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


Journal

Contemporary clinical trials
ISSN: 1559-2030
Titre abrégé: Contemp Clin Trials
Pays: United States
ID NLM: 101242342

Informations de publication

Date de publication:
05 2023
Historique:
received: 18 11 2022
revised: 03 03 2023
accepted: 14 03 2023
medline: 8 5 2023
pubmed: 19 3 2023
entrez: 18 3 2023
Statut: ppublish

Résumé

Routinely-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. Protocol-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. From 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. Concordance 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.

Sections du résumé

BACKGROUND
Routinely-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.
METHODS
Protocol-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.
RESULTS
From 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.
CONCLUSION
Concordance 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.

Identifiants

pubmed: 36933612
pii: S1551-7144(23)00085-X
doi: 10.1016/j.cct.2023.107162
pii:
doi:

Types de publication

Comparative Study Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

107162

Informations de copyright

Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Archie Macnair (A)

MRC 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 Nankivell (M)

MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, 90 High Holborn, London WC1V 6LJ, UK.

Macey L Murray (ML)

MRC 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 Rosen (SD)

National Heart and Lung Institute, Imperial College, London, UK.

Sally Appleyard (S)

University Hospitals Sussex NHS Foundation Trust, Royal Sussex County Hospital, Eastern Road, Brighton BN2 5BE, UK.

Matthew R Sydes (MR)

MRC 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 Forcat (S)

MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, 90 High Holborn, London WC1V 6LJ, UK.

Andrew Welland (A)

MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, 90 High Holborn, London WC1V 6LJ, UK.

Noel W Clarke (NW)

The Christie and Salford Royal Hospitals, Manchester, UK.

Stephen Mangar (S)

Charing Cross Hospital, Imperial College Healthcare NHS Trust, London, UK.

Howard Kynaston (H)

Division of Cancer and Genetics, Cardiff University Medical School, Cardiff, UK.

Roger Kockelbergh (R)

Department of Urology, University Hospitals of Leicester, Leicester, UK.

Abdulla Al-Hasso (A)

Beatson West of Scotland Cancer Centre, Glasgow, UK.

John Deighan (J)

Patient representative, MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, 90 High Holborn, London WC1V 6LJ, UK.

John Marshall (J)

Patient representative, MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, 90 High Holborn, London WC1V 6LJ, UK.

Mahesh Parmar (M)

MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, 90 High Holborn, London WC1V 6LJ, UK.

Ruth E Langley (RE)

MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, 90 High Holborn, London WC1V 6LJ, UK.

Duncan C Gilbert (DC)

MRC 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.

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Classifications MeSH