Elsevier

European Urology

Volume 61, Issue 3, March 2012, Pages 577-583
European Urology

Prostate Cancer
Prediction of Prostate Cancer Risk: The Role of Prostate Volume and Digital Rectal Examination in the ERSPC Risk Calculators

https://doi.org/10.1016/j.eururo.2011.11.012Get rights and content

Abstract

Background

The European Randomized Study of Screening for Prostate Cancer (ERSPC) risk calculators (RCs) are validated tools for prostate cancer (PCa) risk assessment and include prostate volume (PV) data from transrectal ultrasound (TRUS).

Objective

Develop and validate an RC based on digital rectal examination (DRE) that circumvents the need for TRUS but still includes information on PV.

Design, setting, and participants

For development of the DRE-based RC, we studied the original ERSPC Rotterdam RC population including 3624 men (885 PCa cases) and 2896 men (547 PCa cases) detected at first and repeat screening 4 yr later, respectively. A validation cohort consisted of 322 men, screened in 2010–2011 as participants in ERSPC Rotterdam.

Measurements

Data on TRUS-assessed PV in the development cohorts were re-coded into three categories (25, 40, and 60 cm3) to assess the loss of information by categorization of volume information. New RCs including PSA, DRE, and PV categories (DRE-based RC) were developed for men with and without a previous negative biopsy to predict overall and clinically significant PCa (high-grade [HG] PCa) defined as T stage >T2b and/or Gleason score ≥7. Predictive accuracy was quantified by the area under the receiver operating curve. We compared performance with the Prostate Cancer Prevention Trial (PCPT) RC in the validation study.

Results and limitations

Areas under the curve (AUC) of prostate-specific antigen (PSA) alone, PSA and DRE, the DRE-based RC, and the original ERSPC RC to predict PCa at initial biopsy were 0.69, 0.73, 0.77, and 0.79, respectively. The corresponding AUCs for predicting HG PCa were higher (0.74, 0.82, 0.85, and 0.86). Similar results were seen in men previously biopsied and in the validation cohort. The DRE-based RC outperformed the PCPT RC (AUC 0.69 vs 0.59; p = 0.0001) and a model based on PSA and DRE only (AUC 0.69 vs 0.63; p = 0.0075) in the relatively small validation cohort. Further validation is required.

Conclusions

An RC should contain volume estimates based either on TRUS or DRE. Replacing TRUS measurements by DRE estimates may enhance implementation in the daily practice of urologists and general practitioners.

Introduction

It is widely recognized that too many men undergo prostate biopsy if prostate-specific antigen (PSA) alone is used for screening. Multivariable risk calculators (RCs) are essential tools for improved risk stratification. The goal is to identify men at increased risk of having a potentially life-threatening prostate cancer (PCa) as candidates for biopsy [1]. Based on data from the European Randomized Study of Screening for Prostate Cancer (ERSPC) Rotterdam, a multistep PCa RC was developed (www.prostatecancer-riskcalulator.com) [2], [3]. The RC is meant as a decision aid for laypeople, general practitioners, and urologists that provides estimates of current risk on having a biopsy-detectable PCa based on age, family history, and urinary complaints (calculator 1), PSA level (calculator 2), and PSA in combination with digital rectal examination (DRE), transrectal ultrasound (TRUS), prostate volume (PV), and previous biopsy status (calculators 3–5). RC 6 calculates the probability of having a potentially indolent PCa and can be used to aid treatment choice.

The ERSPC RCs 3–5 require information from TRUS, including PV and the presence of hypoechoic lesions. Because the PSA level is related to PV [4], [5], it is reasonable to include PV in PCa prediction models. However, including parameters that require invasive procedures could limit the clinical application of the RC. DRE has a reasonable ability to discriminate correctly between TRUS-assessed PV ± 40 cm3 [6] and performs well for volumes >50 cm3 [7]. We aimed to develop and validate a DRE-based RC that includes information on PV but avoids the need for TRUS before biopsy.

Section snippets

Materials and methods

ERSPC Rotterdam recruited 42 176 men (aged 55–74 yr) randomized into intervention and control arms. Of the 21 210 men randomized to the intervention arm, 19 970 were actually screened. Rescreening was scheduled every 4 yr. Details on biopsy indication are described elsewhere [8]. Men with a biopsy indication first underwent DRE followed by biplanar TRUS using a Bruel and Kjaer model 1846 mainframe and a 7-MHz biplanar endorectal transducer (B&K Medical Systems, Marlborough, MA, USA) in the left

Results

Among the 885 PCa cases detected at first screening, 431 (48.7%) were classified as HG PCa using our criteria. At repeat screening, 131 (23.9%) of the 547 PCa cases were classified as HG PCa (Table 1).

PSA and DRE were both positively correlated with the presence of PCa and HG PCa. A large PV and a previous negative biopsy reduced the likelihood of a biopsy-detectable (HG) PCa (Table 2). An abnormal DRE at the initial screening was highly predictive for HG PCa (odds ratio: 6.1), a direct

Discussion

Multivariable tools have increasingly been developed and validated for use in the primary screening setting. As described earlier, our group previously developed several RCs to aid in the decision for biopsy or to predict indolent disease to help guide management [2], [3] (www.prostatecancer-riskcalculator.com). These RCs have been validated in external populations and shown to have superior discrimination for the prediction of PCa as compared with the PCPT RC, which does not include PV [12],

Conclusions

Risk assessment on the basis of PSA alone is not optimal. It can be improved by adding the outcome of DRE. Additional improvement can easily be obtained, however, by adding information on PV. Realizing that invasive procedures before risk assessment are suboptimal, we developed a DRE-based prediction tool that still contains information on PV and therefore is not only more accurate in risk prediction but also easily implemented into daily urologic practice and therefore also suitable to be used

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