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Sensitivity Analysis for Unmeasured Confounding in Meta-Analyses.

ABSTRACT: Random-effects meta-analyses of observational studies can produce biased estimates if the synthesized studies are subject to unmeasured confounding. We propose sensitivity analyses quantifying the extent to which unmeasured confounding of specified magnitude could reduce to below a certain threshold the proportion of true effect sizes that are scientifically meaningful. We also develop converse methods to estimate the strength of confounding capable of reducing the proportion of scientifically meaningful true effects to below a chosen threshold. These methods apply when a "bias factor" is assumed to be normally distributed across studies or is assessed across a range of fixed values. Our estimators are derived using recently proposed sharp bounds on confounding bias within a single study that do not make assumptions regarding the unmeasured confounders themselves or the functional form of their relationships with the exposure and outcome of interest. We provide an R package, EValue, and a free website that compute point estimates and inference and produce plots for conducting such sensitivity analyses. These methods facilitate principled use of random-effects meta-analyses of observational studies to assess the strength of causal evidence for a hypothesis.

SUBMITTER: Mathur MB

PROVIDER: S-EPMC7518377 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Sensitivity Analysis for Unmeasured Confounding in Meta-Analyses.

Mathur Maya B MB VanderWeele Tyler J TJ

Journal of the American Statistical Association 20190430 529

Random-effects meta-analyses of observational studies can produce biased estimates if the synthesized studies are subject to unmeasured confounding. We propose sensitivity analyses quantifying the extent to which unmeasured confounding of specified magnitude could reduce to below a certain threshold the proportion of true effect sizes that are scientifically meaningful. We also develop converse methods to estimate the strength of confounding capable of reducing the proportion of scientifically m ...[more]

PMID: 32981992

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Project description:BACKGROUND:Although it has been established that low socioeconomic status is linked to increased risk of death after stroke, the mechanisms behind this link are still unclear. In this study we aim to shed light on the relationship between income level and survival after stroke by investigating the extent to which differences in stroke severity account for differences in survival. METHODS:The study was based on patients registered in Riksstroke (the Swedish stroke register) with first time ischemic stroke (n?=?51,159) or intracerebral hemorrhage (n?=?6777) in 2009-2012. We used causal mediation analysis to decompose the effect of low income on 3-month case fatality into a direct effect and an indirect effect due to stroke severity. Since causal mediation analysis relies on strong assumptions regarding residual confounding of the relationships involved, recently developed methods for sensitivity analysis were used to assess the robustness of the results to unobserved confounding. RESULTS:After adjustment for observed confounders, patients in the lowest income tertile had a 3.2% (95% CI: 0.9-5.4%) increased absolute risk of 3-month case fatality after intracerebral hemorrhage compared to patients in the two highest tertiles. The corresponding increase for case fatality after ischemic stroke was 1% (0.4-1.5%). The indirect effect of low income, mediated by stroke severity, was 1.8% (0.7-2.9%) for intracerebral hemorrhage and 0.4% (0.2-0.6%) for ischemic stroke. Unobserved confounders affecting the risk of low income, more severe stroke and case fatality in the same directions could explain the indirect effect, but additional adjustment to observed confounders did not alter the conclusions. CONCLUSIONS:This study provides evidence that as much as half of income-related inequalities in stroke case fatality is mediated through differences in stroke severity. Targeting stroke severity could therefore lead to a substantial reduction in inequalities and should be prioritized. Sensitivity analysis suggests that additional adjustment for a confounder of greater impact than age would be required to considerably alter our conclusions.

Project description:IntroductionConsideration of confounding factors about the association between Lower Respiratory Tract Infections (LRTI) in childhood and the development of subsequent wheezing has been incompletely described. We determined the association between viral LRTI at ≤ 5 years of age and the development of wheezing in adolescence or adulthood by a meta-analysis and a sensitivity analysis including comparable studies for major confounding factors.MethodsWe performed searches through Pubmed and Global Index Medicus databases. We selected cohort studies comparing the frequency of subsequent wheezing in children with and without LRTI in childhood regardless of the associated virus. We extracted the publication data, clinical and socio-demographic characteristics of the children, and confounding factors. We analyzed data using random effect model.ResultsThe meta-analysis included 18 publications (22 studies) that met the inclusion criteria. These studies showed that viral LRTI in children ≤ 3 years was associated with an increased risk of subsequent development of wheezing (OR = 3.1, 95% CI = 2.4-3.9). The risk of developing subsequent wheezing was conserved when considering studies with comparable groups for socio-demographic and clinical confounders.ConclusionsWhen considering studies with comparable groups for most confounding factors, our results provided strong evidence for the association between neonatal viral LRTI and the subsequent wheezing development. Further studies, particularly from lower-middle income countries, are needed to investigate the role of non-bronchiolitis and non-HRSV LRTI in the association between viral LRTI in childhood and the wheezing development later. In addition, more studies are needed to investigate the causal effect between childhood viral LRTI and the wheezing development later.Trial registrationReview registration: PROSPERO, CRD42018116955; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42018116955.

Dataset Information

Sensitivity Analysis for Unmeasured Confounding in Meta-Analyses.

Publications

Sensitivity Analysis for Unmeasured Confounding in Meta-Analyses.

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