Performance of transrectal prostate biopsies in detecting tumours and implications for focal therapy

Prostate MRI added to CAPRA, MSKCC and Partin cancer nomograms significantly enhances the prediction of adverse findings and biochemical recurrence after radical prostatectomy

Background

To determine the added value of preoperative prostate multiparametric MRI (mpMRI) supplementary to clinical variables and their role in predicting post prostatectomy adverse findings and biochemically recurrent cancer (BCR).

Methods

All consecutive patients treated at HUS Helsinki University Hospital with robot assisted radical prostatectomy (RALP) between 2014 and 2015 were included in the analysis. The mpMRI data, clinical variables, histopathological characteristics, and follow-up information were collected. Study end-points were adverse RALP findings: extraprostatic extension, seminal vesicle invasion, lymph node involvement, and BCR. The Memorial Sloan Kettering Cancer Center (MSKCC) nomogram, Cancer of the Prostate Risk Assessment (CAPRA) score and the Partin score were combined with any adverse findings at mpMRI. Predictive accuracy for adverse RALP findings by the regression models was estimated before and after the addition of MRI results. Logistic regression, area under curve (AUC), decision curve analyses, Kaplan-Meier survival curves and Cox proportional hazard models were used.

Results

Preoperative mpMRI data from 387 patients were available for analysis. Clinical variables alone, MSKCC nomogram or Partin tables were outperformed by models with mpMRI for the prediction of any adverse finding at RP. AUC for clinical parameters versus clinical parameters and mpMRI variables were 0.77 versus 0.82 for any adverse finding. For MSKCC nomogram versus MSKCC nomogram and mpMRI variables the AUCs were 0.71 and 0.78 for any adverse finding. For Partin tables versus Partin tables and mpMRI variables the AUCs were 0.62 and 0.73 for any adverse finding. In survival analysis, mpMRI-projected adverse RP findings stratify CAPRA and MSKCC high-risk patients into groups with distinct probability for BCR.

Conclusions

Preoperative mpMRI improves the predictive value of commonly used clinical variables for pathological stage at RP and time to BCR. mpMRI is available for risk stratification prebiopsy, and should be considered as additional source of information to the standard predictive nomograms.

Associations of PTEN and ERG with Magnetic Resonance Imaging Visibility and Assessment of Non-organ-confined Pathology and Biochemical Recurrence After Radical Prostatectomy

BACKGROUND

Diagnosing clinically significant prostate cancer (PCa) is challenging, but may be facilitated by biomarkers and multiparametric magnetic resonance imaging (MRI).

OBJECTIVE

To determine the association between biomarkers phosphatase and tensin homolog (PTEN) and ETS-related gene (ERG) with visible and invisible PCa lesions in MRI, and to predict biochemical recurrence (BCR) and non-organ-confined (non-OC) PCa by integrating clinical, MRI, and biomarker-related data.

DESIGN, SETTING, AND PARTICIPANTS

A retrospective analysis of a population-based cohort of men with PCa, who underwent preoperative MRI followed by radical prostatectomy (RP) during 2014-2015 in Helsinki University Hospital (n = 346), was conducted. A tissue microarray corresponding to the MRI-visible and MRI-invisible lesions in RP specimens was constructed and stained for PTEN and ERG.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Associations of PTEN and ERG with MRI-visible and MRI-invisible lesions were examined (Pearson's χ² test), and predictions of non-OC disease together with clinical and MRI parameters were determined (area under the receiver operating characteristic curve and logistic regression analyses). BCR prediction was analyzed by Kaplan-Meier and Cox proportional hazard analyses.

RESULTS AND LIMITATIONS

Patients with MRI-invisible lesions (n = 35) had less PTEN loss and ERG-positive expression compared with patients (n = 90) with MRI-visible lesions (17.2% vs 43.3% [p = 0.006]; 8.6% vs 20.0% [p = 0.125]). Patients with invisible lesions had better, but not statistically significantly improved, BCR-free survival probability in Kaplan-Meier analyses (p = 0.055). Rates of BCR (5.7% vs 21.1%; p = 0.039), extraprostatic extension (11.4% vs 44.6%; p < 0.001), seminal vesicle invasion (0% vs 21.1%; p = 0.003), and lymph node metastasis (0% vs 12.2%; p = 0.033) differed between the groups in favor of patients with MRI-invisible lesions. Biomarkers had no independent role in predicting non-OC disease or BCR. The short follow-up period was a limitation.

CONCLUSIONS

PTEN loss, BCR, and non-OC RP findings were more often encountered with MRI-visible lesions.

PATIENT SUMMARY

Magnetic resonance imaging (MRI) of the prostate misses some cancer lesions. MRI-invisible lesions seem to be less aggressive than MRI-visible lesions.

Cumulative Cancer Locations is a Novel Metric for Predicting Active Surveillance Outcomes: A Multicenter Study

BACKGROUND

Active surveillance (AS) of prostate cancer (PC) has increased in popularity to address overtreatment.

OBJECTIVE

To determine whether a novel metric, cumulative cancer locations (CCLO), can predict AS outcomes in a group of AS patients with low and very low risk.

DESIGN, SETTING, AND PARTICIPANTS

CCLO is obtained by summing the total number of histological cancer-positive locations in both diagnostic and confirmatory biopsies (Bx). The retrospective study cohort comprised three prospective AS cohorts (Helsinki University Hospital: n=316; European Institute of Oncology: n=204; and University of Münster: n=89).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

We analyzed whether risk stratification based on CCLO predicts different AS outcomes: protocol-based discontinuation (PBD), Gleason upgrading (GU) during AS, and adverse findings in radical prostatectomy (RP) specimens.

RESULTS

In Kaplan Meier analyses, patients in the CCLO high-risk group experienced significantly shorter event-free survival for all outcomes (PBD, GU, and adverse RP findings; all p<0.002). In multivariable Cox regression analysis, patients in the CCLO high-risk group had a significantly higher risk of experiencing PBD (hazard ratio [HR] 12.15, 95% confidence interval [CI] 6.18-23.9; p<0.001), GU (HR 6.01, 95% CI 2.16-16.8; p=0.002), and adverse RP findings (HR 9.144, 95% CI 2.27-36.9; p=0.006). In receiver operating characteristic analyses, the area under the curve for CCLO outperformed the number of cancer-positive Bxs in confirmatory Bx in predicting PBD (0.734 vs 0.682), GU (0.655 vs 0.576) and adverse RP findings (0.662 vs 0.561) and the added value was supported by decision curve analysis.

CONCLUSIONS

CCLO is distinct from the number of positive Bx cores. Higher CCLO predicts AS outcomes and may aid in selection of patients for AS.

PATIENT SUMMARY

For patients on active surveillance for prostate cancer, the cumulative number of cancer-positive locations in diagnostic and confirmatory biopsies is a predictor of active surveillance outcomes.

Repeat multiparametric MRI in prostate cancer patients on active surveillance

Introduction

This study was conducted to describe the changes in repeat multiparametric MRI (mpMRI) occurring in prostate cancer (PCa) patients during active surveillance (AS), and to study possible associations between mpMRI-related parameters in predicting prostate biopsy (Bx) Gleason score (GS) upgrading >3+3 and protocol-based treatment change (TC).

Materials and methods

The study cohort consisted of 76 AS patients with GS 3+3 PCa and at least two consecutive mpMRIs of the prostate performed between 2006–2015. Patients were followed according to the Prostate Cancer Research International Active Surveillance (PRIAS) protocol and an additional mpMRI. The primary end points were GS upgrading (GU) (>3+3) in protocol-based Bxs and protocol-based TC.

Results

Out of 76 patients, 53 (69%) had progression (PIRADS upgrade, size increase or new lesion[s]), while 18 (24%) had radiologically stable disease, and 5 (7%) had regression (PIRADS or size decrease, disappearance of lesion[s]) in repeat mpMRIs during AS. PIRADS scores of 4–5 in the initial mpMRI were associated with GU (p = 0.008) and protocol-based TC (p = 0.009). Tumour progression on repeat mpMRIs was associated with TC (p = 0.045) but not with GU (p = 1.00). PIRADS scores of 4–5 predict GU (sensitivity 0.80 [95% confidence interval (CI); 0.51–0.95, specificity 0.62 [95% CI; 0.52–0.77]) with PPV and NPV values of 0.34 (95% CI; 0.21–0.55) and 0.93 (95% CI; 0.80–0.98), respectively.

Conclusion

mpMRI is a useful tool not only to select but also to monitor PCa patients on AS.