Augmenting Treatment Arms With External Data Through Propensity-Score Weighted Power Priors: An Application in Expanded Access.

The incorporation of real-world data to supplement the analysis of trials and improve decision-making has spurred the development of statistical techniques to account for introduced confounding. Recently, "hybrid" methods have been developed through which measured confounding is first attenuated via propensity scores and unmeasured confounding is addressed through (Bayesian) dynamic borrowing. Most efforts to date have focused on augmenting control arms with historical controls.

Health Insurance Coverage and Unplanned Births in Rotterdam, the Netherlands: A Natural Experiment in the Generation R Study.

Objectives: Starting January 1 2004, contraception was removed from the Dutch social health insurance for people aged 21 years and over. This study investigated the effect of social health insurance coverage for contraception on unplanned births.

Methods: Data from the Generation R Study was used, a population-based birth cohort of pregnant people with delivery dates between 2002 and 2006 (N = 2516) in Rotterdam, the Netherlands.

Mediation of the Association Between ε4 Genotype, Cognition, and Dementia by Neuropathology Imaging Markers in the Rotterdam Study.

Background And Objectives: Insight into -related pathways is important to unravel pathophysiology and identify therapeutic targets against late-life cognitive decline. We aimed to estimate mediators of 4 on cognition and dementia through different disease markers on structural in vivo brain imaging.

Methods: All participants from the population-based Rotterdam Study who underwent brain MRI between 2005 and 2009 were included.

Reducing Inequalities in Timing of Antenatal Care Initiation: A Hypothetical Intervention in the Generation R Study.

Background: Much research has focused on identifying predictors of late antenatal care initiation. Many of these predictors (e.g.

Directed Acyclic Graphs in Decision-Analytic Modeling: Bridging Causal Inference and Effective Model Design in Medical Decision Making.

Decision-analytic models (DAMs) are essentially informative yet complex tools for solving questions in medical decision making. When their complexity grows, the need for causal inference techniques becomes evident as causal relationships between variables become unclear. In this methodological commentary, we argue that graphical representations of assumptions on such relationships, directed acyclic graphs (DAGs), can enhance the transparency of decision models and aid in parameter selection and estimation through visually specifying backdoor paths (i.

Evaluating hypothetical prevention strategies for internalizing symptoms in the general population and at-risk children.

Objective: Specific modifiable factors (e.g., screen time [ST], sleep duration, physical activity, or social connections) are targets for reducing depression risk in adults.

Making Drug Approval Decisions in the Face of Uncertainty: Cumulative Evidence versus Value of Information.

Background: The COVID-19 pandemic underscored the criticality and complexity of decision making for novel treatment approval and further research. Our study aims to assess potential decision-making methodologies, an evaluation vital for refining future public health crisis responses.

Methods: We compared 4 decision-making approaches to drug approval and research: the Food and Drug Administration's policy decisions, cumulative meta-analysis, a prospective value-of-information (VOI) approach (using information available at the time of decision), and a reference standard (retrospective VOI analysis using information available in hindsight).

Reducing behavior problems in children born after an unintended pregnancy: the generation R study.

Objectives: To examine differences in behavior problems between children from intended versus unintended pregnancies, and to estimate how much the difference in problem behavior would be reduced if postnatal depression was eliminated and social support was increased within 6 months after birth.

Methods: Data from the Generation R Study were used, a population-based birth cohort in Rotterdam, the Netherlands (N = 9621). Differences in child internalizing and externalizing behavior at ages 1.

Examining longitudinal associations between prenatal exposure to infections and child brain morphology.

Background: Maternal infection during pregnancy has been identified as a prenatal risk factor for the later development of psychopathology in exposed offspring. Neuroimaging data collected during childhood has suggested a link between prenatal exposure to maternal infection and child brain structure and function, potentially offering a neurobiological explanation for the emergence of psychopathology. Additionally, preclinical studies utilizing repeated measures of neuroimaging data suggest that effects of prenatal maternal infection on the offspring's brain may normalize over time (i.

Attention-deficit hyperactivity disorder symptoms and brain morphology: Addressing potential selection bias with inverse probability weighting.

The goal of this study was to examine what happens to established associations between attention deficit hyperactivity disorder (ADHD) symptoms and cortical surface and thickness regions once we apply inverse probability of censoring weighting (IPCW) to address potential selection bias. Moreover, we illustrate how different factors that predict participation contribute to potential selection bias. Participants were 9- to 11-year-old children from the Generation R study (N = 2707).

Falsification of the instrumental variable conditions in Mendelian randomization studies in the UK Biobank.

Mendelian randomization (MR) is an increasingly popular approach to estimating causal effects. Although the assumptions underlying MR cannot be verified, they imply certain constraints, the instrumental inequalities, which can be used to falsify the MR conditions. However, the instrumental inequalities are rarely applied in MR.

Diagnostic accuracy of MRI techniques for treatment response evaluation in patients with brain metastasis: A systematic review and meta-analysis.

Background: Treatment response assessment in patients with brain metastasis uses contrast enhanced T1-weighted MRI. Advanced MRI techniques have been studied, but the diagnostic accuracy is not well known. Therefore, we performed a metaanalysis to assess the diagnostic accuracy of the currently available MRI techniques for treatment response.

Invited Commentary: Conducting and Emulating Trials to Study Effects of Social Interventions.

All else being equal, if we had 1 causal effect we wished to estimate, we would conduct a randomized trial with a protocol that mapped onto that causal question, or we would attempt to emulate that target trial with observational data. However, studying the social determinants of health often means there are not just 1 but several causal contrasts of simultaneous interest and importance, and each of these related but distinct causal questions may have varying degrees of feasibility in conducting trials. With this in mind, we discuss challenges and opportunities that arise when conducting and emulating such trials.

Do Case-Control Studies Always Estimate Odds Ratios?

Case-control studies are an important part of the epidemiologic literature, yet confusion remains about how to interpret estimates from different case-control study designs. We demonstrate that not all case-control study designs estimate odds ratios. On the contrary, case-control studies in the literature often report odds ratios as their main parameter even when using designs that do not estimate odds ratios.