Evidence map›Paper›PMID 32711460›Full record

Trial reportBMC medical research methodology2020

Linkage of the CHHiP randomised controlled trial with primary care data: a study investigating ways of supplementing cancer trials and improving evidence-based practice.

Agnieszka Lemanska, Rachel C Byford, Clare Cruickshank, David P Dearnaley, Filipa Ferreira, Clare Griffin, Emma Hall, William Hinton, Simon de Lusignan, Julian Sherlock and 1 more

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in BMC medical research methodology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. 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

11 authors.

Agnieszka LemanskaSchool of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, GU2 7XH, UK. a.lemanska@surrey.ac.uk.ORCID 0000-0003-4849-2430
Rachel C ByfordNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Clare CruickshankClinical Trials and Statistics Unit, The Institute of Cancer Research, London, UK.
David P DearnaleyThe Institute of Cancer Research and Royal Marsden NHS Trust, London, UK.
Filipa FerreiraNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Clare GriffinClinical Trials and Statistics Unit, The Institute of Cancer Research, London, UK.
Emma HallClinical Trials and Statistics Unit, The Institute of Cancer Research, London, UK.
William HintonNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Simon de LusignanNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Julian SherlockNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Sara FaithfullSchool of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, GU2 7XH, UK.

Funding

Cancer Research UK 10588Cancer Research UK 12518Cancer Research UK 19727Cancer Research UK 28284Cancer Research UK 7253
6 · The paper itself

Abstract

backgroundRandomised controlled trials (RCTs) are the gold standard for evidence-based practice. However, RCTs can have limitations. For example, translation of findings into practice can be limited by design features, such as inclusion criteria, not accurately reflecting clinical populations. In addition, it is expensive to recruit and follow-up participants in RCTs. Linkage with routinely collected data could offer a cost-effective way to enhance the conduct and generalisability of RCTs. The aim of this study is to investigate how primary care data can support RCTs.

methodsSecondary analysis following linkage of two datasets: 1) multicentre CHHiP radiotherapy trial (ISRCTN97182923) and 2) primary care database from the Royal College of General Practitioners Research and Surveillance Centre. Comorbidities and medications recorded in CHHiP at baseline, and radiotherapy-related toxicity recorded in CHHiP over time were compared with primary care records. The association of comorbidities and medications with toxicity was analysed with mixed-effects logistic regression.

resultsPrimary care records were extracted for 106 out of 2811 CHHiP participants recruited from sites in England (median age 70, range 44 to 82). Complementary information included longitudinal body mass index, blood pressure and cholesterol, as well as baseline smoking and alcohol usage but was limited by the considerable missing data. In the linked sample, 9 (8%) participants were recorded in CHHiP as having a history of diabetes and 38 (36%) hypertension, whereas primary care records indicated incidence prior to trial entry of 11 (10%) and 40 (38%) respectively. Concomitant medications were not collected in CHHiP but available in primary care records. This indicated that 44 (41.5%) men took aspirin, 65 (61.3%) statins, 14 (13.2%) metformin and 46 (43.4%) phosphodiesterase-5-inhibitors at some point before or after trial entry.

conclusionsWe provide a set of recommendations on linkage and supplementation of trials. Data recorded in primary care are a rich resource and linkage could provide near real-time information to supplement trials and an efficient and cost-effective mechanism for long-term follow-up. In addition, standardised primary care data extracts could form part of RCT recruitment and conduct. However, this is at present limited by the variable quality and fragmentation of primary care data.

Indexed as

MetforminNeoplasmsAgedEnglandEvidence-Based PracticeHumansMalePrimary Health CareMetforminData linkageElectronic health recordsPrimary careRandomised controlled trial

Identifiers

PMID32711460
PMCPMC7382082

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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.