A further critique of the analytic strategy of adjusting for covariates to identify biologic mediation

BACKGROUND: Epidemiologic research is often devoted to etiologic investigation, and so techniques that may facilitate mechanistic inferences are attractive. Some of these techniques rely on rigid and/or unrealistic assumptions, making the biologic inferences tenuous. The methodology investigated here is effect decomposition: the contrast between effect measures estimated with and without adjustment for one or more variables hypothesized to lie on the pathway through which the exposure exerts its effect. This contrast is typically used to distinguish the exposure's indirect effect, through the specified intermediate variables, from its direct effect, transmitted via pathways that do not involve the specified intermediates. METHODS: We apply a causal framework based on latent potential response types to describe the limitations inherent in effect decomposition analysis. For simplicity, we assume three measured binary variables with monotonic effects and randomized exposure, and use difference contrasts as measures of causal effect. Previous authors showed that confounding between intermediate and the outcome threatens the validity of the decomposition strategy, even if exposure is randomized. We define exchangeability conditions for absence of confounding of causal effects of exposure and intermediate, and generate two example populations in which the no-confounding conditions are satisfied. In one population we impose an additional prohibition against unit-level interaction (synergism). We evaluate the performance of the decomposition strategy against true values of the causal effects, as defined by the proportions of latent potential response types in the two populations. RESULTS: We demonstrate that even when there is no confounding, partition of the total effect into direct and indirect effects is not reliably valid. Decomposition is valid only with the additional restriction that the population contain no units in which exposure and intermediate interact to cause the outcome. This restriction implies homogeneity of causal effects across strata of the intermediate. CONCLUSIONS: Reliable effect decomposition requires not only absence of confounding, but also absence of unit-level interaction and use of linear contrasts as measures of causal effect. Epidemiologists should be wary of etiologic inference based on adjusting for intermediates, especially when using ratio effect measures or when absence of interacting potential response types cannot be confidently asserted

(Errors in statistical tests)3

In 2004, Garcia-Berthou and Alcaraz published "Incongruence between test statistics and P values in medical papers," a critique of statistical errors that received a tremendous amount of attention. One of their observations was that the final reported digit of p-values in articles published in the journal Nature departed substantially from the uniform distribution that they suggested should be expected. In 2006, Jeng critiqued that critique, observing that the statistical analysis of those terminal digits had been based on comparing the actual distribution to a uniform continuous distribution, when digits obviously are discretely distributed. Jeng corrected the calculation and reported statistics that did not so clearly support the claim of a digit preference. However delightful it may be to read a critique of statistical errors in a critique of statistical errors, we nevertheless found several aspects of the whole exchange to be quite troubling, prompting our own meta-critique of the analysis

Observed and Expected Mortality in Cohort Studies

Epidemiologists often compare the observed number of deaths in a cohort with the expected number of deaths, obtained by multiplying person-time accrued in the cohort by mortality rates for a reference population (ideally, a reference that represents the mortality rate in the cohort in the absence of exposure). However, if exposure is hazardous (or salutary), this calculation will not consistently estimate the number of deaths expected in the absence of exposure because exposure will have affected the distribution of person-time observed in the study cohort. While problems with interpretation of this standard calculation of expected counts were discussed more than 2 decades ago, these discussions had little impact on epidemiologic practice. The logic of counterfactuals may help clarify this topic as we revisit these issues. In this paper, we describe a simple way to consistently estimate the expected number of deaths in such settings, and we illustrate the approach using data from a cohort study of mortality among underground miners

Association of Educational Attainment With Lifetime Risk of Cardiovascular Disease: The Atherosclerosis Risk in Communities Study

Estimates of lifetime risk may help raise awareness of the extent to which educational inequalities are associated with risk of cardiovascular disease (CVD). To estimate lifetime risks of CVD according to categories of educational attainment. Participants were followed from 1987 through December 31, 2013. All CVD events (coronary heart disease, heart failure, and stroke) were confirmed by physician review and International Classification of Diseases codes. A total of 13 948 whites and African Americans who were 45 to 64 years old and free of CVD at baseline were included from 4 US communities (Washington County, Maryland; Forsyth County, North Carolina; Jackson, Mississippi; and suburbs of Minneapolis, Minnesota). The data analysis was performed from June 7 to August 31, 2016. Educational attainment. We used a life table approach to estimate lifetime risks of CVD from age 45 through 85 years according to educational attainment. We adjusted for competing risks of death from underlying causes other than CVD. The sample of 13 948 participants was 56% female and 27% African American. During 269 210 person-years of follow-up, we documented 4512 CVD events and 2401 non-CVD deaths. Educational attainment displayed an inverse dose-response relation with cumulative risk of CVD, which became evident in middle age, with the most striking gap between those not completing vs completing high school. In men, lifetime risks of CVD were 59.0% (95% CI, 54.0%-64.1%) for grade school, 52.5% (95% CI, 47.7%-56.8%) for high school education without graduation, 50.9% (95% CI, 47.3%-53.9%) for high school graduation, 47.2% (95% CI, 41.5%-52.5%) for vocational school, 46.4% (95% CI, 42.8%-49.6%) for college with or without graduation, and 42.2% (95% CI, 36.6%-47.0%) for graduate/professional school; in women, 50.8% (95% CI, 45.7%-55.8%), 49.3% (95% CI, 45.1%-53.1%), 36.3% (95% CI, 33.4%-39.1%), 32.2% (95% CI, 26.0%-37.3%), 32.8% (95% CI, 29.1%-35.9%), and 28.0% (95% CI, 21.9%-33.3%), respectively. Educational attainment was inversely associated with CVD even within categories of family income, income change, occupation, or parental educational level. More than 1 in 2 individuals with less than high school education had a lifetime CVD event. Educational attainment was inversely associated with the lifetime risk of CVD, regardless of other important socioeconomic characteristics. Our findings emphasize the need for further efforts to reduce CVD inequalities related to educational disparities

Sensitivity Analyses for Sparse-Data Problems—Using Weakly Informative Bayesian Priors

Sparse-data problems are common, and approaches are needed to evaluate the sensitivity of parameter estimates based on sparse data. We propose a Bayesian approach that uses weakly informative priors to quantify sensitivity of parameters to sparse data. The weakly informative prior is based on accumulated evidence regarding the expected magnitude of relationships using relative measures of disease association. We illustrate the use of weakly informative priors with an example of the association of lifetime alcohol consumption and head and neck cancer. When data are sparse and the observed information is weak, a weakly informative prior will shrink parameter estimates toward the prior mean. Additionally, the example shows that when data are not sparse and the observed information is not weak, a weakly informative prior is not influential. Advancements in implementation of Markov Chain Monte Carlo simulation make this sensitivity analysis easily accessible to the practicing epidemiologist

Inpatient versus outpatient acute venous thromboembolism management: Trends and postacute healthcare utilization from 2011 to 2018

Background - Acute outpatient management of venous thromboembolism (VTE), which includes pulmonary embolism (PE) and deep vein thrombosis (DVT), is perceived to be as safe as inpatient management in some settings. How widely this strategy is used is not well documented. Methods and Results - Using MarketScan administrative claims databases for years 2011 through 2018, we identified patients with International Classification of Diseases (ICD) codes indicating incident VTE and trends in the use of acute outpatient management. We also evaluated healthcare utilization and hospitalized bleeding events in the 6 months following the incident VTE event. A total of 200 346 patients with VTE were included, of whom 50% had evidence of PE. Acute outpatient management was used for 18% of those with PE and 57% of those with DVT only, and for both DVT and PE its use increased from 2011 to 2018. Outpatient management was less prevalent among patients with cancer, higher Charlson comorbidity index scores, and whose primary treatment was warfarin as compared with a direct oral anticoagulant. Healthcare utilization in the 6 months following the incident VTE event was generally lower among patients managed acutely as outpatients, regardless of initial presentation. Acute outpatient management was associated with lower hazard ratios of incident bleeding risk for both patients who initially presented with PE (0.71 [95% CI, 0.61, 0.82]) and DVT only (0.59 [95% CI, 0.54, 0.64]). Conclusions - Outpatient management of VTE is increasing. In the present analysis, it was associated with lower subsequent healthcare utilization and fewer bleeding events. However, this may be because healthier patients were managed on an outpatient basis

A flexible Bayesian hierarchical model of preterm birth risk among US Hispanic subgroups in relation to maternal nativity and education

Abstract: Background: Previous research has documented heterogeneity in the effects of maternal education on adverse birth outcomes by nativity and Hispanic subgroup in the United States. In this article, we considered the risk of preterm birth (PTB) using 9 years of vital statistics birth data from New York City. We employed finer categorizations of exposure than used previously and estimated the risk dose-response across the range of education by nativity and ethnicity. Methods: Using Bayesian random effects logistic regression models with restricted quadratic spline terms for years of completed maternal education, we calculated and plotted the estimated posterior probabilities of PTB (gestational age < 37 weeks) for each year of education by ethnic and nativity subgroups adjusted for only maternal age, as well as with more extensive covariate adjustments. We then estimated the posterior risk difference between native and foreign born mothers by ethnicity over the continuous range of education exposures. Results: The risk of PTB varied substantially by education, nativity and ethnicity. Native born groups showed higher absolute risk of PTB and declining risk associated with higher levels of education beyond about 10 years, as did foreign-born Puerto Ricans. For most other foreign born groups, however, risk of PTB was flatter across the education range. For Mexicans, Central Americans, Dominicans, South Americans and “Others”, the protective effect of foreign birth diminished progressively across the educational range. Only for Puerto Ricans was there no nativity advantage for the foreign born, although small numbers of foreign born Cubans limited precision of estimates for that group. Conclusions: Using flexible Bayesian regression models with random effects allowed us to estimate absolute risks without strong modeling assumptions. Risk comparisons for any sub-groups at any exposure level were simple to calculate. Shrinkage of posterior estimates through the use of random effects allowed for finer categorization of exposures without restricting joint effects to follow a fixed parametric scale. Although foreign born Hispanic women with the least education appeared to generally have low risk, this seems likely to be a marker for unmeasured environmental and behavioral factors, rather than a causally protective effect of low education itself

Autoimmune disease and risk of postpartum venous thromboembolism

Background - The risk of pregnancy-related mortality in the United States has nearly doubled since 1990, with venous thromboembolism (VTE) accounting for approximately 10% of these deaths. Objectives - The objective of this study was to assess whether preexisting autoimmune disease is a risk factor for postpartum VTE. Methods - Using the MarketScan Commercial and Medicare Supplemental administrative databases, a retrospective cohort study analyzed whether postpartum persons with autoimmune disease had a higher risk of postpartum VTE incidence than postpartum persons without autoimmune disease. Using International Classification of Diseases codes, we identified 757,303 individuals of childbearing age who had a valid delivery date with at least 12 weeks of follow-up. Results - Individuals were, on average, 30.7 years old (SD, 5.4), and 3.7% (N = 27,997 of 757,303) of them had evidence of preexisting autoimmune disease. In covariate-adjusted models, postpartum persons with preexisting autoimmune disease had higher rates of postpartum VTE than postpartum persons without autoimmune disease (hazard ratio [HR], 1.33; 95% CI, 1.07-1.64). When analyzed by individual autoimmune disease, those with systemic lupus erythematosus (HR, 2.49; 95% CI, 1.47-4.21) and Crohn’s disease (HR, 2.49; 95% CI, 1.34-4.64) were at an elevated risk of postpartum VTE compared with those without autoimmune disease. Conclusion - Autoimmune disease was associated with a higher rate of postpartum VTE, with evidence that the association was most pronounced among individuals with systemic lupus erythematosus and Crohn’s disease. These findings suggest that postpartum persons of childbearing age with autoimmune disease may require more monitoring and prophylactic care after delivery to prevent potentially fatal VTE events

Obstructive Sleep Apnea and 15-Year Cognitive Decline: The Atherosclerosis Risk in Communities (ARIC) Study

Prospective data evaluating abnormal sleep quality and quantity with cognitive decline are limited because most studies used subjective data and/or had short follow-up. We hypothesized that, over 15 y of follow-up, participants with objectively measured obstructive sleep apnea (OSA) and other indices of poor sleep quantity and quality would experience greater decline in cognitive functioning than participants with normal sleep patterns