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Prospective multicenter evaluation of the Beckman Coulter Prostate Health Index using WHO calibration.

ABSTRACT: Reported prostate specific antigen values may differ substantially among assays using Hybritech® or WHO standardization. The Beckman Coulter® Prostate Health Index and [-2]proPSA are newly approved serum markers associated with prostate cancer risk and aggressiveness. We studied the influence of assay standardization on these markers.Prostate specific antigen, percent free prostate specific antigen and [-2]proPSA were measured using Hybritech calibration in 892 men from a prospective, multicenter study undergoing prostate biopsy. We calculated the Prostate Health Index using the equation, ([-2]proPSA/free prostate specific antigen) × PSA. Index performance characteristics for prostate cancer detection were then determined using recalculated WHO calibration prostate specific antigen values.The median Prostate Health Index was significantly higher in men with prostate cancer than in those with negative biopsies using WHO values (47.4 vs 39.8, p <0.001). The index offered improved discrimination of prostate cancer detection on biopsy (AUC 0.704) compared to percent free or total prostate specific antigen using the WHO calibration.The Prostate Health Index can be calculated using Hybritech or WHO standardized assays. It significantly improved prediction of the biopsy outcome over that of percent free or prostate specific antigen alone.

SUBMITTER: Loeb S

PROVIDER: S-EPMC4273580 | biostudies-other | 2013 May

REPOSITORIES: biostudies-other

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Prospective multicenter evaluation of the Beckman Coulter Prostate Health Index using WHO calibration.

Loeb Stacy S Sokoll Lori J LJ Broyles Dennis L DL Bangma Chris H CH van Schaik Ron H N RH Klee George G GG Wei John T JT Sanda Martin G MG Partin Alan W AW Slawin Kevin M KM Marks Leonard S LS Mizrahi Isaac A IA Shin Sanghyuk S SS Cruz Amabelle B AB Chan Daniel W DW Roberts William L WL Catalona William J WJ

The Journal of urology 20121130 5

<h4>Purpose</h4>Reported prostate specific antigen values may differ substantially among assays using Hybritech® or WHO standardization. The Beckman Coulter® Prostate Health Index and [-2]proPSA are newly approved serum markers associated with prostate cancer risk and aggressiveness. We studied the influence of assay standardization on these markers.<h4>Materials and methods</h4>Prostate specific antigen, percent free prostate specific antigen and [-2]proPSA were measured using Hybritech calibra ...[more]

PMID: 23206426

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Project description:BackgroundWe aimed to evaluate the usefulness of the Beckman Coulter prostate health index (PHI) and to compare it with total prostate-specific antigen (PSA) levels and related derivatives in predicting the presence and aggressiveness of prostate cancer (PCa) in the Korean population.MethodsA total of 140 men who underwent their first prostate biopsy for suspected PCa were included in this prospective observational study. The diagnostic performance of total PSA, free PSA, %free PSA, [-2] proPSA (p2PSA), %p2PSA, and PHI in detecting and predicting the aggressiveness of PCa was estimated using the receiver operating characteristic curve (ROC) and logistic multivariate regression analyses.ResultsOf 140 patients, PCa was detected in 63 (45%) of participants, and 48 (76.2%) of them had significant cancer with a Gleason score (GS) ≥ 7. In the whole group, the area under the curve (AUC) for ROC analysis of tPSA, free PSA, %fPSA, p2PSA, %p2PSA, and PHI were 0.63, 0.57, 0.69, 0.69, 0.72, and 0.76, respectively, and the AUC was significantly greater in the PHI group than in the tPSA group (p = 0.005). For PCa with GS ≥ 7, the AUCs for tPSA, free PSA, %fPSA, p2PSA, %p2PSA, and PHI were 0.62, 0.58, 0.41, 0.79, 0.86, and 0.87, respectively, and the AUC was significantly greater in the PHI group than in the tPSA group (p < 0.001). In the subgroup with tPSA 4-10 ng/mL, both %p2PSA and PHI were strong independent predictors for PCa (p = 0.007, p = 0.006) and significantly improved the predictive accuracy of a base multivariable model, including age, tPSA, fPSA and %fPSA, using multivariate logistic regression analysis. (p = 0.054, p = 0.048). Additionally, at a cutoff PHI value > 33.4, 22.9% (32/140) of biopsies could be avoided without missing any cases of aggressive cancer.ConclusionsThis study shows that %p2PSA and PHI are superior to total PSA and %fPSA in predicting the presence and aggressiveness (GS ≥ 7) of PCa among Korean men. Using PHI, a significant proportion of unnecessary biopsies can be avoided.

Project description:BackgroundAssessing calibration-the agreement between estimated risk and observed proportions-is an important component of deriving and validating clinical prediction models. Methods for assessing the calibration of prognostic models for use with competing risk data have received little attention.MethodsWe propose a method for graphically assessing the calibration of competing risk regression models. Our proposed method can be used to assess the calibration of any model for estimating incidence in the presence of competing risk (e.g., a Fine-Gray subdistribution hazard model; a combination of cause-specific hazard functions; or a random survival forest). Our method is based on using the Fine-Gray subdistribution hazard model to regress the cumulative incidence function of the cause-specific outcome of interest on the predicted outcome risk of the model whose calibration we want to assess. We provide modifications of the integrated calibration index (ICI), of E50 and of E90, which are numerical calibration metrics, for use with competing risk data. We conducted a series of Monte Carlo simulations to evaluate the performance of these calibration measures when the underlying model has been correctly specified and when the model was mis-specified and when the incidence of the cause-specific outcome differed between the derivation and validation samples. We illustrated the usefulness of calibration curves and the numerical calibration metrics by comparing the calibration of a Fine-Gray subdistribution hazards regression model with that of random survival forests for predicting cardiovascular mortality in patients hospitalized with heart failure.ResultsThe simulations indicated that the method for constructing graphical calibration curves and the associated calibration metrics performed as desired. We also demonstrated that the numerical calibration metrics can be used as optimization criteria when tuning machine learning methods for competing risk outcomes.ConclusionsThe calibration curves and numeric calibration metrics permit a comprehensive comparison of the calibration of different competing risk models.

Dataset Information

Prospective multicenter evaluation of the Beckman Coulter Prostate Health Index using WHO calibration.

Publications

Prospective multicenter evaluation of the Beckman Coulter Prostate Health Index using WHO calibration.

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