Evidence map›Paper›PMID 36933612›Full record

ArticleContemporary clinical trials2023

Healthcare systems data in the context of clinical trials - A comparison of cardiovascular data from a clinical trial dataset with routinely collected data.

Archie Macnair, Matthew Nankivell, Macey L Murray, Stuart D Rosen, Sally Appleyard, Matthew R Sydes, Sylvia Forcat, Andrew Welland, Noel W Clarke, Stephen Mangar and 8 more

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Contemporary clinical trials, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Trial
  2. Review
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

18 authors.

Archie MacnairMRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, 90 High Holborn, London WC1V 6LJ, UK; Health Data Research, UK; Guys and St Thomas' NHS Foundation Trust, London, UK.
Matthew NankivellMRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, 90 High Holborn, London WC1V 6LJ, UK.
Macey L MurrayMRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, 90 High Holborn, London WC1V 6LJ, UK; Health Data Research, UK; NHS DigiTrials, NHS Digital, 7 and 8 Wellington Place, Leeds, West Yorkshire LS1 4AP, UK.
Stuart D RosenNational Heart and Lung Institute, Imperial College, London, UK.
Sally AppleyardUniversity Hospitals Sussex NHS Foundation Trust, Royal Sussex County Hospital, Eastern Road, Brighton BN2 5BE, UK.
Matthew R SydesMRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, 90 High Holborn, London WC1V 6LJ, UK; Health Data Research, UK; BHF Data Science Centre, Health Data Research UK (Central Office), Gibbs Building, 215 Euston Road, London NW1 2BE, UK.
Sylvia ForcatMRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, 90 High Holborn, London WC1V 6LJ, UK.
Andrew WellandMRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, 90 High Holborn, London WC1V 6LJ, UK.
Noel W ClarkeThe Christie and Salford Royal Hospitals, Manchester, UK.
Stephen MangarCharing Cross Hospital, Imperial College Healthcare NHS Trust, London, UK.
Howard KynastonDivision of Cancer and Genetics, Cardiff University Medical School, Cardiff, UK.
Roger KockelberghDepartment of Urology, University Hospitals of Leicester, Leicester, UK.
Abdulla Al-HassoBeatson West of Scotland Cancer Centre, Glasgow, UK.
John DeighanPatient representative, MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, 90 High Holborn, London WC1V 6LJ, UK.
John MarshallPatient representative, MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, 90 High Holborn, London WC1V 6LJ, UK.
Mahesh ParmarMRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, 90 High Holborn, London WC1V 6LJ, UK.
Ruth E LangleyMRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, 90 High Holborn, London WC1V 6LJ, UK.
Duncan C GilbertMRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, 90 High Holborn, London WC1V 6LJ, UK; University Hospitals Sussex NHS Foundation Trust, Royal Sussex County Hospital, Eastern Road, Brighton BN2 5BE, UK. Electronic address: duncan.gilbert@ucl.ac.uk.

Funding

Cancer Research UK 12443Medical Research Council MC_UU_00004/02
6 · The paper itself

Abstract

backgroundRoutinely-collected healthcare systems data (HSD) are proposed to improve the efficiency of clinical trials. A comparison was undertaken between cardiovascular (CVS) data from a clinical trial database with two HSD resources.

methodsProtocol-defined and clinically reviewed CVS events (heart failure (HF), acute coronary syndrome (ACS), thromboembolic stroke, venous and arterial thromboembolism) were identified within the trial data. Data (using pre-specified codes) was obtained from NHS Hospital Episode Statistics (HES) and National Institute for Cardiovascular Outcomes Research (NICOR) HF and myocardial ischaemia audits for trial participants recruited in England between 2010 and 2018 who had provided consent. The primary comparison was trial data versus HES inpatient (APC) main diagnosis (Box-1). Correlations are presented with descriptive statistics and Venn diagrams. Reasons for non-correlation were explored.

resultsFrom 1200 eligible participants, 71 protocol-defined clinically reviewed CVS events were recorded in the trial database. 45 resulted in a hospital admission and therefore could have been recorded by either HES APC/ NICOR. Of these, 27/45 (60%) were recorded by HES inpatient (Box-1) with an additional 30 potential events also identified. HF and ACS were potentially recorded in all 3 datasets; trial data recorded 18, HES APC 29 and NICOR 24 events respectively. 12/18 (67%) of the HF/ACS events in the trial dataset were recorded by NICOR.

conclusionConcordance between datasets was lower than anticipated and the HSD used could not straightforwardly replace current trial practices, nor directly identify protocol-defined CVS events. Further work is required to improve the quality of HSD and consider event definitions when designing clinical trials incorporating HSD.

Indexed as

Acute Coronary SyndromeCoronary Artery DiseaseHeart FailureDelivery of Health CareHumansRoutinely Collected Health DataCardiovascular diseaseClinical trialsHealthcare systems dataProstate cancer

Identifiers

PMID36933612
PMCPMC7617340

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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.