Prostate CancerComparison of Two Prostate Cancer Risk Calculators that Include the Prostate Health Index
Introduction
Prostate cancer (PCa) is the most common form of cancer in men in Europe [1]. Prostate-specific antigen (PSA) testing is the mainstay of early PCa detection [2]. However, PSA has limited specificity in predicting the presence of PCa, which leads to unnecessary biopsies and the diagnosis of potentially indolent PCa [3], [4]. A prostate biopsy is an invasive procedure, and apart from costs and anxiety, is not without a risk of complications [5].
PSA-based multivariable prediction tools have been developed to improve the prediction of biopsy-detectable PCa. Well-known and externally validated models include the European Randomized Study of Prostate Cancer (ERSPC) risk calculators (RCs) (http://www.prostatecancer-riskcalculator.com/) [6], the Prostate Cancer Prevention Trial calculator (http://deb.uthscsa.edu/URORiskCalc/Pages/calcs.jsp) [7], and the Montreal model [8]. Risk prediction models have become an important tool in reducing unnecessary prostate biopsies [9]. The addition of new biomarkers to an existing prediction tool may increase its accuracy. Novel and promising markers in the field of PCa include the Prostate Health Index (PHI), based on data for total PSA (tPSA), free PSA (fPSA), and [–2]proPSA (p2PSA). PHI has been approved for use by the US Food and Drug Administration (http://www.accessdata.fda.gov/cdrh_docs/pdf9/p090026a.pdf).
Lughezzani et al [10] developed and validated a nomogram that includes PHI. We aimed to compare PCa RCs that include PHI, the Lughezzani PHI-based nomogram, and PHI-updated digital rectal examination (DRE)-based ERSPC models.
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Participants
Our study cohort comprised 1185 men from four sites in Europe (Paris, Rennes, Hamburg, and Münster). Data on tPSA, fPSA, p2PSA, PHI, DRE, prostate volume, and biopsy outcome (PCa detected yes/no) were collected for all men. Participants in the study underwent a biopsy according to the standard clinical practice routinely used at each participating site, which was a ≥10-core biopsy. We calculated PHI using the equation (p2PSA / fPSA) × √tPSA [11]. tPSA was between 2.0 and 10.0 ng/ml (Access
Participants
Among the 1185 men studied, 797 (67%, 453 with PCa) had no previous biopsy and 388 (170 with PCa) had a previous negative biopsy (Table 1). Median PSA was 5.0 ng/ml for men with no prior biopsy and 5.6 ng/ml for men with a prior biopsy, and median PHI values were 47 and 41, respectively. Men without a prior biopsy were more likely to have (clinically relevant) cancer compared to men with a prior biopsy.
Updating the ERSPC model
For total PCa, PHI improved discrimination (AUC 0.72, 95% confidence interval [CI] 0.69–0.75)
Discussion
PHI and its PSA components add important diagnostic information in distinguishing PCa from normal prostate tissue and when considered in addition to existing PCa RC models. However, the net reduction in biopsies was limited and only observed at PCa risk thresholds of approximately 20–30% using the two RCs we investigated. Nevertheless, it must be noted that NB would be higher in a population in which PCa prevalence is closer to the relevant decision threshold (eg, ∼30%), as found for some
Conclusions
In conclusion, PHI increases the predictive ability of previously developed RCs for detection of cancer. However, only limited reductions in the rates of unnecessary biopsies are possible for both the Lughezzani and the updated ERSPC models.
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These authors contributed equally to this work.