Whom to Biopsy: Prediagnostic Risk Stratification with Biomarkers, Nomograms, and Risk Calculators

MRI-based prostate cancer classification using 3D efficient capsule network

BACKGROUND

Prostate cancer (PCa) is the most common cancer in men and the second leading cause of male cancer-related death. Gleason score (GS) is the primary driver of PCa risk-stratification and medical decision-making, but can only be assessed at present via biopsy under anesthesia. Magnetic resonance imaging (MRI) is a promising non-invasive method to further characterize PCa, providing additional anatomical and functional information. Meanwhile, the diagnostic power of MRI is limited by qualitative or, at best, semi-quantitative interpretation criteria, leading to inter-reader variability.

PURPOSES

Computer-aided diagnosis employing quantitative MRI analysis has yielded promising results in non-invasive prediction of GS. However, convolutional neural networks (CNNs) do not implicitly impose a frame of reference to the objects. Thus, CNNs do not encode the positional information properly, limiting method robustness against simple image variations such as flipping, scaling, or rotation. Capsule network (CapsNet) has been proposed to address this limitation and achieves promising results in this domain. In this study, we develop a 3D Efficient CapsNet to stratify GS-derived PCa risk using T2-weighted (T2W) MRI images.

METHODS

In our method, we used 3D CNN modules to extract spatial features and primary capsule layers to encode vector features. We then propose to integrate fully-connected capsule layers (FC Caps) to create a deeper hierarchy for PCa grading prediction. FC Caps comprises a secondary capsule layer which routes active primary capsules and a final capsule layer which outputs PCa risk. To account for data imbalance, we propose a novel dynamic weighted margin loss. We evaluate our method on a public PCa T2W MRI dataset from the Cancer Imaging Archive containing data from 976 patients.

RESULTS

Two groups of experiments were performed: (1) we first identified high-risk disease by classifying low + medium risk versus high risk; (2) we then stratified disease in one-versus-one fashion: low versus high risk, medium versus high risk, and low versus medium risk. Five-fold cross validation was performed. Our model achieved an area under receiver operating characteristic curve (AUC) of 0.83 and 0.64 F1-score for low versus high grade, 0.79 AUC and 0.75 F1-score for low + medium versus high grade, 0.75 AUC and 0.69 F1-score for medium versus high grade and 0.59 AUC and 0.57 F1-score for low versus medium grade. Our method outperformed state-of-the-art radiomics-based classification and deep learning methods with the highest metrics for each experiment. Our divide-and-conquer strategy achieved weighted Cohen's Kappa score of 0.41, suggesting moderate agreement with ground truth PCa risks.

CONCLUSIONS

In this study, we proposed a novel 3D Efficient CapsNet for PCa risk stratification and demonstrated its feasibility. This developed tool provided a non-invasive approach to assess PCa risk from T2W MR images, which might have potential to personalize the treatment of PCa and reduce the number of unnecessary biopsies.

Prostate cancer screening: Continued controversies and novel biomarker advancements

Prostate cancer (PCa) screening remains one of the most controversial topics in clinical and public health. Despite being the second most common cancer in men worldwide, recommendations for screening using prostate-specific antigen (PSA) are unclear. Early detection and the resulting postscreening treatment lead to overdiagnosis and overtreatment of otherwise indolent cases. In addition, several unwanted harms are associated with PCa screening process. This literature review focuses on the limitations of PSA-specific PCa screening, reasons behind the screening controversy, and the novel biomarkers and advanced innovative methodologies that improve the limitations of traditional screening using PSA. With the verdict of whether or not to screen not yet unanimous, we hope to aid in resolution of the long-standing debate.

miRNAs as molecular biomarkers for prostate cancer

MicroRNAs (miRNAs) are short noncoding RNA able to regulate specific mRNA stability, thus influencing target gene expression. Disrupted levels of several miRNA have been associated with prostate cancer, the leading cause of cancer death among men and the fifth leading cause of death worldwide. Here, we investigated whether miR-145, miR-148, and miR-185 circulating levels in plasma could be used as molecular biomarkers, to allow distinguishing between individuals with benign prostatic hyperplasia, precancerous lesion, and prostate cancer. In this study, we recruited 170 urological clinic patients with suspected prostate cancer who underwent prostate biopsy. Total RNA was isolated from plasma, and TaqMan MicroRNA assays were used to analyze miR-145, miR-185, and miR-148 expression. First, differential miRNA expression among patient groups was evaluated. Then, miRNA levels were combined with clinical assessment outcomes, including results from invasive tests, using multivariate analysis to examine their ability in discriminating among the three patient groups. Our results suggest that miRNA is a promising molecular tool for clinical management of at-risk patients.

The efficiency of prostate-specific antigen density measurement using three different methods on the prediction of biochemical recurrence

BACKGROUND

The aim of this study was to evaluate the efficiency of prostate-specific antigen (PSA) density (PSAD) calculated through prostate volume (PV) obtained via transrectal ultrasound (TRUS) and magnetic resonance imaging (MRI) and actual prostate weight (PW) methods obtained via pathological evaluation on the prediction of biochemical recurrence (BCR) in the follow-ups of patients who had undergone radical prostatectomy (RP).

METHODS

A total of 335 clinically localized prostate cancer (PCa) patients who had received open RP between January 2015 and December 2018 were enrolled in the study. Pre and postoperative demographic data, clinical and pathological findings and BCR conditions were recorded. The PSAD was calculated using information obtained through preoperative TRUS examinations, MRI, and collected pathological specimens after RP by dividing the maximum preoperative PSA value and PV/PW.

RESULTS

In a mean follow-up duration of 20.2 ± 8.5 months, recurrence was observed in 52 patients (24.4%) and progression was observed in 8 (3.8%) patients. The TRUS-PSAD, MRI-PSAD, and PW-PSAD values were statistically significantly higher in BCR patients compared to non-BCR patients. The International Society of Urologic Pathologists (ISUP) grade 5 and pT3b as a pathological stage were detected as independent variables in the prediction of BCR formation. Actual PW had a high prediction value compared to other PSAD measurements at <40 g prostate weights, but it had a low prediction value in prostates with an actual PW >60 g.

CONCLUSIONS

In this study, it was stated that PSAD acquired through different imaging methods does not affect the usability of PSAD in BCR prediction in clinical practice. The ISUP grade 5 and pT3b stage PCa were detected as independent markers in BCR prediction after RP.

Predicting high-grade prostate cancer at initial biopsy: clinical performance of the ExoDx (EPI) Prostate Intelliscore test in three independent prospective studies

Background

The ability to discriminate indolent from clinically significant prostate cancer (PC) at the initial biopsy remains a challenge. The ExoDx Prostate (IntelliScore) (EPI) test is a noninvasive liquid biopsy that quantifies three RNA targets in urine exosomes. The EPI test stratifies patients for risk of high-grade prostate cancer (HGPC; ≥ Grade Group 2 [GG] PC) in men ≥ 50 years with equivocal prostate-specific antigen (PSA) (2–10 ng/mL). Here, we present a pooled meta-analysis from three independent prospective-validation studies in men presenting for initial biopsy decision.

Methods

Pooled data from two prospective multi-site validation studies and the control arm of a clinical utility study were analyzed. Performance was evaluated using the area under the receiver-operating characteristic curve (AUC), negative predictive value (NPV), positive predictive value (PPV), sensitivity, and specificity for discriminating ≥ GG2 from GG1 and benign pathology.

Results

The combined cohort (n = 1212) of initial-biopsy subjects had a median age of 63 years and median PSA of 5.2 ng/mL. The EPI AUC (0.70) was superior to PSA (0.56), Prostate Cancer Prevention Trial Risk Calculator (PCPT-RC) (0.62), and The European Randomized Study of Screening for Prostate Cancer (ERSPC) (0.59), (all p-values <0.001) for discriminating GG2 from GG1 and benign histology. The validated cutoff of 15.6 would avoid 23% of all prostate biopsies and 30% of “unnecessary” (benign or Gleason 6/GG1) biopsies, with an NPV of 90%.

Conclusions

EPI is a noninvasive, easy-to-use, urine exosome–RNA assay that has been validated across 3 independent prospective multicenter clinical trials with 1212 subjects. The test can discriminate high-grade (≥GG2) from low-grade (GG1) cancer and benign disease. EPI effectively guides the biopsy-decision process independent of PSA and other standard-of-care factors.

18F-choline PET/computed tomography and clinical parameters in the detection of significant prostate cancer in patients with increased prostate-specific antigen levels and previous negative biopsies

OBJECTIVES

The aim of this study is to assess the value of the F-choline PET/computed tomography (CT) in predicting significant prostate cancer (sPCa) in patients with persistently increased prostate-specific antigen (PSA) levels and previous negative biopsies. To study the possible predictive added value of F-choline PET/CT to clinical variables and biomarkers derived from PSA in detecting sPCa.

METHODS

We evaluated patients who underwent F-choline PET/CT because of ongoing suspicion of prostate cancer (PCa) due to elevated PSA levels (4-20 ng/mL) and at least one previous negative or no conclusive prostate biopsy for PCa. Age, PSA, free PSA, free/total PSA ratio, PSA velocity, PSA doubling time, PSA density and score risk were obtained. F-choline PET/CT was classified as negative/positive (PET-categorical). Additionally, we subclassified F-choline PET/CT according to the radiotracer uptake patterns (PET-pattern). The reference standard was the histological confirmation. Accuracy of PET/CT was evaluated. Univariate and multivariate logistic regression analyses were performed for metabolic and clinical variables.

RESULTS

A total of 78 patients were included in our study, 23 had PCa (15 with sPCa). The PET pattern showed the highest accuracy and was the most powerful predictor of sPCa. In this research, the prediction of sPCa was improved combining PET pattern and score risk.

CONCLUSION

F-choline PET/CT is a potential tool for predicting sPCa in patients with persistently increased PSA levels and previous negative biopsies, and also it could improve the performance of score risk in predicting sPCa.

Concordance and Performance of 4Kscore and SelectMDx for Informing Decision to Perform Prostate Biopsy and Detection of Prostate Cancer

OBJECTIVES

To compare both the concordance between the 4Kscore and SelectMDx for informing decision to perform prostate biopsy (PB) and the performance of these tests for detecting clinically significant prostate cancer (csPCa). Several biomarkers were developed to inform decisions whether to perform a PB based on the probability of detecting csPCa. There is a paucity of studies directly comparing them METHODS: Between 11/2018 and 4/2019, all new referrals with the diagnosis of elevated PSA were advised to undergo 4Kscore and SelectMDx in order to guide the selection of candidates for PB. Men were advised to undergo PB if the reported biomarker risk for detecting csPCA was ≥7.5%, or if they presented a Prostate Image Reporting and Data System ≥1 MRI. Cohen's Kappa was used to assess the concordance between the binary 4Kscore and SelectMDx results using externally validated cutoffs of 7.5% and 12%. Receiver operating characteristics curve and area under the curve (AUC) assessed the performance of each biomarker for distinguishing csPCa.

RESULTS

Of 128 consecutive patients referred, 114 (89.1%) underwent 4Kscore and SelectMDx. The kappa coefficient between the biomarkers using the 7.5% cutoff was 0.184 (poor concordance) and 0.22 using the 12% cutoff. The two biomarkers yielded discordant guidance whether to proceed with PB in 46% and 38% of cases, respectively. csPCa was found in 22 of the 50 patients who underwent PB (44%). The AUC for 4Kscore and SelectMDx was 0.830 (95% confidence interval [CI]: 0.710 - 0.949) and 0.672 (95%CI: 0.517 - 0.828; P = .036) for csPCa, respectively.

CONCLUSION

The discordance observed between the 4Kscore and SelectMDx is disconcerting. The 4Kscore when combined with magnetic resonance imaging was superior to the SelectMDx for detecting csPCa. Prospective comparative studies must be performed to optimize implementation of biomarkers for selecting candidates for PB.

MRI combined with PSA density in detecting clinically significant prostate cancer in patients with PSA serum levels of 4∼10ng/mL: Biparametric versus multiparametric MRI

PURPOSE

To compare the performance of biparametric magnetic resonance imaging (bpMRI) to that of multiparametric MRI (mpMRI) in combination with prostate-specific antigen density (PSAD) in detecting clinically significant prostate cancer (csPCa) in patients with PSA serum levels of 4∼10ng/mL.

MATERIALS AND METHODS

A total of 123 men (mean age, 66.3±8.9 [SD]; range: 42-83 years) with PSA serum levels of 4∼10ng/mL with suspected csPCa were included. All patients underwent mpMRI at 3 Tesla and transrectal ultrasound-guided prostate biopsy in their clinical workup and were followed-up for >1 year when no csPCa was found at initial biopsy. The mpMRI images were reinterpreted according to the Prostate Imaging Reporting and Data System (PI-RADS, v2.1) twice in two different sessions using either mpMRI sequences or bpMRI sequences. The patients were divided into 2 groups according to whether csPCa was detected. The PI-RADS (mpMRI or bpMRI) categories and PSAD were used in combination to detect csPCa. Receiver operating characteristic (ROC) curve and decision curve analyses were performed to compare the efficacy of the different models (mpMRI, bpMRI, PSAD, mpMRI+PSAD and bpMRI+PSAD).

RESULTS

Thirty-seven patients (30.1%, 37/123) had csPCa. ROC analysis showed that bpMRI (AUC=0.884 [95% confidence interval (CI): 0.814-0.935]) outperformed mpMRI (AUC=0.867 [95% CI: 0.794-0.921]) (P=0.035) and that bpMRI and mpMRI performed better than PSAD (0.682 [95% CI: 0.592-0.763]) in detecting csPCa; bpMRI+PSAD (AUC=0.907 [95% CI: 0.841-0.952]) performed similarly to mpMRI+PSAD (AUC=0.896 [95% CI: 0.828-0.944]) (P=0.151) and bpMRI (P=0.224). The sensitivity and specificity were 81.1% (95% CI: 64.8-92.0%) and 88.4% (95% CI: 79.7-94.3%), respectively for bpMRI, and 83.8% (95% CI: 68.0-93.8%) and 80.2% (95% CI: 70.2-88.0%), respectively for mpMRI (P>0.999 for sensitivity and P=0.016 for specificity). Among the 5 decision models, the decision curve analysis showed that all models (except for PSAD) achieved a high net benefit.

CONCLUSION

In patients with PSA serum levels of 4∼10ng/mL, bpMRI and bpMRI combined with PSAD achieve better performance than mpMRI in detecting csPCa; bpMRI has a higher specificity than mpMRI, which could decrease unnecessary biopsy, and may serve as a potential alternative to mpMRI to optimize clinical workup.

Development and External Validation of Multiparametric MRI-Derived Nomogram to Predict Risk of Pathologic Upgrade in Patients on Active Surveillance for Prostate Cancer

OBJECTIVE. The aim of this study was to create, develop, and externally validate a nomogram that predicts pathologic upgrade in patients on active surveillance (AS) for prostate cancer using commonly available clinical and multiparametric MRI (mpMRI) factors. MATERIALS AND METHODS. A consecutive sample of 300 patients undergoing AS for prostate cancer at the Keimyung University Dongsan Hospital between 2010 and 2016 was used to develop the nomogram. The validation cohort consisted of 150 patients undergoing active surveillance at Kyungpook National University Hospital between 2013 and 2017. The study outcome was the occurrence of pathologic upgrade in AS patients. The relationship between the clinical and mpMRI factors considered and pathologic upgrade was tested using univariate and multivariate logistic regression analyses. The predictive accuracy of the nomogram was determined using the ROC AUC. RESULTS. The overall rate of pathologic upgrade was 25.0% in the developmental cohort and 22.0% in the validation cohort. Significant variables in the models were age, prostate-specific antigen level, biopsy grade group 2, baseline Prostate Imaging Reporting and Data System (PI-RADS) scores of 4 and 5, positive cores on initial biopsy greater than 1, and biopsy cores with 50% or more tumor involvement. The progression seen on mpMRI of PI-RADS score was significantly associated with pathologic upgrade. The nomogram used to predict the risk of pathologic upgrade had a predictive accuracy of 0.78 in the external validation cohort. CONCLUSION. This study developed and externally validated a nomogram that predicts the risk of pathologic upgrade on the basis of commonly used factors. This nomogram may be used to assist management decision making for patients on AS for prostate cancer.

Novel Diagnostic Biomarkers of Prostate Cancer: An Update

OBJECTIVE

In recent years, several biomarkers alternative to standard prostate specific antigen (PSA) for prostate cancer (PCa) diagnosis have become available. The aim of this systematic review is to assess the current knowledge about alternative serum and urinary biomarkers for the diagnosis of PCa.

MATERIAL AND METHODS

A research was conducted in Medline, restricted to English language articles published between December 2014 and June 2018 with the aim to update previously published series on PCa biomarkers. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) criteria were used for selecting studies with the lowest risk of bias.

RESULTS

Emerging role and actual controversies on serum and urine alternative biomarkers to standard PSA for PCa diagnosis, staging and prognosis assessment, such as prostate health index (PHI), PCA3, ConfirmMDx, Aberrant PSA glycosylation, MiPS, miRNAs are critically presented in the current review.

CONCLUSION

Although the use of several biomarkers has been recommended or questioned by different international guidelines, larger prospective randomized studies are still necessary to validate their efficacy in PCa detection, discrimination, prognosis and treatment effectiveness. To date, only PHI and 4Kscore have shown clinical relevance for discriminating more aggressive PCa. Furthermore, a new grading classification based on molecular features relevant for PCa risk-stratification and tailoring treatment is still needed.

A Prospective Adaptive Utility Trial to Validate Performance of a Novel Urine Exosome Gene Expression Assay to Predict High-grade Prostate Cancer in Patients with Prostate-specific Antigen 2-10ng/ml at Initial Biopsy

BACKGROUND

Discriminating indolent from clinically significant prostate cancer (PCa) in the initial biopsy setting remains an important issue. Prospectively evaluated diagnostic assays are necessary to ensure efficacy and clinical adoption.

OBJECTIVE

Performance and utility assessment of ExoDx Prostate (IntelliScore) (EPI) urine exosome gene expression assay versus standard clinical parameters for discriminating Grade Group (GG) ≥2 PCa from GG1 PCa and benign disease on initial biopsy.

DESIGN, SETTING, AND PARTICIPANTS

A two-phase adaptive clinical utility study (NCT03031418) comparing EPI results with biopsy outcomes in men, with age ≥50 yr and prostate-specific antigen (PSA) 2-10ng/ml, scheduled for initial prostate biopsy. After EPI performance assessment during phase I, a clinical implementation document (ie, CarePath) was developed for utilizing the EPI test in phase II, where the biopsy decision is uncertain.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Performance evaluation of the EPI test in patients enrolled in phase I and publication of a consensus CarePath for phase II.

RESULTS AND LIMITATIONS

In a total of 503 patients, with median age of 64 yr, median PSA 5.4ng/ml, 14% African American, 70% Caucasian, 53% positive biopsy rate (22% GG1, 17% GG2, and 15% ≥ GG3), EPI was superior to an optimized model of standard clinical parameters with an area under the curve (AUC) 0.70 versus 0.62, respectively, comparable with previously published results (n=519 patients, EPI AUC 0.71). Validated cut-point 15.6 would avoid 26% of unnecessary prostate biopsies and 20% of total biopsies, with negative predictive value (NPV) 89% and missing 7% of ≥GG2 PCa. Alternative cut-point 20 would avoid 40% of unnecessary biopsies and 31% of total biopsies, with NPV 89% and missing 11% of ≥GG2 PCa. The clinical investigators reached consensus recommending use of the 15.6 cut-point for phase II. Outcome of the decision impact cohort in phase II will be reported separately.

CONCLUSIONS

EPI is a noninvasive, easy-to-use, gene expression urine assay, which has now been successfully validated in over 1000 patients across two prospective validation trials to stratify risk of ≥GG2 from GG1 cancer and benign disease. The test improves identification of patients with higher grade disease and would reduce the total number of unnecessary biopsies.

PATIENT SUMMARY

It is challenging to predict which men are likely to have high-grade prostate cancer (PCa) at initial biopsy with prostate-specific antigen 2-10ng/ml. This study further demonstrates that the ExoDx Prostate (IntelliScore) test can predict ≥GG2 PCa at initial biopsy and defer unnecessary biopsies better than existing risk calculator's and standard clinical data.

Assessment of the Diagnostic Accuracy of Biparametric Magnetic Resonance Imaging for Prostate Cancer in Biopsy-Naive Men: The Biparametric MRI for Detection of Prostate Cancer (BIDOC) Study

IMPORTANCE

Multiparametric magnetic resonance imaging (MRI) enhances detection and risk stratification for significant prostate cancer but is time-consuming (approximately 40 minutes) and expensive. Rapid and simpler (approximately 15-minute) biparametric MRI (bpMRI) using fewer scan sequences could be implemented as a prostate MRI triage test on a larger scale before performing biopsies.

OBJECTIVES

To assess the diagnostic accuracy and negative predictive value (NPV) of a novel bpMRI method in biopsy-naive men in detecting and ruling out significant prostate cancer in confirmatory biopsies.

DESIGN, SETTING, AND PARTICIPANTS

A single-institutional, paired, prospective cohort study of biopsy-naive men with clinical suspicion of prostate cancer from November 1, 2015, to June 15, 2017.

INTERVENTIONS

All patients underwent bpMRI (T2-weighted and diffusion-weighted imaging) followed by standard transrectal ultrasound-guided biopsies (all men) and targeted biopsies of men with suspicious bpMRI findings.

MAIN OUTCOMES AND MEASURES

Suspicion grades of bpMRI, biopsy results, and NPV of bpMRI were evaluated for detection of or ruling out significant prostate cancer (Gleason score ≥4 + 3 or maximum cancerous core length >50% for Gleason score 3 + 4). We compared the diagnostic performance of standard biopsies in all men vs standard plus targeted (combined) biopsies restricted to men with suspicious bpMRI findings. The reference standard was combined biopsy results from all men.

RESULTS

A total of 1020 men were enrolled, with a median age of 67 years (interquartile range, 61-71 years) and a median prostate-specific antigen level of 8.0 ng/mL (interquartile range, 5.7-13.0 ng/mL). Combined biopsies detected any and significant prostate cancer in 655 of 1020 men (64%) and 404 of 1020 men (40%), respectively. Restricting combined biopsies to men with suspicious bpMRI findings meant 305 of 1020 men (30%) with low-suspicious bpMRIs could avoid prostate biopsies (biopsy in 715 men with suspicious bpMRIs vs all 1020 men who required standard biopsies [70%]; P < .001). Significant prostate cancer diagnoses were improved by 11% (396 vs 351 men; P < .001), and insignificant prostate cancer diagnoses were reduced by 40% (173 vs 288 men; P < .001) compared with our current diagnostic standard, standard biopsies alone in all men. The NPV of bpMRI findings in ruling out significant prostate cancer was 97% (95% CI, 95%-99%).

CONCLUSIONS AND RELEVANCE

Low-suspicion bpMRI has a high NPV in ruling out significant prostate cancer in biopsy-naive men. Using a simple and rapid bpMRI method as a triage test seems to improve risk stratification and may be used to exclude aggressive disease and avoid unnecessary biopsies with its inherent risks. Future studies are needed to fully explore its role in clinical prostate cancer management.