Evidence map›Paper›PMID 39720844›Full record

ArticleClinical trials (London, England)2025

An open-source SQL database schema for integrated clinical and translational data management in clinical trials.

Umar Niazi, Charlotte Stuart, Patricia Soares, Vincent Foure, Gareth Griffiths

Abstract read
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. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Umar NiaziCancer Research UK Southampton Clinical Trials Unit, MP131, Southampton General Hospital, University of Southampton, Southampton, UK.ORCID 0000-0001-7176-8883
Charlotte StuartCancer Research UK Southampton Clinical Trials Unit, MP131, Southampton General Hospital, University of Southampton, Southampton, UK.
Patricia SoaresiSolutions, University of Southampton, Southampton, UK.
Vincent FoureiSolutions, University of Southampton, Southampton, UK.
Gareth GriffithsCancer Research UK Southampton Clinical Trials Unit, MP131, Southampton General Hospital, University of Southampton, Southampton, UK.

Funding

Cancer Research UK CTUQQR-DEC22/100008
6 · The paper itself

Abstract

Unlocking the power of personalised medicine in oncology hinges on the integration of clinical trial data with translational data (i.e. biospecimen-derived molecular information). This combined analysis allows researchers to tailor treatments to a patient's unique biological makeup. However, current practices within UK Clinical Trials Units present challenges. While clinical data are held in standardised formats, translational data are complex, diverse, and requires specialised storage. This disparity in format creates significant hurdles for researchers aiming to curate, integrate and analyse these datasets effectively. This article proposes a novel solution: an open-source SQL database schema designed specifically for the needs of academic trial units. Inspired by Cancer Research UK's commitment to open data sharing and exemplified by the Southampton Clinical Trials Unit's CONFIRM trial (with over 150,000 clinical data points), this schema offers a cost-effective and practical 'middle ground' between raw data and expensive Secure Data Environments/Trusted Research Environments. By acting as a central hub for both clinical and translational data, the schema facilitates seamless data sharing and analysis. Researchers gain a holistic view of trials, enabling exploration of connections between clinical observations and the molecular underpinnings of treatment response. Detailed instructions for setting up the database are provided. The open-source nature and straightforward design ensure ease of implementation and affordability, while robust security measures safeguard sensitive data. We further showcase how researchers can leverage popular statistical software like R to directly query the database. This approach fosters collaboration within the academic discovery community, ultimately accelerating progress towards personalised cancer therapies.

Indexed as

Clinical Trials as TopicDatabase Management SystemsDatabases, FactualData ManagementTranslational Research, BiomedicalHumansInformation DisseminationPrecision MedicineUnited Kingdomclinical trial data integration with translational dataOpen-source SQL database schema for clinical trialspersonalised medicine in clinical research

Identifiers

PMID39720844
PMCPMC12092935

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LicenceCC BY
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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.