ArticleDrug and alcohol dependence2017
Statistical considerations in the choice of endpoint for drug use disorder trials.
Article in Drug and alcohol dependence, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 10 citations in OpenAlex.
- Characterizing cannabis use reduction and change in functioning during treatment: Initial steps on the path to new clinical endpoints.Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors · 2022Trial
- Exploring the performance of during-treatment substance use outcome measures in predicting longer-term psychosocial functioning and post-treatment abstinence.Drug and alcohol dependence · 2023Article
- Percentage of negative urine drug screens as a clinically meaningful endpoint for RCTs evaluating treatment for cocaine use.Drug and alcohol dependence · 2023Article
- The relationship of frequency of cocaine use to substance and psychiatric disorders in the U.S. general population.Drug and alcohol dependence · 2021Article
- Within-treatment frequency of use versus abstinence as a predictor of longitudinal post-treatment follow-up assessments of drug use.Drug and alcohol dependence · 2020Article
- Measuring Within-Individual Cannabis Reduction in Clinical Trials: A Review of the Methodological Challenges.Current addiction reports · 2019Article
- Methods to reduce the incidence of false negative trial results in substance use treatment research.Current opinion in psychology · 2019Review
- Distress tolerance trajectories following substance use treatment.Journal of consulting and clinical psychology · 2019Article
- What defines a clinically meaningful outcome in the treatment of substance use disorders: reductions in direct consequences of drug use or improvement in overall functioning?Addiction (Abingdon, England) · 2019Article
- Consumption outcomes in clinical trials of alcohol use disorder treatment: Consideration of standard drink misestimation.The American journal of drug and alcohol abuse · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundTo date, the US Food and Drug Administration (FDA) requires drug use disorder trials developing new medications to use abstinence, a clinically meaningful endpoint, as the primary outcome. Although abstinence is the gold standard, only a relatively small percentage of participants in drug use disorder trials ever achieve this endpoint. This has prompted clinical trialists to consider quantitative measures of frequency of use, recognizing that some reductions in drug use that fall short of complete abstinence may potentially represent clinically important improvements. While much of the discussion concerning alternative outcomes to abstinence has focused on their clinical relevance, there are important statistical considerations that should also be taken into account. PURPOSE: In this paper, we demonstrate and highlight the degree to which use of a quantitative measure of frequency of use, relative to a binary measure of abstinence, yields a very discernible increase in statistical power for assessing efficacy or effectiveness of treatments for drug use disorders.
conclusionWhile it is well established that dichotomizing a quantitative measure invariably results in loss of statistical power, what is less well recognized is the degree of loss in the context of drug use disorder trials. In some cases, the required sample size must be almost doubled to achieve the same level of power.
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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.