Evidence map›Paper›PMID 38549510›Full record

ArticleJournal of biopharmaceutical statistics2024

FDA experiences with a centralized statistical monitoring tool.

Xiaofeng Tina Wang, Paul Schuette, Matilde Kam

Erratum issuedAbstract read
PubMed Publisher
In one paragraph

Article in Journal of biopharmaceutical statistics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Xiaofeng Tina WangFDA/CDER/OTS/OB/DAI (Food and Drug Administration, Center for Drug Evaluation and Research, Office of Translational Sciences, Office of Biostatistics, Division of Analytics and Informatics), Silver Spring, Maryland, United States.
Paul SchuetteFDA/CDER/OTS/OB/DAI (Food and Drug Administration, Center for Drug Evaluation and Research, Office of Translational Sciences, Office of Biostatistics, Division of Analytics and Informatics), Silver Spring, Maryland, United States.
Matilde KamFDA/CDER/OTS/OB/DAI (Food and Drug Administration, Center for Drug Evaluation and Research, Office of Translational Sciences, Office of Biostatistics, Division of Analytics and Informatics), Silver Spring, Maryland, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The U.S. Food and Drug Administration (FDA) has broadly supported quality by design initiatives for clinical trials - including monitoring and data validation - by releasing two related guidance documents (FDA 2013 and 2019). Centralized statistical monitoring (CSM) can be a component of a quality by design process. In this article, we describe our experience with a CSM platform as part of a Cooperative Research and Development Agreement between CluePoints and FDA. This agreement's approach to CSM is based on many statistical tests performed on all relevant subject-level data submitted to identify outlying sites. An overall data inconsistency score is calculated to assess the inconsistency of data from one site compared to data from all sites. Sites are ranked by the data inconsistency score (

Indexed as

Data Interpretation, StatisticalSoftwareUnited States Food and Drug AdministrationClinical Trials as TopicClinical Trials Data Monitoring CommitteesFemaleHumansMalePharmacologyUnited StatesCentralized statistical monitoringclinical investigator site selectiondata anomaliesdata quality/integrityerror detection

Identifiers

PMID38549510

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.