ArticlePloS one2017
Second thoughts on the final rule: An analysis of baseline participant characteristics reports on ClinicalTrials.gov.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Automated detection of over- and under-dispersion in baseline tables in randomised controlled trials.F1000Research · 2022Article
- Latent Dirichlet Allocation in predicting clinical trial terminations.BMC medical informatics and decision making · 2019Article
- The 10-year Landscape of United States-Registered Parkinson Disease Clinical Trials: 2007-2016.Movement disorders clinical practiceArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundClinicalTrials.gov is valuable for aggregate-level analysis of trials. The recently published final rule aims to improve reporting of trial results. We aimed to assess variability in ClinicalTirals.gov records reporting participants' baseline measures. METHODS AND
findingsThe September 2015 edition of the database for Aggregate Analysis of ClinicalTrials.gov (AACT), was used in this study. To date, AACT contains 186,941 trials of which 16,660 trials reporting baseline (participant) measures were analyzed. We also analyzed a subset of 13,818 Highly Likely Applicable Clinical Trials (HLACT), for which reporting of results is likely mandatory and compared a random sample of 30 trial records to their journal articles. We report counts for each mandatory baseline measure and variability reporting in their formats. The AACT dataset contains 8,161 baseline measures with 1206 unique measurement units. However, of these 6,940 (85%) variables appear only once in the dataset. Age and Gender are reported using many different formats (178 and 49 respectively). "Age" as the variable name is reported in 60 different formats. HLACT subset reports measures using 3,931 variables. The most frequent Age format (i.e. mean (years) ± sd) is found in only 45% of trials. Overall only 4 baseline measures (Region of Enrollment, Age, Number of Participants, and Gender) are reported by > 10% of trials. Discrepancies are found in both the types and formats of ClinicalTrials.gov records and their corresponding journal articles. On average, journal articles include twice the number of baseline measures (13.6±7.1 (sd) vs. 6.6±7.6) when compared to the ClinicalTrials.gov records that report any results.
conclusionsWe found marked variability in baseline measures reporting. This is not addressed by the final rule. To support secondary use of ClinicalTrials.gov, a uniform format for baseline measures reporting is warranted.
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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.