Comparison of Two Prostate Cancer Risk Calculators that Include the Prostate Health Index

被引:24
|
作者
Roobol, Monique J. [1 ]
Vedder, Moniek M. [2 ]
Nieboer, Daan [2 ]
Houlgatte, Alain [3 ]
Vincendeau, Sebastien [4 ]
Lazzeri, Massimo [5 ]
Guazzoni, Giorgio [5 ]
Stephan, Carsten [6 ,7 ]
Semjonow, Axel [8 ]
Haese, Alexander [9 ]
Graefen, Markus [9 ]
Steyerberg, Ewout W. [2 ]
机构
[1] Erasmus MC, Dept Urol, POB 2040, NL-3000 CA Rotterdam, Netherlands
[2] Erasmus MC, Dept Publ Hlth, Rotterdam, Netherlands
[3] HIA Du Val De Grace, Dept Urol, Paris, France
[4] Hosp Pontchaillou, Dept Urol, Rennes, France
[5] San Raffaele Hosp Turro, Dept Urol, Milan, Italy
[6] Charite, Dept Urol, Berlin, Germany
[7] Berlin Inst Urol Res, Berlin, Germany
[8] Univ Hosp Munster, Dept Urol, Prostate Ctr, Munster, Germany
[9] Univ Hamburg Eppendorf, Martini Clin, Prostate Canc Ctr, Hamburg, Germany
来源
EUROPEAN UROLOGY FOCUS | 2015年 / 1卷 / 02期
关键词
-2] Pro-prostate-specific antigen; European Randomized Study of; Screening for Prostate Cancer; Lughezzani nomogram; Prostate biopsy; Prostate cancer; Prostate cancer risk calculator; Prostate Health Index; Validation;
D O I
10.1016/j.euf.2015.06.004
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Background: Risk prediction models for prostate cancer (PCa) have become important tools in reducing unnecessary prostate biopsies. The Prostate Health Index (PHI) may increase the predictive accuracy of such models. Objectives: To compare two PCa risk calculators (RCs) that include PHI. Design, setting, and participants: We evaluated the predictive performance of a previously developed PHI-based nomogram and updated versions of the European Randomized Study of Screening for Prostate Cancer (ERSPC) RCs based on digital rectal examination (DRE): RC3 (no prior biopsy) and RC4 (prior biopsy). For the ERSPC updates, the original RCs were recalibrated and PHI was added as a predictor. The PHI-updated ERSPC RCs were compared with the Lughezzani nomogram in 1185 men from four European sites. Outcomes were biopsy-detectable PC and potentially advanced or aggressive PCa, defined as clinical stage >T2b and/or a Gleason score >= 7 (clinically relevant PCa). Results and limitations: The PHI-updated ERSPC models had a combined area under the curve for the receiver operating characteristic (AUC) of 0.72 for all PCa and 0.68 for clinically relevant PCa. For the Lughezzani PHI-based nomogram, AUCs were 0.75 for all PCa and 0.69 for clinically relevant PCa. For men without a prior biopsy, PHI-updated RC3 resulted in AUCs of 0.73 for PCa and 0.66 for clinically relevant PCa. Decision curves confirmed these patterns, although the number of clinically relevant cancers was low. Conclusion: Differences between RCs that include PHI are small. Addition of PHI to an RC leads to further reductions in the rate of unnecessary biopsies when compared to a strategy based on prostate-specific antigen measurement. Patient summary: Risk prediction models for prostate cancer have become important tools in reducing unnecessary prostate biopsies. We compared two risk prediction models for prostate cancer that include the Prostate Health Index. We found that these models are equivalent to each other, and both perform better than the prostate-specific antigen test alone in predicting cancer. (C) 2015 European Association of Urology. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:185 / 190
页数:6
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