ArticleBMC medical research methodology2022
Challenges of using external data in clinical trials- an illustration in patients with COVID-19.
Article in BMC medical research methodology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 4 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.
Dexamethasone and Oxygen Support Strategies in ICU Patients With Covid-19 pneumonia_COVIDICUS
Randomised Evaluation of COVID-19 Therapy
Who cites it
4 citing papers in PubMed, 5 citations in OpenAlex.
- A review of use of external data and update on reporting standards in Sequential Multiple-Assignment Randomised Trials.Clinical trials (London, England) · 2026Review
- ACCESS-OSA: a randomized controlled trial for accurate, accessible, and cost-effective screening solutions for obstructive sleep apnoea: study protocol.Sleep advances : a journal of the Sleep Research Society · 2026Article
- External control arms: COVID-19 reveals the merits of using real world evidence in real-time for clinical and public health investigations.Frontiers in medicine · 2023Review
- A SuperLearner-enforced approach for the estimation of treatment effect in pediatric trials.Digital healthArticle
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
No grant is acknowledged in the PubMed record.
Abstract
backgroundTo improve the efficiency of clinical trials, leveraging external data on control and/or treatment effects, which is almost always available, appears to be a promising approach.
methodsWe used data from the experimental arm of the Covidicus trial evaluating high-dose dexamethasone in severely ill and mechanically ventilated COVID-19 patients, using published data from the Recovery trial as external data, to estimate the 28-day mortality rate. Primary approaches to deal with external data were applied.
resultsEstimates ranged from 0.241 ignoring the external data up to 0.294 using hierarchical Bayesian models. Some evidence of differences in mortality rates between the Covidicus and Recovery trials were observed, with an matched adjusted odds ratio of death in the Covidicus arm of 0.41 compared to the Recovery arm.
conclusionsThese indirect comparisons appear sensitive to the method used. None of those approaches appear robust enough to overcome randomized clinical trial data.
trial registrationCovidicus Trial: NCT04344730, First Posted: 14/04/2020; Recovery trial: NCT04381936.
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.