Imperial College London
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DrOlgaKostopoulou

Faculty of Medicine, Department of Surgery & Cancer

Reader in Medical Decision Making
 
 
 
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Contact

 

o.kostopoulou Website

 
 
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Location

 

5.07Medical SchoolSt Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Okoli:2018:10.1371/journal.pone.0207686,
author = {Okoli, GN and Kostopoulou, O and Delaney, BC},
doi = {10.1371/journal.pone.0207686},
journal = {PLoS ONE},
title = {Is symptom-based diagnosis of lung cancer possible? A systematic review and meta-analysis of symptomatic lung cancer prior to diagnosis for comparison with real-time data from routine general practice},
url = {http://dx.doi.org/10.1371/journal.pone.0207686},
volume = {13},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - BackgroundLung cancer is a good example of the potential benefit of symptom-based diagnosis, as it is the commonest cancer worldwide, with the highest mortality from late diagnosis and poor symptom recognition. The diagnosis and risk assessment tools currently available have been shown to require further validation. In this study, we determine the symptoms associated with lung cancer prior to diagnosis and demonstrate that by separating prior risk based on factors such as smoking history and age, from presenting symptoms and combining them at the individual patient level, we can make greater use of this knowledge to create a practical framework for the symptomatic diagnosis of individual patients presenting in primary care.AimTo provide an evidence-based analysis of symptoms observed in lung cancer patients prior to diagnosis.Design and settingSystematic review and meta-analysis of primary and secondary care data.MethodSeven databases were searched (MEDLINE, Embase, Cumulative Index to Nursing and Allied Health Literature, Health Management Information Consortium, Web of Science, British Nursing Index and Cochrane Library). Thirteen studies were selected based on predetermined eligibility and quality criteria for diagnostic assessment to establish the value of symptom-based diagnosis using diagnosistic odds ratio (DOR) and summary receiver operating characteristic (SROC) curve. In addition, routinely collated real-time data from primary care electronic health records (EHR), TransHis, was analysed to compare with our findings.ResultsHaemoptysis was found to have the greatest diagnostic value for lung cancer, diagnostic odds ratio (DOR) 6.39 (3.32–12.28), followed by dyspnoea 2.73 (1.54–4.85) then cough 2.64 (1.24–5.64) and lastly chest pain 2.02 (0.88–4.60). The use of symptom-based diagnosis to accurately diagnose lung cancer cases from non-cases was determined using the summary receiver operating characteristic (SROC) curve, the area under t
AU  - Okoli,GN
AU  - Kostopoulou,O
AU  - Delaney,BC
DO  - 10.1371/journal.pone.0207686
PY  - 2018///
SN  - 1932-6203
TI  - Is symptom-based diagnosis of lung cancer possible? A systematic review and meta-analysis of symptomatic lung cancer prior to diagnosis for comparison with real-time data from routine general practice
T2  - PLoS ONE
UR  - http://dx.doi.org/10.1371/journal.pone.0207686
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000451054800076&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - http://hdl.handle.net/10044/1/65409
VL  - 13
ER  -
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