ReviewThe journal of pain2023
Covariate Adjustment in Chronic Pain Trials: An Oft-Missed Opportunity.
Review in The journal of pain, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Clinical relevance of combined treatment with exercise in patients with chronic low back pain: a randomized controlled trial.Scientific reports · 2024Trial
- Efficacy of Cognitively-based compassion training for Veterans with chronic pain with psychological Comorbidity: Protocol for a randomized clinical trial.Contemporary clinical trials communications · 2026Article
- Optimising clinical trial methods for complex regional pain syndrome: a methodological framework (OptiMeth-CRPS).Pain reports · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
Self-reported pain intensity, frequently used as an outcome in randomized clinical trials (RCTs) of chronic pain, is often highly variable and could be associated with multiple baseline factors. Thus, the assay sensitivity of pain trials (ie, the ability of the trial to detect a true treatment effect) could be improved by including prespecified baseline factors in the primary statistical model. The objective of this focus article was to characterize the baseline factors included in statistical analyses of chronic pain RCTs. Seventy-three RCTs published between 2016 and 2021 that investigated interventions for chronic pain were included. The majority of trials identified a single primary analysis (72.6%; n = 53). Of these, 60.4% (n = 32) included one or more covariates in the primary statistical model, most commonly baseline value of the primary outcome, study site, sex, and age. Only one of the trials reported information regarding associations between covariates and outcomes (ie, information that could inform prioritization of covariates for prespecification in future analyses). These findings demonstrate inconsistent use of covariates in the statistical models in chronic pain clinical trials. Prespecified adjustments for baseline covariates that could increase precision and assay sensitivity should be considered in future clinical trials of chronic pain treatments. PERSPECTIVE: This review demonstrates inconsistent inclusion and potential underutilization of covariate adjustment in analyses of chronic pain RCTs. This article highlights areas for possible improvement in design and reporting related to covariate adjustment to improve efficiency in future RCTs.
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.