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A four-kallikrein panel for the prediction of repeat prostate biopsy: data from the European Randomized Study of Prostate Cancer Screening in Rotterdam, Netherlands

Gupta, A. ; Roobol, M. J. ; Savage, C. J. ; Peltola, M. ; Pettersson, K. ; Scardino, P. T. ; Vickers, A. J. ; Schroder, F. H. and Lilja, Hans LU orcid (2010) In British Journal of Cancer 103(5). p.708-714
Abstract
BACKGROUND: Most men with elevated levels of prostate-specific antigen (PSA) do not have prostate cancer, leading to a large number of unnecessary biopsies. A statistical model based on a panel of four kallikreins has been shown to predict the outcome of a first prostate biopsy. In this study, we apply the model to an independent data set of men with previous negative biopsy but persistently elevated PSA. METHODS: The study cohort consisted of 925 men with a previous negative prostate biopsy and elevated PSA (>= 3 ngml(-1)), with 110 prostate cancers detected (12%). A previously published statistical model was applied, with recalibration to reflect the lower positive biopsy rates on rebiopsy. RESULTS: The full-kallikrein panel had... (More)
BACKGROUND: Most men with elevated levels of prostate-specific antigen (PSA) do not have prostate cancer, leading to a large number of unnecessary biopsies. A statistical model based on a panel of four kallikreins has been shown to predict the outcome of a first prostate biopsy. In this study, we apply the model to an independent data set of men with previous negative biopsy but persistently elevated PSA. METHODS: The study cohort consisted of 925 men with a previous negative prostate biopsy and elevated PSA (>= 3 ngml(-1)), with 110 prostate cancers detected (12%). A previously published statistical model was applied, with recalibration to reflect the lower positive biopsy rates on rebiopsy. RESULTS: The full-kallikrein panel had higher discriminative accuracy than PSA and DRE alone, with area under the curve (AUC) improving from 0.58 (95% confidence interval (CI): 0.52, 0.64) to 0.68 (95% CI: 0.62, 0.74), P<0.001, and high-grade cancer (Gleason >= 7) at biopsy with AUC improving from 0.76 (95% CI: 0.64, 0.89) to 0.87 (95% CI: 0.81, 0.94), P 0.003). Application of the panel to 1000 men with persistently elevated PSA after initial negative biopsy, at a 15% risk threshold would reduce the number of biopsies by 712; would miss (or delay) the diagnosis of 53 cancers, of which only 3 would be Gleason 7 and the rest Gleason 6 or less. CONCLUSIONS: Our data constitute an external validation of a previously published model. The four-kallikrein panel predicts the result of repeat prostate biopsy in men with elevated PSA while dramatically decreasing unnecessary biopsies. British Journal of Cancer (2010) 103, 708-714. doi:10.1038/sj.bjc.6605815 www.bjcancer.com Published online 27 July 2010 (C) 2010 Cancer Research UK (Less)
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author
; ; ; ; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
cancer screening, prostate-specific antigen, predictive value of tests, prostate cancer, biomarkers
in
British Journal of Cancer
volume
103
issue
5
pages
708 - 714
publisher
Nature Publishing Group
external identifiers
  • wos:000281287700016
  • scopus:77955981143
ISSN
1532-1827
DOI
10.1038/sj.bjc.6605815
language
English
LU publication?
yes
id
19322a95-6cc2-423f-b435-deffe6eaf483 (old id 1673384)
date added to LUP
2016-04-01 10:14:35
date last changed
2022-01-25 21:16:40
@article{19322a95-6cc2-423f-b435-deffe6eaf483,
  abstract     = {{BACKGROUND: Most men with elevated levels of prostate-specific antigen (PSA) do not have prostate cancer, leading to a large number of unnecessary biopsies. A statistical model based on a panel of four kallikreins has been shown to predict the outcome of a first prostate biopsy. In this study, we apply the model to an independent data set of men with previous negative biopsy but persistently elevated PSA. METHODS: The study cohort consisted of 925 men with a previous negative prostate biopsy and elevated PSA (&gt;= 3 ngml(-1)), with 110 prostate cancers detected (12%). A previously published statistical model was applied, with recalibration to reflect the lower positive biopsy rates on rebiopsy. RESULTS: The full-kallikrein panel had higher discriminative accuracy than PSA and DRE alone, with area under the curve (AUC) improving from 0.58 (95% confidence interval (CI): 0.52, 0.64) to 0.68 (95% CI: 0.62, 0.74), P&lt;0.001, and high-grade cancer (Gleason &gt;= 7) at biopsy with AUC improving from 0.76 (95% CI: 0.64, 0.89) to 0.87 (95% CI: 0.81, 0.94), P 0.003). Application of the panel to 1000 men with persistently elevated PSA after initial negative biopsy, at a 15% risk threshold would reduce the number of biopsies by 712; would miss (or delay) the diagnosis of 53 cancers, of which only 3 would be Gleason 7 and the rest Gleason 6 or less. CONCLUSIONS: Our data constitute an external validation of a previously published model. The four-kallikrein panel predicts the result of repeat prostate biopsy in men with elevated PSA while dramatically decreasing unnecessary biopsies. British Journal of Cancer (2010) 103, 708-714. doi:10.1038/sj.bjc.6605815 www.bjcancer.com Published online 27 July 2010 (C) 2010 Cancer Research UK}},
  author       = {{Gupta, A. and Roobol, M. J. and Savage, C. J. and Peltola, M. and Pettersson, K. and Scardino, P. T. and Vickers, A. J. and Schroder, F. H. and Lilja, Hans}},
  issn         = {{1532-1827}},
  keywords     = {{cancer screening; prostate-specific antigen; predictive value of tests; prostate cancer; biomarkers}},
  language     = {{eng}},
  number       = {{5}},
  pages        = {{708--714}},
  publisher    = {{Nature Publishing Group}},
  series       = {{British Journal of Cancer}},
  title        = {{A four-kallikrein panel for the prediction of repeat prostate biopsy: data from the European Randomized Study of Prostate Cancer Screening in Rotterdam, Netherlands}},
  url          = {{http://dx.doi.org/10.1038/sj.bjc.6605815}},
  doi          = {{10.1038/sj.bjc.6605815}},
  volume       = {{103}},
  year         = {{2010}},
}