ArticleDrug and alcohol dependence2022
Trajectories of craving during medication-assisted treatment for opioid-use disorder: Subtyping for early identification of higher risk.
Article in Drug and alcohol dependence, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.
- Predictive Models for Identifying Adult Patients at High Risk of Developing Opioid-Related Harms: a Systematic Review.Drug safety · 2025Pooled it
- Longitudinal craving profiles in cannabis use disorder: A latent class growth analysis of the achieving cannabis cessation: Evaluating N-Acetylcysteine Treatment (ACCENT) (CTN-0053) trial.Drug and alcohol dependence · 2026Trial
- Investigating craving as an indicator of early response to buprenorphine treatment among adults with opioid use disorder.Journal of consulting and clinical psychology · 2026Trial
- Craving for a Robust Methodology: A Systematic Review of Machine Learning Algorithms on Substance-Use Disorders Treatment Outcomes.International journal of mental health and addiction · 2026Article
- Computational modeling of the temporal influences between cues, craving and use in addiction: a dynamical system analysis based on ecological momentary assessment data.Translational psychiatry · 2025Article
- Sex disparities in outcome of medication-assisted therapy of opioid use disorder: Nationally representative outpatient clinic data.Drug and alcohol dependence · 2025Observational
- Craving changes in first 14 days of addiction treatment: an outcome predictor of 5 years substance use status?Translational psychiatry · 2024Article
- Machine learning models for temporally precise lapse prediction in alcohol use disorder.Journal of psychopathology and clinical science · 2024Article
- Sex disparities in outcome of medication-assisted therapy of opioid use disorder: Nationally representative study.medRxiv : the preprint server for health sciences · 2024Article
- Time-varying effect modeling with intensive longitudinal data: Examining dynamic links among craving, affect, self-efficacy and substance use during addiction recovery.Addiction (Abingdon, England) · 2023Article
- Trajectories of drug treatment and illicit opioid use in the AIDS Linked to the IntraVenous Experience cohort, 2014-2019.The International journal on drug policy · 2023Article
- Examining Associations Between Negative Affect and Substance Use in Treatment-Seeking Samples: A Review of Studies Using Intensive Longitudinal Methods.Current addiction reports · 2022Article
- Insights into Exosome in the Intervertebral Disc: Emerging Role for Disc Homeostasis and Normal Function.International journal of medical sciences · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
aimsTo examine evidence for subtypes of opioid craving trajectories during medication for opioid use disorder (MOUD), and to (a) test whether these subtypes differed on MOUD-related outcomes, and (b) determine whether nonresponders could be identified before treatment initiation. DESIGN, SETTING, AND
participantsOutpatients (n = 211) being treated with buprenorphine or methadone for up to 16 weeks. Growth mixture modeling was used to identify unobserved craving-trajectory subtypes. Support Vector Machines (SVM) were trained to predict subtype membership from pretreatment data. MEASUREMENTS: Self-reported opioid craving (Ecological Momentary Assessment - EMA - three random moments per day). Participant-initiated EMA reports of drug use or higher-than-usual stress. Addiction Severity Index (ASI) pretreatment.
findingsFour craving trajectories were identified: Low (73%); High and Increasing (HIC) (10.9%); Increasing and Decreasing (8.5%); and Rapidly Declining (7.6%). The HIC subgroup reported the highest use of heroin, any opiate, and cannabis during treatment. The Low Craving subgroup reported the lowest use of heroin or any opiate use, and the lowest levels of stress and drug-cue exposure during treatment. SVM models predicting HIC membership before treatment initiation had a sensitivity of 0.70, specificity of 0.78, and accuracy of 0.77. Including 3 weeks of EMA reports increased sensitivity to 0.78, specificity to 0.84, and accuracy to 0.85.
conclusionsSubgroups of MOUD patients show distinct patterns of opioid craving during treatment. Subgroups differ on critical outcomes including drug-use lapse, stress, and exposure to drug cues. Data from enrollment and early in treatment may help focus clinical attention.
Indexed as
Identifiers
What OpenQuestion holds
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.