Evidence map›Paper›PMID 39744904›Full record

ArticleClinical trials (London, England)2025

Central statistical monitoring in clinical trial management: A scoping review.

Maciej Fronc, Michał Jakubczyk, Sharon B Love, Susan Talbot, Timothy Rolfe

Abstract readScoping Review
In one paragraph

Article in Clinical trials (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Maciej FroncDecision Analysis and Support Unit, Institute of Econometrics, SGH Warsaw School of Economics, Warsaw, Poland.ORCID 0000-0002-4874-950X
Michał JakubczykDecision Analysis and Support Unit, Institute of Econometrics, SGH Warsaw School of Economics, Warsaw, Poland.ORCID 0000-0002-0006-6769
Sharon B LoveMRC Clinical Trials Unit at UCL, University College London, London, UK.ORCID 0000-0002-6695-5390
Susan TalbotBiostatistics, Amgen, Thousand Oaks, CA, USA.ORCID 0000-0002-7713-2226
Timothy RolfeCentral Monitoring and Data Analytics, GSK, Brentford, UK.ORCID 0000-0001-8798-840X

Funding

Medical Research Council MC_UU_00004/08
6 · The paper itself

Abstract

backgroundClinical trials handle a huge amount of data which can be used during the trial to improve the ongoing study conduct. It is suggested by regulators to implement the remote approach to evaluate clinical trials by analysing collected data. Central statistical monitoring helps to achieve that by employing quantitative methods, the results of which are a basis for decision-making on quality issues.

methodsThis article presents a scoping review which is based on a systematic and iterative approach to identify and synthesise literature on central statistical monitoring methodology. In particular, we investigated the decision-making processes (with emphasis on quality issues) of central statistical monitoring methodology and its place in the clinical trial workflow. We reviewed papers published over the last 10 years in two databases (Scopus and Web of Science) with a focus on data mining algorithms of central statistical monitoring and its benefit to the quality of trials.

resultsAs a result, 24 scientific papers were selected for this review, and they consider central statistical monitoring at two levels. First, the perspective of the central statistical monitoring process and its location in the study conduct in terms of quality issues. Second, central statistical monitoring methods categorised into practices applied in the industry, and innovative methods in development. The established methods are discussed through the prism of categories of their usage. In turn, the innovations refer to either research on new methods or extensions to existing ones. DISCUSSION: Our review suggests directions for further research into central statistical monitoring methodology - including increased application of multivariate analysis and using advanced distance metrics - and guidance on how central statistical monitoring operates in response to regulators' requirements.

Indexed as

Clinical Trials as TopicResearch DesignData Interpretation, StatisticalData MiningDecision MakingHumanscentral monitoringcentral statistical monitoringClinical trialsdata-driven approachquality by designrisk-based monitoringrisk-based quality management

Identifiers

PMID39744904
PMCPMC7617700

What OpenQuestion holds

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Registered trials

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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.