ArticleTherapeutic innovation & regulatory science2024
Does Central Statistical Monitoring Improve Data Quality? An Analysis of 1,111 Sites in 159 Clinical Trials.
Article in Therapeutic innovation & regulatory science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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
8 citing papers in PubMed.
- Optimising data completeness and quality in multicentre randomised clinical trials using central data monitoring: a pragmatic approach.BMC medical research methodology · 2026Trial
- Quantifying the Financial Return on Investment of Risk-Based Quality Management Implementation in Clinical Development.Therapeutic innovation & regulatory science · 2026Article
- Analysis of Serious Breach Cases Reported in the EU Clinical Trials Information System: Quantitative and Qualitative Assessment.Therapeutic innovation & regulatory science · 2026Article
- Enhancing Data Quality in Clinical Trials: Cross-Company Validation of the Open-Source Clinical Trial Anomaly Spotter (CTAS).Therapeutic innovation & regulatory science · 2026Article
- Regional variation in clinical-trial risks: a large-scale analysis of 585 clinical trials.BMJ open · 2025Article
- Central statistical monitoring in clinical trial management: A scoping review.Clinical trials (London, England) · 2025Article
- SPIRIT 2025 explanation and elaboration: updated guideline for protocols of randomised trials.BMJ (Clinical research ed.) · 2025Article
- Biostatistical challenges in multicenter clinical trials: Best practices for collaboration and data harmonization across institutions.Bioinformation · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCentral monitoring aims at improving the quality of clinical research by pro-actively identifying risks and remediating emerging issues in the conduct of a clinical trial that may have an adverse impact on patient safety and/or the reliability of trial results. This paper, focusing on statistical data monitoring (SDM), is the second of a series that attempts to quantify the impact of central monitoring in clinical trials. MATERIAL AND
methodsQuality improvement was assessed in studies using SDM from a single large central monitoring platform. The analysis focused on a total of 1111 sites that were identified as at-risk by the SDM tests and for which the study teams conducted a follow-up investigation. These sites were taken from 159 studies conducted by 23 different clinical development organizations (including both sponsor companies and contract research organizations). Two quality improvement metrics were assessed for each selected site, one based on a site data inconsistency score (DIS, overall -log
resultsThe SDM quality metrics showed improvement in 83% (95% CI, 80-85%) of the sites across therapeutic areas and study phases (primarily phases 2 and 3). In contrast, only 56% (95% CI, 41-70%) of sites showed improvement in 2 historical studies that did not use SDM during study conduct.
conclusionThe results of this analysis provide clear quantitative evidence supporting the hypothesis that the use of SDM in central monitoring is leading to improved quality in clinical trial conduct and associated data across participating sites.
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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.