ArticleAlcoholism, clinical and experimental research2016
Missing Data in Alcohol Clinical Trials with Binary Outcomes.
Article in Alcoholism, clinical and experimental research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed.
- Exploring the role of gender on treatment outcomes in older adults with alcohol use disorder.Alcohol, clinical & experimental research · 2025Trial
- A randomized comparison of extended-release naltrexone with or without patient navigation vs enhanced treatment-as-usual for incarcerated adults with opioid use disorder.Journal of substance abuse treatment · 2020Trial
- World Health Organization risk drinking level reductions are associated with improved functioning and are sustained among patients with mild, moderate and severe alcohol dependence in clinical trials in the United States and United Kingdom.Addiction (Abingdon, England) · 2020Trial
- Maintenance of World Health Organization Risk Drinking Level Reductions and Posttreatment Functioning Following a Large Alcohol Use Disorder Clinical Trial.Alcoholism, clinical and experimental research · 2019Trial
- Evaluation of Drinking Risk Levels as Outcomes in Alcohol Pharmacotherapy Trials: A Secondary Analysis of 3 Randomized Clinical Trials.JAMA psychiatry · 2019Trial
- Predictors and Outcomes of Twelve-Step Sponsorship of Stimulant Users: Secondary Analyses of a Multisite Randomized Clinical Trial.Journal of studies on alcohol and drugs · 2017Trial
- Reductions in World Health Organization Risk Drinking Level Are Associated With Reductions in Alcohol Use Disorder Diagnosis and Criteria: Evidence From an Alcohol Pharmacotherapy Trial.Journal of addiction medicineTrial
- Telehealth-Delivered Mindfulness-Based Intervention: Protocol for a Randomized Clinical Trial for Individuals With Alcohol Use Disorder.JMIR research protocols · 2026Article
- Missing Data Sensitivity Analyses for Alcohol Research.Alcohol, clinical & experimental research · 2026Article
- K-nearest neighbor algorithm for imputing missing longitudinal prenatal alcohol data.Advances in drug and alcohol research · 2024Article
- Response to Letter to the Editors regarding 'A Meta-Regression of Trial Features Predicting the Effects of Alcohol Use Disorder Pharmacotherapies on Drinking Outcomes in Randomized Clinical Trials: A Secondary Data Analysis'.Alcohol and alcoholism (Oxford, Oxfordshire) · 2023Article
- Article
- A Meta-Regression of Trial Features Predicting the Effects of Alcohol Use Disorder Pharmacotherapies on Drinking Outcomes in Randomized Clinical Trials: A Secondary Data Analysis.Alcohol and alcoholism (Oxford, Oxfordshire) · 2022Review
- Validity and measurement invariance of the Addictions Neuroclinical Assessment incentive salience domain among treatment-seekers with alcohol use disorder.Journal of substance abuse treatment · 2021Article
- Potential impact of missing outcome data on treatment effects in systematic reviews: imputation study.BMJ (Clinical research ed.) · 2020Review
- Results of Database Studies in Spine Surgery Can Be Influenced by Missing Data.Clinical orthopaedics and related research · 2017Article
- Tdap Vaccination Among Healthcare Personnel, Internet Panel Survey, 2012-2014.American journal of preventive medicine · 2017Article
- Volatility and change in chronic pain severity predict outcomes of treatment for prescription opioid addiction.Addiction (Abingdon, England) · 2017Article
- Prediction of Suicide Ideation and Attempt Among Substance-Using Patients in Primary Care.Journal of the American Board of Family Medicine : JABFMArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
backgroundMissing data are common in alcohol clinical trials for both continuous and binary end points. Approaches to handle missing data have been explored for continuous outcomes, yet no studies have compared missing data approaches for binary outcomes (e.g., abstinence, no heavy drinking days). This study compares approaches to modeling binary outcomes with missing data in the COMBINE study.
methodsWe included participants in the COMBINE study who had complete drinking data during treatment and who were assigned to active medication or placebo conditions (N = 1,146). Using simulation methods, missing data were introduced under common scenarios with varying sample sizes and amounts of missing data. Logistic regression was used to estimate the effect of naltrexone (vs. placebo) in predicting any drinking and any heavy drinking outcomes at the end of treatment using 4 analytic approaches: complete case analysis (CCA), last observation carried forward (LOCF), the worst case scenario (WCS) of missing equals any drinking or heavy drinking, and multiple imputation (MI). In separate analyses, these approaches were compared when drinking data were manually deleted for those participants who discontinued treatment but continued to provide drinking data.
resultsWCS produced the greatest amount of bias in treatment effect estimates. MI usually yielded less biased estimates than WCS and CCA in the simulated data and performed considerably better than LOCF when estimating treatment effects among individuals who discontinued treatment.
conclusionsMissing data can introduce bias in treatment effect estimates in alcohol clinical trials. Researchers should utilize modern missing data methods, including MI, and avoid WCS and CCA when analyzing binary alcohol clinical trial outcomes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.