Imperial College London
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DrHarryWhitwell

Faculty of Medicine, Department of Metabolism, Digestion and Reproduction

Lecturer in Proteomics and Integrative Data Analysis Proteom
 
 
 
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Location

 

312Burlington DanesHammersmith Campus

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Summary

 

Publications

Citation

BibTex format

@article{Whitwell:2020:10.1038/s41416-019-0718-9,
author = {Whitwell, HJ and Worthington, J and Blyuss, O and Gentry-Maharaj, A and Ryan, A and Gunu, R and Kalsi, J and Menon, U and Jacobs, I and Zaikin, A and Timms, JF},
doi = {10.1038/s41416-019-0718-9},
journal = {British Journal of Cancer},
pages = {847--856},
title = {Improved early detection of ovarian cancer using longitudinal multimarker models},
url = {http://dx.doi.org/10.1038/s41416-019-0718-9},
volume = {122},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - BackgroundOvarian cancer has a poor survival rate due to late diagnosis and improved methods are needed for its early detection. Our primary objective was to identify and incorporate additional biomarkers into longitudinal models to improve on the performance of CA125 as a first-line screening test for ovarian cancer.MethodsThis case–control study nested within UKCTOCS used 490 serial serum samples from 49 women later diagnosed with ovarian cancer and 31 control women who were cancer-free. Proteomics-based biomarker discovery was carried out using pooled samples and selected candidates, including those from the literature, assayed in all serial samples. Multimarker longitudinal models were derived and tested against CA125 for early detection of ovarian cancer.ResultsThe best performing models, incorporating CA125, HE4, CHI3L1, PEBP4 and/or AGR2, provided 85.7% sensitivity at 95.4% specificity up to 1 year before diagnosis, significantly improving on CA125 alone. For Type II cases (mostly high-grade serous), models achieved 95.5% sensitivity at 95.4% specificity. Predictive values were elevated earlier than CA125, showing the potential of models to improve lead time.ConclusionsWe have identified candidate biomarkers and tested longitudinal multimarker models that significantly improve on CA125 for early detection of ovarian cancer. These models now warrant independent validation.
AU  - Whitwell,HJ
AU  - Worthington,J
AU  - Blyuss,O
AU  - Gentry-Maharaj,A
AU  - Ryan,A
AU  - Gunu,R
AU  - Kalsi,J
AU  - Menon,U
AU  - Jacobs,I
AU  - Zaikin,A
AU  - Timms,JF
DO  - 10.1038/s41416-019-0718-9
EP  - 856
PY  - 2020///
SN  - 0007-0920
SP  - 847
TI  - Improved early detection of ovarian cancer using longitudinal multimarker models
T2  - British Journal of Cancer
UR  - http://dx.doi.org/10.1038/s41416-019-0718-9
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000508172100004&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://www.nature.com/articles/s41416-019-0718-9
UR  - http://hdl.handle.net/10044/1/91321
VL  - 122
ER  -
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