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  4. Comparison of cancer diagnosis recording between the Clinical Practice Research Datalink, Cancer Registry and Hospital Episodes Statistics
 
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Comparison of cancer diagnosis recording between the Clinical Practice Research Datalink, Cancer Registry and Hospital Episodes Statistics
File(s)
Difference in dates CPRD submitted full article Cancer Epidemiology accepted.docx (208.02 KB)
Accepted version
Author(s)
Arhi, Chanpreet S
Bottle, Alex
Burns, Elaine M
Clarke, Jonathan M
Aylin, Paul
more
Type
Journal Article
Abstract
Introduction

The Clinical Practice Research Datalink (CPRD) is a large electronic dataset of primary care medical records. For the purpose of epidemiological studies, it is necessary to ensure accuracy and completeness of cancer diagnoses in CPRD.
Method

Cases included had a colorectal, oesophagogastric (OG), breast, prostate or lung cancer diagnosis recorded in a least one of CPRD, Cancer Registry (CR) or Hospital Episodes Statistics(HES) between 2000 and 2013. Agreement in diagnosis between the datasets, difference in dates, survival at one and five-years, and whether patient characteristics differed according to the dataset or the timing of diagnosis were investigated.
Results

116,769 patients were included. For each cancer, approximately 10% of cases identified from CPRD or HES were not confirmed in the CR. 25.5% colorectal, 26.0% OG, 8.9% breast, 32.0% lung and 18.6% prostate cases identified from the CR were missing in CPRD. The diagnosis date was recorded later in CPRD compared with CR for each cancer, ranging from 81.1% for prostate to 59.6% for colorectal, especially if the diagnosis was an emergency. Compared with the CR and HES, the adjusted risk of a missing diagnosis in CPRD was significantly higher if the patient was older, had more co-morbidities or was diagnosed as an emergency. Survival at one and five-years was highest for CPRD.
Conclusion

Patient demographics and the route of diagnosis impact the accuracy of cancer diagnosis in CPRD. Although CPRD provides invaluable primary care data, patients should ideally be identified from the CR to reduce bias.
Date Issued
2018-12-01
Date Acceptance
2018-08-26
Citation
Cancer Epidemiology, 2018, 57, pp.148-157
URI
http://hdl.handle.net/10044/1/67166
DOI
https://www.dx.doi.org/10.1016/j.canep.2018.08.009
ISSN
0361-090X
Publisher
Elsevier
Start Page
148
End Page
157
Journal / Book Title
Cancer Epidemiology
Volume
57
Copyright Statement
© 2018 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/
Sponsor
Imperial College Healthcare NHS Trust
The Peter Sowerby Charitable Foundation
National Institute for Health Research
Dr Foster Intelligence
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000452018100022&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Grant Number
NRLS2
N/A
n/a
WPPA_P72388
Subjects
Science & Technology
Life Sciences & Biomedicine
Oncology
Public, Environmental & Occupational Health
Clinical practice research datalink
Cancer registry
Hospital episodes statistics
Accuracy of diagnosis
Survival
PRACTICE RESEARCH DATABASE
Publication Status
Published
Date Publish Online
2018-10-02
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