacoepidemiologic analytic designs can be used to evaluate the routine clinical care and effectiveness of therapeutic advancements in a population-based setting while considering some limitations of the approach.