ArticleTrials2024
Standardized study performance, quality assurance, and quality control in a cluster-randomized trial: the Pneumococcal Vaccine Schedules trial.
Article in Trials, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
21 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Randomized controlled trials are considered the "gold standard" for evaluating the effectiveness of an intervention. However, large-scale, cluster-randomized trials are complex and costly to implement. The generation of accurate, reliable, and high-quality data is essential to ensure the validity and generalizability of findings. Robust quality assurance and quality control procedures are important to optimize and validate the quality, accuracy, and reliability of trial data. To date, few studies have reported on study procedures to assess and optimize data integrity during the implementation of large cluster-randomized trials. The dearth of literature on these methods of trial implementation may contribute to questions about the quality of data collected in clinical trials. Trial protocols should consider the inclusion of quality assurance indicators and targets for implementation. Publishing quality assurance and control measures implemented in clinical trials should increase public trust in the findings from such studies. In this manuscript, we describe the development and implementation of internal and external quality assurance and control procedures and metrics in the Pneumococcal Vaccine Schedules trial currently ongoing in rural Gambia. This manuscript focuses on procedures and metrics to optimize trial implementation and validate clinical, laboratory, and field data. We used a mixture of procedure repetition, supervisory visits, checklists, data cleaning and verification methods and used the metrics to drive process improvement in all domains.
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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.