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A Four-Kallikrein Panel Predicts Prostate Cancer in Men with Recent Screening: Data from the European Randomized Study of Screening for Prostate Cancer, Rotterdam

Vickers, Andrew J.; Cronin, Angel M.; Roobol, Monique J.; Savage, Caroline J.; Peltola, Mari; Pettersson, Kim; Scardino, Peter T.; Schroeder, Fritz H. and Lilja, Hans LU (2010) In Clinical Cancer Research 16(12). p.3232-3239
Abstract
Purpose: We have developed a statistical prediction model for prostate cancer based on four kallikrein markers in blood: total, free, and intact prostate-specific antigen ( PSA), and kallikrein-related peptidase 2 ( hK2). Although this model accurately predicts the result of biopsy in unscreened men, its properties for men with a history of PSA screening have not been fully characterized. Experimental Design: A total of 1,501 previously screened men with elevated PSA underwent initial biopsy during rounds 2 and 3 of the European Randomized Study of Screening for Prostate Cancer, Rotterdam, with 388 cancers diagnosed. Biomarker levels were measured in serum samples taken before biopsy. The prediction model developed on the unscreened cohort... (More)
Purpose: We have developed a statistical prediction model for prostate cancer based on four kallikrein markers in blood: total, free, and intact prostate-specific antigen ( PSA), and kallikrein-related peptidase 2 ( hK2). Although this model accurately predicts the result of biopsy in unscreened men, its properties for men with a history of PSA screening have not been fully characterized. Experimental Design: A total of 1,501 previously screened men with elevated PSA underwent initial biopsy during rounds 2 and 3 of the European Randomized Study of Screening for Prostate Cancer, Rotterdam, with 388 cancers diagnosed. Biomarker levels were measured in serum samples taken before biopsy. The prediction model developed on the unscreened cohort was then applied and predictions compared with biopsy outcome. Results: The previously developed four-kallikrein prediction model had much higher predictive accuracy than PSA and age alone ( area under the curve of 0.711 versus 0.585, and 0.713 versus 0.557 with and without digital rectal exam, respectively; both P < 0.001). Similar statistically significant enhancements were seen for high-grade cancer. Applying the model with a cutoff of 20% cancer risk as the criterion for biopsy would reduce the biopsy rate by 362 for every 1,000 men with elevated PSA. Although diagnosis would be delayed for 47 cancers, these would be predominately low-stage and low-grade ( 83% Gleason 6 T-1c). Conclusions: A panel of four kallikreins can help predict the result of initial biopsy in previously screened men with elevated PSA. Use of a statistical model based on the panel would substantially decrease rates of unnecessary biopsy. Clin Cancer Res; 16( 12); 3232-9. (C)2010 AACR. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Clinical Cancer Research
volume
16
issue
12
pages
3232 - 3239
publisher
American Association for Cancer Research
external identifiers
  • wos:000278749400018
  • scopus:77953715079
ISSN
1078-0432
DOI
10.1158/1078-0432.CCR-10-0122
language
English
LU publication?
yes
id
5a2f51eb-8bd9-4312-9f7b-19c73f7708c8 (old id 1631488)
date added to LUP
2010-07-22 13:48:28
date last changed
2018-05-29 11:15:33
@article{5a2f51eb-8bd9-4312-9f7b-19c73f7708c8,
  abstract     = {Purpose: We have developed a statistical prediction model for prostate cancer based on four kallikrein markers in blood: total, free, and intact prostate-specific antigen ( PSA), and kallikrein-related peptidase 2 ( hK2). Although this model accurately predicts the result of biopsy in unscreened men, its properties for men with a history of PSA screening have not been fully characterized. Experimental Design: A total of 1,501 previously screened men with elevated PSA underwent initial biopsy during rounds 2 and 3 of the European Randomized Study of Screening for Prostate Cancer, Rotterdam, with 388 cancers diagnosed. Biomarker levels were measured in serum samples taken before biopsy. The prediction model developed on the unscreened cohort was then applied and predictions compared with biopsy outcome. Results: The previously developed four-kallikrein prediction model had much higher predictive accuracy than PSA and age alone ( area under the curve of 0.711 versus 0.585, and 0.713 versus 0.557 with and without digital rectal exam, respectively; both P &lt; 0.001). Similar statistically significant enhancements were seen for high-grade cancer. Applying the model with a cutoff of 20% cancer risk as the criterion for biopsy would reduce the biopsy rate by 362 for every 1,000 men with elevated PSA. Although diagnosis would be delayed for 47 cancers, these would be predominately low-stage and low-grade ( 83% Gleason 6 T-1c). Conclusions: A panel of four kallikreins can help predict the result of initial biopsy in previously screened men with elevated PSA. Use of a statistical model based on the panel would substantially decrease rates of unnecessary biopsy. Clin Cancer Res; 16( 12); 3232-9. (C)2010 AACR.},
  author       = {Vickers, Andrew J. and Cronin, Angel M. and Roobol, Monique J. and Savage, Caroline J. and Peltola, Mari and Pettersson, Kim and Scardino, Peter T. and Schroeder, Fritz H. and Lilja, Hans},
  issn         = {1078-0432},
  language     = {eng},
  number       = {12},
  pages        = {3232--3239},
  publisher    = {American Association for Cancer Research},
  series       = {Clinical Cancer Research},
  title        = {A Four-Kallikrein Panel Predicts Prostate Cancer in Men with Recent Screening: Data from the European Randomized Study of Screening for Prostate Cancer, Rotterdam},
  url          = {http://dx.doi.org/10.1158/1078-0432.CCR-10-0122},
  volume       = {16},
  year         = {2010},
}