Polypharmacy's Association With Mortality: Confounding From Underlying Morbidity.

Background: Studies consistently associate use of multiple medications with increased mortality. However, such studies often lack adequate adjustment for confounding, particularly from underlying diseases.

Objective: To illustrate challenges in studying the association between polypharmacy and mortality by examining this relationship in two separate populations.

Multi-ancestry genome-wide association study of topiramate's effects on heavy alcohol use.

Background: Topiramate reduces alcohol consumption in individuals who drink heavily. Candidate gene studies aimed at identifying genetic variants that predict topiramate's effects on drinking have yielded inconsistent findings. To identify genetic variation associated with treatment response, we conducted a genome-wide association study (GWAS) among participants in the Million Veteran Program (MVP) who initiated topiramate treatment.

Alcohol use disorder and body mass index show genetic pleiotropy and shared neural associations.

Despite neurobiological overlap, alcohol use disorder (AUD) and body mass index (BMI) show minimal genetic correlation (r), possibly due to mixed directions of shared variants. Here we applied MiXeR to investigate shared genetic architecture between AUD and BMI, conjunctional false discovery rate to detect shared loci and their directional effect, local analysis of (co)variant association for local r, functional mapping and annotation to identify lead single-nucleotide polymorphisms, Genotype-Tissue Expression (GTEx) to examine tissue enrichment and BrainXcan to assess associations with brain phenotypes. MiXeR indicated 82.

Glucagon-like peptide-1 receptor agonists, but not dipeptidyl peptidase-4 inhibitors, reduce alcohol intake.

BACKGROUNDDespite growing preclinical evidence that glucagon-like peptide1 receptor agonists (GLP-1RAs) could be repurposed to treat alcohol use disorder (AUD), clinical evidence is scarce. Additionally, the potential impact of dipeptidyl peptidase-4 inhibitors (DPP-4Is) on alcohol intake is largely unknown.METHODSWe conducted a large cohort study using 2008-2023 electronic health records data from the U.

Time to direct-acting antiviral initiation and liver-related events in people with HIV and hepatitis C virus.

Objective: People with HIV-hepatitis C virus (HCV) co-infection need antiretroviral treatment (ART) to suppress HIV and direct-acting antivirals (DAAs) to cure HCV. ART is typically prioritized, but delays in DAA initiation may increase the risk of liver-related events and HCV transmission to others.

Design: Target trial emulation with observational data collected in routine clinical practice from a collaboration of cohorts from Europe and North America.

Cannabis Use and Self-Reported Bothersome Symptoms in People with HIV.

Objective: While cannabis use is common among people with HIV (PWH), there have been few studies examining the association of use with health outcomes among PWH. We aimed to evaluate the association between cannabis use and bothersome physical and mental health symptoms using both self-report and a direct biomarker for cannabis use.

Method: The Medications, Alcohol and Substance use in HIV Study (MASH) is a cross-cohort study focused on polypharmacy and substance use among PWH.

Study protocol: Comparison of different risk prediction modelling approaches for COVID-19 related death using the OpenSAFELY platform.

On March 11th 2020, the World Health Organization characterised COVID-19 as a pandemic. Responses to containing the spread of the virus have relied heavily on policies involving restricting contact between people. Evolving policies regarding shielding and individual choices about restricting social contact will rely heavily on perceived risk of poor outcomes from COVID-19.

Four targets: an enhanced framework for guiding causal inference from observational data.

Observational studies play an increasingly important role in estimating causal effects of a treatment or an exposure, especially with the growing availability of routinely collected real-world data. To facilitate drawing causal inference from observational data, we introduce a conceptual framework centered around "four targets"-target estimand, target population, target trial, and target validity. We illustrate the utility of our proposed "four targets" framework with the example of buprenorphine dosing for treating opioid use disorder, explaining the rationale and process for employing the framework to guide causal thinking from observational data.

Utility of Candidate Genes From an Algorithm Designed to Predict Genetic Risk for Opioid Use Disorder.

Importance: Recently, the US Food and Drug Administration gave premarketing approval to an algorithm based on its purported ability to identify individuals at genetic risk for opioid use disorder (OUD). However, the clinical utility of the candidate genetic variants included in the algorithm has not been independently demonstrated.

Objective: To assess the utility of 15 genetic variants from an algorithm intended to predict OUD risk.

Benzodiazepine and z-drug prescribing in critical care survivors and the risk of rehospitalisation or death due to falls/trauma and due to any cause: a retrospective matched cohort study using the UK Clinical Practice Research Datalink.

Purpose: Benzodiazepines and z-drugs are often prescribed to critical care survivors due to high prevalence of mental health problems and insomnia. However, their safety has not been studied in this population.

Methods: Retrospective cohort study of 28,678 adult critical care survivors hospitalised in 2010 and 2018: 4844 prescribed benzodiazepines or z-drugs, matched to 23,834 unexposed survivors using UK Clinical Practice Research Datalink linked datasets.

What Are High-Quality Race and Ethnicity Data and How Are They Used in Health Equity Research?

The COVID-19 pandemic changed public awareness of the importance of high-quality race and ethnicity data for identifying and redressing widely documented racial and ethnic health inequity. This article emphasizes the importance of high-quality race and ethnicity data in health equity research, as highlighted by the COVID-19 pandemic. The article defines what constitutes high-quality race and ethnicity data, discusses challenges in using these data, and provides 2 cases that illustrate the role of these data in identifying and redressing health inequity.

How Should Meaningful Evidence Be Generated From Datasets?

Datasets are often considered "ideal" when they are large and contain longitudinal and representative data. But even research that uses ideal datasets might not generate high-quality evidence. This article emphasizes the roles that transparency plays in enhancing observational epidemiological findings' credibility and relevance and argues that epidemiological research can produce high-quality evidence even when datasets are not ideal.

A Mendelian randomization study of alcohol use and cardiometabolic disease risk in a multi-ancestry population from the Million Veteran Program.

Background: Observational studies link moderate alcohol consumption to reduced risk of cardiometabolic diseases, including coronary heart disease (CHD) and type 2 diabetes mellitus (T2D). Mendelian randomization (MR) studies suggest that these associations are due to confounding. We present observed and genetically proxied associations between alcohol consumption and the incidence of CHD and T2D among African Americans (AA), European Americans (EA), and Hispanic Americans (HA) from the Million Veteran Program.

Core Concepts in Pharmacoepidemiology: Quantitative Bias Analysis.

Pharmacoepidemiological studies provide important information on the safety and effectiveness of medications, but the validity of study findings can be threatened by residual bias. Ideally, biases would be minimized through appropriate study design and statistical analysis methods. However, residual biases can remain, for example, due to unmeasured confounders, measurement error, or selection into the study.

Severe Acute Liver Injury After Hepatotoxic Medication Initiation in Real-World Data.

Importance: Current approaches to classify the hepatotoxic potential of medications are based on cumulative case reports of acute liver injury (ALI), which do not consider the size of the exposed population. There is little evidence from real-world data (data relating to patient health status and/or the delivery of health care routinely collected from sources outside of a research setting) on incidence rates of severe ALI after initiation of medications, accounting for duration of exposure.

Objective: To identify the most potentially hepatotoxic medications based on real-world incidence rates of severe ALI and to examine how these rates compare with categorization based on case reports.

Contribution of Potentially Inappropriate Medications to Polypharmacy-Associated Risk of Mortality in Middle-Aged Patients: A National Cohort Study.

Background: The role of potentially inappropriate medications (PIMs) in mortality has been studied among those 65 years or older. While middle-aged individuals are believed to be less susceptible to the harms of polypharmacy, PIMs have not been as carefully studied in this group.

Objective: To estimate PIM-associated risk of mortality and evaluate the extent PIMs explain associations between polypharmacy and mortality in middle-aged patients, overall and by sex and race/ethnicity.

Candidate Genes from an FDA-Approved Algorithm Fail to Predict Opioid Use Disorder Risk in Over 450,000 Veterans.

Importance: Recently, the Food and Drug Administration gave pre-marketing approval to algorithm based on its purported ability to identify genetic risk for opioid use disorder. However, the clinical utility of the candidate genes comprising the algorithm has not been independently demonstrated.

Objective: To assess the utility of 15 variants in candidate genes from an algorithm intended to predict opioid use disorder risk.

Alcohol use disorder and body mass index show genetic pleiotropy and shared neural associations.

Despite neurobiological overlap, alcohol use disorder (AUD) and body mass index (BMI) show minimal genetic correlation (r), possibly due to mixed directions of shared variants. We applied MiXeR to investigate shared genetic architecture between AUD and BMI, conjunctional false discovery rate (conjFDR) to detect shared loci and their directional effect, Local Analysis of (co)Variant Association (LAVA) for local r, Functional Mapping and Annotation (FUMA) to identify lead single nucleotide polymorphisms (SNPs), Genotype-Tissue Expression (GTEx) to examine tissue enrichment, and BrainXcan to assess associations with brain phenotypes. MiXeR indicated 82.

Care interruptions and mortality among adults in Europe and North America.

Objective: Interruptions in care of people with HIV (PWH) on antiretroviral therapy (ART) are associated with adverse outcomes, but most studies have relied on composite outcomes. We investigated whether mortality risk following care interruptions differed from mortality risk after first starting ART.

Design: Collaboration of 18 European and North American HIV observational cohort studies of adults with HIV starting ART between 2004 and 2019.