Personalizing prostate cancer diagnosis with multivariate risk prediction tools: how should prostate MRI be incorporated?

From molecular mechanisms of prostate cancer to translational applications: based on multi-omics fusion analysis and intelligent medicine

Prostate cancer is the most common cancer in men worldwide and has a high mortality rate. The complex and heterogeneous development of prostate cancer has become a core obstacle in the treatment of prostate cancer. Simultaneously, the issues of overtreatment in early-stage diagnosis, oligometastasis and dormant tumor recognition, as well as personalized drug utilization, are also specific concerns that require attention in the clinical management of prostate cancer. Some typical genetic mutations have been proved to be associated with prostate cancer's initiation and progression. However, single-omic studies usually are not able to explain the causal relationship between molecular alterations and clinical phenotypes. Exploration from a systems genetics perspective is also lacking in this field, that is, the impact of gene network, the environmental factors, and even lifestyle behaviors on disease progression. At the meantime, current trend emphasizes the utilization of artificial intelligence (AI) and machine learning techniques to process extensive multidimensional data, including multi-omics. These technologies unveil the potential patterns, correlations, and insights related to diseases, thereby aiding the interpretable clinical decision making and applications, namely intelligent medicine. Therefore, there is a pressing need to integrate multidimensional data for identification of molecular subtypes, prediction of cancer progression and aggressiveness, along with perosonalized treatment performing. In this review, we systematically elaborated the landscape from molecular mechanism discovery of prostate cancer to clinical translational applications. We discussed the molecular profiles and clinical manifestations of prostate cancer heterogeneity, the identification of different states of prostate cancer, as well as corresponding precision medicine practices. Taking multi-omics fusion, systems genetics, and intelligence medicine as the main perspectives, the current research results and knowledge-driven research path of prostate cancer were summarized.

Diagnostic performance of MRI in detecting prostate cancer in patients with prostate-specific antigen levels of 4-10 ng/mL: a systematic review and meta-analysis

OBJECTIVE

To investigate the diagnostic performance of MRI in detecting clinically significant prostate cancer (csPCa) and prostate cancer (PCa) in patients with prostate-specific antigen (PSA) levels of 4-10 ng/mL.

METHODS

A computerized search of PubMed, Embase, Cochrane Library, Medline, and Web of Science was conducted from inception until October 31, 2023. We included articles on the use of MRI to detect csPCa or PCa at 4-10 ng/mL PSA. The primary and secondary outcomes were MRI performance in csPCa and PCa detection, respectively; the estimates of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were pooled in a bivariate random-effects model.

RESULTS

Among the 19 studies (3879 patients), there were 10 (2205 patients) and 13 studies (2965 patients) that reported MRI for detecting csPCa or PCa, respectively. The pooled sensitivity and specificity for csPCa detection were 0.84 (95% confidence interval [CI], 0.79-0.88) and 0.76 (95%CI, 0.65-0.84), respectively, for PCa detection were 0.82 (95%CI, 0.75-0.87) and 0.74 (95%CI, 0.65-0.82), respectively. The pooled NPV for csPCa detection was 0.91 (0.87-0.93). Biparametric magnetic resonance imaging also showed a significantly higher sensitivity and specificity relative to multiparametric magnetic resonance imaging (both p < 0.01).

CONCLUSION

Prostate MRI enables the detection of csPCa and PCa with satisfactory performance in the PSA gray zone. The excellent NPV for csPCa detection indicates the possibility of biopsy decision-making in patients in the PSA gray zone, but substantial heterogeneity among the included studies should be taken into account.

CLINICAL RELEVANCE STATEMENT

Prostate MRI can be considered a reliable and satisfactory tool for detecting csPCa and PCa in patients with PSA in the "gray zone", allowing for reducing unnecessary biopsy and optimizing the overall examination process.

KEY POINTS

Prostate-specific antigen (PSA) is a common screening tool for prostate cancer but risks overdiagnosis. MRI demonstrated excellent negative predictive value for prostate cancer in the PSA gray zone. MRI can influence decision-making for these patients, and biparametric MRI should be further evaluated.

Reduction of false positives using zone-specific prostate-specific antigen density for prostate MRI-based biopsy decision strategies

OBJECTIVES

To develop and test zone-specific prostate-specific antigen density (sPSAD) combined with PI-RADS to guide prostate biopsy decision strategies (BDS).

METHODS

This retrospective study included consecutive patients, who underwent prostate MRI and biopsy (01/2012-10/2018). The whole gland and transition zone (TZ) were segmented at MRI using a retrained deep learning system (DLS; nnU-Net) to calculate PSAD and sPSAD, respectively. Additionally, sPSAD and PI-RADS were combined in a BDS, and diagnostic performances to detect Grade Group ≥ 2 (GG ≥ 2) prostate cancer were compared. Patient-based cancer detection using sPSAD was assessed by bootstrapping with 1000 repetitions and reported as area under the curve (AUC). Clinical utility of the BDS was tested in the hold-out test set using decision curve analysis. Statistics included nonparametric DeLong test for AUCs and Fisher-Yates test for remaining performance metrics.

RESULTS

A total of 1604 patients aged 67 (interquartile range, 61-73) with 48% GG ≥ 2 prevalence (774/1604) were evaluated. By employing DLS-based prostate and TZ volumes (DICE coefficients of 0.89 (95% confidence interval, 0.80-0.97) and 0.84 (0.70-0.99)), GG ≥ 2 detection using PSAD was inferior to sPSAD (AUC, 0.71 (0.68-0.74)/0.73 (0.70-0.76); p < 0.001). Combining PI-RADS with sPSAD, GG ≥ 2 detection specificity doubled from 18% (10-20%) to 43% (30-44%; p < 0.001) with similar sensitivity (93% (89-96%)/97% (94-99%); p = 0.052), when biopsies were taken in PI-RADS 4-5 and 3 only if sPSAD was ≥ 0.42 ng/mL/cc as compared to all PI-RADS 3-5 cases. Additionally, using the sPSAD-based BDS, false positives were reduced by 25% (123 (104-142)/165 (146-185); p < 0.001).

CONCLUSION

Using sPSAD to guide biopsy decisions in PI-RADS 3 lesions can reduce false positives at MRI while maintaining high sensitivity for GG ≥ 2 cancers.

CLINICAL RELEVANCE STATEMENT

Transition zone-specific prostate-specific antigen density can improve the accuracy of prostate cancer detection compared to MRI assessments alone, by lowering false-positive cases without significantly missing men with ISUP GG ≥ 2 cancers.

KEY POINTS

• Prostate biopsy decision strategies using PI-RADS at MRI are limited by a substantial proportion of false positives, not yielding grade group ≥ 2 prostate cancer. • PI-RADS combined with transition zone (TZ)-specific prostate-specific antigen density (PSAD) decreased the number of unproductive biopsies by 25% compared to PI-RADS only. • TZ-specific PSAD also improved the specificity of MRI-directed biopsies by 9% compared to the whole gland PSAD, while showing identical sensitivity.

Magnetic Resonance Imaging, Clinical, and Biopsy Findings in Suspected Prostate Cancer: A Systematic Review and Meta-Analysis

Importance

Multiple strategies integrating magnetic resonance imaging (MRI) and clinical data have been proposed to determine the need for a prostate biopsy in men with suspected clinically significant prostate cancer (csPCa) (Gleason score ≥3 + 4). However, inconsistencies across different strategies create challenges for drawing a definitive conclusion.

Objective

To determine the optimal prostate biopsy decision-making strategy for avoiding unnecessary biopsies and minimizing the risk of missing csPCa by combining MRI Prostate Imaging Reporting & Data System (PI-RADS) and clinical data.

Data Sources

PubMed, Ovid MEDLINE, Embase, Web of Science, and Cochrane Library from inception to July 1, 2022.

Study Selection

English-language studies that evaluated men with suspected but not confirmed csPCa who underwent MRI PI-RADS followed by prostate biopsy were included. Each study had proposed a biopsy plan by combining PI-RADS and clinical data.

Data Extraction and Synthesis

Studies were independently assessed for eligibility for inclusion. Quality of studies was appraised using the Quality Assessment of Diagnostic Accuracy Studies 2 tool and the Newcastle-Ottawa Scale. Mixed-effects meta-analyses and meta-regression models with multimodel inference were performed. Reporting of this study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline.

Main Outcomes and Measures

Independent risk factors of csPCa were determined by performing meta-regression between the rate of csPCa and PI-RADS and clinical parameters. Yields of different biopsy strategies were assessed by performing diagnostic meta-analysis.

Results

The analyses included 72 studies comprising 36 366 patients. Univariable meta-regression showed that PI-RADS 4 (β-coefficient [SE], 7.82 [3.85]; P = .045) and PI-RADS 5 (β-coefficient [SE], 23.18 [4.46]; P < .001) lesions, but not PI-RADS 3 lesions (β-coefficient [SE], -4.08 [3.06]; P = .19), were significantly associated with a higher risk of csPCa. When considered jointly in a multivariable model, prostate-specific antigen density (PSAD) was the only clinical variable significantly associated with csPCa (β-coefficient [SE], 15.50 [5.14]; P < .001) besides PI-RADS 5 (β-coefficient [SE], 9.19 [3.33]; P < .001). Avoiding biopsy in patients with lesions with PI-RADS category of 3 or less and PSAD less than 0.10 (vs <0.15) ng/mL2 resulted in reducing 30% (vs 48%) of unnecessary biopsies (compared with performing biopsy in all suspected patients), with an estimated sensitivity of 97% (vs 95%) and number needed to harm of 17 (vs 15).

Conclusions and Relevance

These findings suggest that in patients with suspected csPCa, patient-tailored prostate biopsy decisions based on PI-RADS and PSAD could prevent unnecessary procedures while maintaining high sensitivity.

Risk stratification of prostate cancer with MRI and prostate-specific antigen density-based tool for personalized decision making

OBJECTIVES

MRI is now established for initial prostate cancer diagnosis; however, there is no standardized pathway to avoid unnecessary biopsy in low-risk patients. Our study aimed to test previously proposed MRI-focussed and risk-adapted biopsy decision models on a real-world dataset.

METHODS

Single-centre retrospective study performed on 2055 biopsy naïve patients undergoing MRI. Diagnostic pathways included "biopsy all", "MRI-focussed" and two risk-based MRI-directed pathways. Risk thresholds were based on prostate-specific antigen (PSA) density as low (<0.10 ng mL-2), intermediate (0.10-0.15 ng mL-2), high (0.15-0.20 ng mL-2), or very high-risk (>0.20 ng mL-2). The outcome measures included rates of biopsy avoidance, detection of clinically significant prostate cancer (csPCa), missed csPCa, and overdiagnosis of insignificant prostate cancer (iPCa).

RESULTS

Overall cancer rate was 39.9% (819/2055), with csPCa (Grade-Group ≥2) detection of 30.3% (623/2055). In men with a negative MRI (Prostate Imaging-Reporting and Data System, PI-RADS 1-2), the risk of cancer was 1.2%, 2.6%, 9.0%, and 12.9% in the low, intermediate, high, and very high groups, respectively; for PI-RADS score 3 lesions, the rates were 10.5%, 14.3%, 25.0%, and 33.3%, respectively. MRI-guided pathway and risk-based pathway with a low threshold missed only 1.6% csPCa with a biopsy-avoidance rate of 54.4%, and the risk-based pathway with a higher threshold avoided 62.9% (1292/2055) of biopsies with 2.9% (61/2055) missed csPCa detection. Decision curve analysis found that the "risk-based low threshold" pathway has the highest net benefit for probability thresholds between 3.6% and 13.9%.

CONCLUSION

Combined MRI and PSA-density risk-based pathways can be a helpful decision-making tool enabling high csPCa detection rates with the benefit of biopsy avoidance and reduced iPCa detection.

ADVANCES IN KNOWLEDGE

This real-world dataset from a large UK-based cohort confirms that combining MRI scoring with PSA density for risk stratification enables safe biopsy avoidance and limits the over-diagnosis of insignificant cancers.

Dynamic Contrast-Enhanced Study in the mpMRI of the Prostate-Unnecessary or Underutilised? A Narrative Review

The aim of this review is to summarise recent scientific literature regarding the clinical use of DCE-MRI as a component of multiparametric resonance imaging of the prostate. This review presents the principles of DCE-MRI acquisition and analysis, the current role of DCE-MRI in clinical practice with special regard to its role in presently available categorisation systems, and an overview of the advantages and disadvantages of DCE-MRI described in the current literature. DCE-MRI is an important functional sequence that requires intravenous administration of a gadolinium-based contrast agent and gives information regarding the vascularity and capillary permeability of the lesion. Although numerous studies have confirmed that DCE-MRI has great potential in the diagnosis and monitoring of prostate cancer, its role is still inadequate in the PI-RADS categorisation. Moreover, there have been numerous scientific discussions about abandoning the intravenous application of gadolinium-based contrast as a routine part of MRI examination of the prostate. In this review, we summarised the recent literature on the advantages and disadvantages of DCE-MRI, focusing on an overview of currently available data on bpMRI and mpMRI, as well as on studies providing information on the potential better usability of DCE-MRI in improving the sensitivity and specificity of mpMRI examinations of the prostate.

Transverse prostate maximum sectional area can predict clinically significant prostate cancer in PI-RADS 3 lesions at multiparametric magnetic resonance imaging

Background

To evaluate multiparametric magnetic resonance imaging (mpMRI) parameters, such as TransPA (transverse prostate maximum sectional area), TransCGA (transverse central gland sectional area), TransPZA (transverse peripheral zone sectional area), and TransPAI (TransPZA/TransCGA ratio) in predicting prostate cancer (PCa) in prostate imaging reporting and data system (PI-RADS) 3 lesions.

Methods

Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV), the area under the receiver operating characteristic curve (AUC), and the best cut-off, were calculated. Univariate and multivariate analyses were carried out to evaluate the capability to predict PCa.

Results

Out of 120 PI-RADS 3 lesions, 54 (45.0%) were PCa with 34 (28.3%) csPCas. Median TransPA, TransCGA, TransPZA and TransPAI were 15.4cm², 9.1cm², 5.5cm² and 0.57, respectively. At multivariate analysis, location in the transition zone (OR=7.92, 95% CI: 2.70-23.29, P<0.001) and TransPA (OR=0.83, 95% CI: 0.76-0.92, P<0.001) were independent predictors of PCa. The TransPA (OR=0.90, 95% CI: 0.082-0.99, P=0.022) was an independent predictor of csPCa. The best cut-off of TransPA for csPCa was 18 (Sensitivity 88.2%, Specificity 37.2%, PPV 35.7%, NPV 88.9%). The discrimination (AUC) of the multivariate model was 0.627 (95% CI: 0.519-0.734, P<0.031).

Conclusions

In PI-RADS 3 lesions, the TransPA could be useful in selecting patients requiring biopsy.

Magnetic Resonance Imaging-Targeted Biopsy and Pretherapeutic Prostate Cancer Risk Assessment: a Systematic Review: Biopsie ciblée par Imagerie par résonance magnétique et évaluation pré-thérapeutique du risque de cancer de la prostate : revue systématique

INTRODUCTION

Multiparametric magnetic resonance imaging (MRI) has been included in prostate cancer (PCa) diagnostic pathway and may improve disease characterization. The aim of this systematic review is to assess the added value of MRI-targeted biopsy (TB) in pre-therapeutic risk assessment models over existing tools based on systematic biopsy (SB) for localized PCa.

EVIDENCE ACQUISITION

A systematic search was conducted using Pubmed (Medline), Scopus and ScienceDirect databases according to Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) statement. We included studies through October 2021 reporting on TB in pretherapeutic risk assessment models.

EVIDENCE SYNTHESIS

We identified 24 eligible studies including 24'237 patients for the systematic review. All included studies were retrospective and conducted in patients undergoing radical prostatectomy. Nine studies reported on the risk of extraprostatic extension, seven on the risk of lymph node invasion, three on the risk of biochemical recurrence and nine on the improvement of PCa risk stratification. Overall, the combination of TB with imaging, clinical and biochemical parameters outperformed current pretherapeutic risk assessment models. External validation studies are lacking for certain endpoints and the absence of standardization among TB protocols, including number of TB cores and fusion systems, may limit the generalizability of the results.

CONCLUSION

TB should be incorporated in pretherapeutic risk assessment models to improve clinical decision making. Further high-quality studies are required to determine models' generalizability while there is an urgent need to reach consensus on a standardized TB protocol. Long-term outcomes after treatment are also awaited to confirm the superiority of such models over classical risk classifications only based on SB. © 2022 Elsevier Masson SAS. All rights reserved.

Second Primary Malignancy in Patients with Hypopharyngeal Carcinoma: A SEER-Based Study

Background

A population-based analysis of the risk of secondary primary malignancy (SPM) in patients with hypopharyngeal carcinoma (HPC) has been lacking in the literature. Therefore, we conducted this study to determine the risk factors and assess the effects of SPM on the overall survival (OS) and cancer-specific survival (CSS) of patients with HPC.

Methods

Data on selected patients diagnosed with HPC from the Surveillance, Epidemiology and End Results (SEER) database between 1973 and 2015 were examined through logistic regression, Cox regression and nomogram methods.

Results

The overall risk of SPM in patients with HPC was higher than that in the general population (SIR: 2.77; P < 0.05). The specific-site, including the oral cavity, pharynx, digestive system, respiratory system and endocrine system, had a relatively higher risk of SPM. The overall risks of the subgroup of people 55–75 years of age and all subgroups of sex, race and latency were significantly elevated. In addition, patients with HPC were more likely to have been diagnosed in 2010–2015 (vs 2004–2009; P = 0.002), to be unmarried (vs married; P = 0.008), to have distant metastasis (vs no metastasis; P = 0.016) and to have had no surgery for the first tumor (vs surgery for the first tumor; P = 0.021), and these aspects were associated with a significantly elevated risk of developing SPM. SPM was independently associated with better OS and CSS. The OS and CSS in patients with HPC with SPM were better than those in patients without SPM (log rank P < 0.0001). The C indexes of the nomogram constructed with ten influencing factors including SPM were 0.681:0.699 for OS and 0.705:0.724 for CSS (training cohort:validation cohort).

Conclusion

Although the overall risk of SPM in patients with HPC was elevated, SPM did not decrease the OS and CSS in patients with HPC. This finding is inconsistent with clinical observations and thus requires further research and exploration. It possibly because HPC might have a shorter survival time, or the follow-up time was not long enough.

Artificial Intelligence-assisted Prostate Cancer Diagnosis: Radiologic-Pathologic Correlation

The classic prostate cancer (PCa) diagnostic pathway that is based on prostate-specific antigen (PSA) levels and the findings of digital rectal examination followed by systematic biopsy has shown multiple limitations. The use of multiparametric MRI (mpMRI) is now widely accepted in men with clinical suspicion for PCa. In addition, clinical information, PSA density, risk calculators, and genomic and other "omics" biomarkers are being used to improve risk stratification. On the basis of mpMRI and MRI-targeted biopsies (MRI-TBx), new diagnostic pathways have been established, aiming to improve the limitations of the classic diagnostic approach. However, these pathways still show limitations associated with mpMRI and MRI-TBx. Definitive PCa diagnosis is made on the basis of histopathologic Gleason grading, which has demonstrated an excellent correlation with clinical outcomes. However, Gleason grading is done subjectively by pathologists and involves poor reproducibility, and PCa may have a heterogeneous distribution of histologic patterns. Thus, important discrepancies persist between biopsy tumor grading and final whole-organ pathologic assessment after radical prostatectomy. PCa offers a unique opportunity to establish a real radiologic-pathologic correlation, as whole-mount radical prostatectomy specimens permit a complete spatial relationship with mpMRI. Artificial intelligence is increasingly being applied to radiologic and pathologic images to improve clinical accuracy and efficiency in PCa diagnosis. This review delineates current PCa diagnostic pathways, with a focus on the role of mpMRI, MRI-TBx, and pathologic analysis. An overview of the expected improvements in PCa diagnosis derived from the use of artificial intelligence, integrated radiologic-pathologic systems, and decision support tools for multidisciplinary teams is provided. An invited commentary by Purysko is available online. Online supplemental material is available for this article. ^©RSNA, 2021.

Changing the Prostate Cancer Detection Paradigm: Clinical Application of European Association of Urology Guideline-recommended Magnetic Resonance Imaging-based Risk Stratification in Men with Suspected Prostate Cancer

BACKGROUND

Multiparametric magnetic resonance imaging using the Prostate Imaging Reporting and Data System version 2.1 allows for a personalized, risk-stratified approach to indicating prostate biopsies (PBx) in order to reduce PBx and concomitant complications in men with suspected prostate cancer (PCa). One way to achieve this goal is to implement the risk-stratified pathway (RSP) using the Rotterdam Prostate Cancer Risk Calculator.

OBJECTIVE

To describe the clinical implementation of the RSP and to examine its impact on the number of PBx and the resulting changes in the PCa detection pattern compared with men undergoing PBx in a detection-focused pathway (DFP) without prior risk assessment.

DESIGN, SETTING, AND PARTICIPANTS

An institutional dataset of 505 consecutive patients with suspected PCa between July 2019 and February 2020 was used.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Chi-square test and Mann-Whitney U test were employed to examine differences in the number of PBx and the PCa detection pattern between the DFP (n = 195, 38.6%) and the RSP (n = 310, 61.4%). To minimize differences in risk stratification, inverse probability of treatment weighting was used.

RESULTS AND LIMITATIONS

After implementing the RSP, the overall biopsy rate could be reduced by 11.2% (100% vs 88.8%, p < 0.001. Additionally, compared with the DFP, the number of biopsy cores per patient was reduced in the RSP (14 [interquartile range {IQR} 14-15] vs 14 [IQR 6-14], p < 0.001) and the detection of clinically significant PCa was increased (44.3% vs 57.7%, p = 0.038). Overdiagnosis of clinically insignificant disease was decreased in the RSP (22.8% vs 12.6%, p = 0.039).

CONCLUSIONS

Implementation of the RSP in clinical practice reduced the number of PBx and brought forth a shift in the PCa detection pattern toward clinically significant disease, while reducing overdiagnosis of clinically insignificant disease.

PATIENT SUMMARY

In this study, we examined the impact of risk stratification on the number of prostate biopsies (PBx) and the consecutive detection pattern in men with suspected prostate cancer (PCa). We found that the risk-stratified pathway reduced the number of PBx while simultaneously shifting the PCa detection pattern toward clinically significant PCa.

Pathological features of Prostate Imaging Reporting and Data System (PI-RADS) 3 MRI lesions in biopsy and radical prostatectomy specimens

OBJECTIVE

To assess the whole pathology spectrum of Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions, identified on magnetic resonance imaging, using systematic (SB), targeted biopsy (TB) and radical prostatectomy (RP) specimen analysis.

METHODS

From a prospective database of patients undergoing RP after a combination of SB (median 12 cores) and fusion TB (median 3 cores), we included 150 PI-RADS 3 cases. Clinically significant prostate cancer (csPCa) was defined by a Grade Group 2 or more. The primary endpoints were unfavourable features in RP specimens.

RESULTS

Targeted biopsy was negative in 20.7% of patients. Final Grade Group 3 or more and a pT3 stage was reported in 36.7% and 38.7% of RP specimens. The upgrading rate was 38.2% between biopsy and RP specimens. The concordance rate between Grade Group on TB and RP was only 38.0%. The two independent predictive factors for unfavourable disease (pT3-4 and/or final Grade Group 3-5) were prostate-specific antigen density (PSAD; P = 0.001) and presence of csPCa on TB (odds ratio 3.7; P = 0.001). The risk of unfavourable disease was increased 2.3-fold and 5.8-fold, respectively, for patients with a PSAD between 0.15 and 0.20, and a PSAD >0.20 ng/mL/g. The 5-year biochemical recurrence-free survival rate was 93.2%.

CONCLUSIONS

PI-RADS 3 lesions exhibited aggressive features in almost 40% of cases. PSAD and presence of csPCa on TB are independent predictive factors for high-grade and/or extraprostatic disease. A combination of SB and TB improve grade prediction compared to use of TB alone.

Optimal PSA Threshold for Obtaining MRI-Fusion Biopsy in Biopsy-Naïve Patients

OBJECTIVE

The study investigates the prostate-specific antigen threshold for adding targeted, software-based, magnetic resonance imaging-ultrasound fusion biopsy during a standard 12-core biopsy in biopsy-naïve patients. It secondarily explores whether the targeted biopsy is necessary in setting of abnormal digital rectal examination.

METHODS

260 patients with suspected localized prostate cancer with no prior biopsy underwent prostate magnetic resonance imaging and were found to have Prostate Imaging Reporting and Data System score ≥ 3 lesion(s). All 260 patients underwent standard 12-core biopsy and targeted biopsy during the same session. Clinically significant cancer was Gleason ≥3 + 4.

RESULTS

Percentages of patients with prostate-specific antigen 0-1.99, 2-3.99, 4-4.99, 5-5.99, 6-9.99, and ≥10 were 3.0%, 4.7%, 20.8%, 16.9%, 37.7%, and 16.9%, respectively. Cumulative frequency of clinically significant prostate cancer increased with the addition of targeted biopsy compared with standard biopsy alone across all prostate-specific antigen ranges. The difference in clinically significant cancer detection between targeted plus standard biopsy compared to standard biopsy alone becomes statistically significant at prostate-specific antigen >4.3 (p=0.031). At this threshold, combination biopsy detected 20 clinically significant prostate cancers, while standard detected 14 with 88% sensitivity and 20% specificity. Excluding targeted biopsy in setting of a positive digital rectal exam would save 12.3% magnetic resonance imaging and miss 1.8% clinically significant cancers in our cohort.

CONCLUSIONS

In biopsy-naïve patients, at prostate-specific antigen >4.3, there is a significant increase in clinically significant prostate cancer detection when targeted biopsy is added to standard biopsy. Obtaining standard biopsy alone in patients with abnormal digital rectal examinations would miss 1.8% clinically significant cancers in our cohort.

Detection of Single Cancer Cells in Blood with Artificially Intelligent Nanoarray

Detection and monitoring of single cancer cells (SCCs), such as circulating tumor cells (CTCs), would be of aid in an efficient early detection of cancer, a tailored (personalized) therapy, and in a fast bedside assessment of treatment efficacy. Nevertheless, currently available techniques, which mostly rely on the isolation of SCCs based on their physical or biological properties, suffer from low sensitivity, complicated technical procedures, low cost-effectiveness, and being unsuitable for continuous monitoring. We report here on the design and use of an artificially intelligent nanoarray based on a heterogeneous set of chemisensitive nanostructured films for the detection of SCCs using volatile organic compounds emanating in the air trapped above blood samples containing SCCs. For demonstration purposes, we have focused on samples containing A549 lung cancer cells (hereafter, SCC^A549). The nanoarray developed to detect SCC^A549 has >90% accuracy, >85% sensitivity, and >95% specificity. Detection works irrespective of the medium and/or the environment. These results were validated by complementary mass spectrometry. The ability to continuously record, store, and preprocess the signals increases the chances that this nanotechnology might also be useful in the early detection of cancer cells in the blood and continuous monitoring of their possible progression.

Delivering Clinical impacts of the MRI diagnostic pathway in prostate cancer diagnosis

Pre-biopsy multiparametric MRI is now recommended by multiple guidelines, not only for men with persistent suspicion of prostate cancer after prior negative systematic biopsy, but also at initial screening before the first biopsy. The major benefit of pre-biopsy MRI in the diagnostic work-up is to promote individualized risk-adapted approaches for biopsy-decision management. Multiple MRI-directed diagnostic pathways can be conceived, with each approach having net-benefit trade-offs between benefits and harms, based on improved diagnostic yields of significant cancers and reduced biopsy testing and reduced detection of indolent prostate cancer. In this paper, we illustrate how clinical benefits can be maximized in men with MRI-negative and MRI-positive results, using the PI-RADS Multiparametric MRI and MRI-directed biopsy pathway. From a practice perspective, we emphasize five golden rules: (1) that multiparametric MRI approach including targeted biopsies be reserved for men likely to benefit from early detection and treatment of prostate cancer; (2) that there is a need to carefully assess risk of significant disease using PSA and clinical parameters before and after MRI; (3) do not offer immediate biopsy if the MRI is negative, unless other high-risk factors are present; (4) accept that not all significant cancers are found immediately and have robust ‘safety nets’ for men with negative MRI scans who avoid immediate biopsy and for positive MRI patients with negative or non-explanatory histology; and (5) use MRI-directed biopsy methods that minimize overdiagnosis and improve risk stratification.

A multifaceted approach to quality in the MRI-directed biopsy pathway for prostate cancer diagnosis

KEY POINTS

• Identify, assure, and measure major sources of variability affecting the MRI-directed biopsy pathway for prostate cancer diagnosis.• Develop strategies to control and minimize variations that impair pathway effectiveness including the performance of main players and team working.• Assure end-to-end quality of the diagnostic chain with robust multidisciplinary team working.

Indications for and complications of pelvic lymph node dissection in prostate cancer: accuracy of available nomograms for the prediction of lymph node invasion

OBJECTIVES

To externally validate the currently available nomograms for predicting lymph node invasion (LNI) in patients with prostate cancer (PCa) and to assess the potential risk of complications of extended pelvic lymph node dissection (ePLND) when using the recommended threshold.

METHODS

A total of 14 921 patients, who underwent radical prostatectomy with ePLND at eight European tertiary referral centres, were retrospectively identified. After exclusion of patients with incomplete biopsy or pathological data, 12 009 were included. Of these, 609 had undergone multiparametic magnetic resonance imaging-targeted biopsies. Among ePLND-related complications we included lymphocele, lymphoedema, haemorrhage, infection and sepsis. The performances of the Memorial Sloan Kettering Cancer Centre (MSKCC), Briganti 2012, Briganti 2017, Briganti 2019, Partin 2016 and Yale models were evaluated using receiver-operating characteristic curve analysis (area under the curve [AUC]), calibration plots, and decision-curve analysis.

RESULTS

Overall, 1158 patients (9.6%) had LNI, with a mean of 17.7 and 3.2 resected and positive nodes, respectively. No significant differences in AUCs were observed between the MSKCC (0.79), Briganti 2012 (0.79), Partin 2016 (0.78), Yale (0.80), Briganti 2017 (0.81) and Briganti 2019 (0.76) models. A direct comparison of older models showed that better discrimination was achieved with the MSKCC and Briganti 2012 nomograms. A tendency for underestimation was seen for all the older models, whereas the Briganti 2017 and 2019 nomograms tended to overestimate LNI risk. Decision-curve analysis showed a net benefit for all models, with a lower net benefit for the Partin 2016 and Briganti 2019 models. ePLND-related complications were experienced by 1027 patients (8.9%), and 12.6% of patients with pN1 disease.

CONCLUSIONS

The currently available nomograms have similar performances and limitations in the prediction of LNI. Miscalibration was present, however, for all nomograms showing a net benefit. In patients with only systematic biopsy, the MSKCC and Briganti 2012 nomograms were superior in the prediction of LNI.

Personalized strategies in population screening for prostate cancer

This review discusses evidence for population-based screening with contemporary screening tools. In Europe, prostate-specific antigen (PSA)-based screening led to a relative reduction of prostate cancer (PCa) mortality, but also to a substantial amount of overdiagnosis and unnecessarily biopsies. Risk stratification based on a single variable (a clinical variable or based on the presence of a lesion on prostate imaging) or based on multivariable approaches can aid in reducing unnecessary prostate biopsies and overdiagnosis by selecting men who can benefit from further clinical assessment. Multivariable approaches include clinical variables, and biomarkers, often combined in risk calculators or nomograms. These risk calculators can also incorporate the result of MRI imaging. In general, as compared to a purely PSA based approach, the combination of relevant prebiopsy information results in superior selection of men at higher risk of harboring clinically significant prostate cancer. Currently, it is not possible to draw any conclusions on the superiority of these multivariable risk-based approaches since head-to-head comparisons are virtually lacking. Recently initiated large population-based screening studies in Finland, Germany and Sweden, incorporating various multivariable risk stratification approaches will hopefully give more insight in whether the harm-benefit ratio can be improved, that is, maintain (or improving) the ability to reduce metastatic disease and prostate cancer mortality while reducing harm caused by unnecessary testing and overdiagnosis including related overtreatment.

Clinical utility and cost modelling of the phi test to triage referrals into image-based diagnostic services for suspected prostate cancer: the PRIM (Phi to RefIne Mri) study

BACKGROUND

The clinical pathway to detect and diagnose prostate cancer has been revolutionised by the use of multiparametric MRI (mpMRI pre-biopsy). mpMRI however remains a resource-intensive test and is highly operator dependent with variable effectiveness with regard to its negative predictive value. Here we tested the use of the phi assay in standard clinical practice to pre-select men at the highest risk of harbouring significant cancer and hence refine the use of mpMRI and biopsies.

METHODS

A prospective five-centre study recruited men being investigated through an mpMRI-based prostate cancer diagnostic pathway. Test statistics for PSA, PSA density (PSAd) and phi were assessed for detecting significant cancers using 2 definitions: ≥ Grade Group (GG2) and ≥ Cambridge Prognostic Groups (CPG) 3. Cost modelling and decision curve analysis (DCA) was simultaneously performed.

RESULTS

A total of 545 men were recruited and studied with a median age, PSA and phi of 66 years, 8.0 ng/ml and 44 respectively. Overall, ≥ GG2 and ≥ CPG3 cancer detection rates were 64% (349/545), 47% (256/545) and 32% (174/545) respectively. There was no difference across centres for patient demographics or cancer detection rates. The overall area under the curve (AUC) for predicting ≥ GG2 cancers was 0.70 for PSA and 0.82 for phi. AUCs for ≥ CPG3 cancers were 0.81 and 0.87 for PSA and phi respectively. AUC values for phi did not differ between centres suggesting reliability of the test in different diagnostic settings. Pre-referral phi cut-offs between 20 and 30 had NPVs of 0.85-0.90 for ≥ GG2 cancers and 0.94-1.0 for ≥ CPG3 cancers. A strategy of mpMRI in all and biopsy only positive lesions reduced unnecessary biopsies by 35% but missed 9% of ≥ GG2 and 5% of ≥ CPG3 cancers. Using PH ≥ 30 to rule out referrals missed 8% and 5% of ≥ GG2 and ≥ CPG3 cancers (and reduced unnecessary biopsies by 40%). This was achieved however with 25% fewer mpMRI. Pathways incorporating PSAd missed fewer cancers but necessitated more unnecessary biopsies. The phi strategy had the lowest mean costs with DCA demonstrating net clinical benefit over a range of thresholds.

CONCLUSION

phi as a triaging test may be an effective way to reduce mpMRI and biopsies without compromising detection of significant prostate cancers.

External validation of Cormio nomogram for predicting all prostate cancers and clinically significant prostate cancers

PURPOSE

Recently, the Cormio et al. nomogram has been developed to predict prostate cancer (PCa) and clinically significant PCa using benign prostatic obstruction parameters. The aim of the present study was to externally validate the nomogram in a multicentric cohort.

METHODS

Between 2013 and 2019, patients scheduled for ultrasound-guided prostate biopsy were prospectively enrolled at 11 Italian institutions. Demographic, clinical and histological data were collected and analysed. Discrimination and calibration of Cormio nomogram were assessed with the receiver operator characteristics (ROC) curve and calibration plots. The clinical net benefit of the nomogram was assessed with decision curve analysis. Clinically significant PCa was defined as ISUP grade group > 1.

RESULTS

After accounting for inclusion criteria, 1377 patients were analysed. 816/1377 (59%) had cancer at final pathology (574/816, 70%, clinically significant PCa). Multivariable analysis showed age, prostate volume, DRE and post-voided residual volume as independent predictors of any PCa. Discrimination of the nomogram for cancer was 0.70 on ROC analysis. Calibration of the nomogram was excellent (p = 0.94) and the nomogram presented a net benefit in the 40-80% range of probabilities. Multivariable analysis for predictors of clinically significant PCa found age, PSA, prostate volume and DRE as independent variables. Discrimination of the nomogram was 0.73. Calibration was poor (p = 0.001) and the nomogram presented a net benefit in the 25-75% range of probabilities.

CONCLUSION

We confirmed that the Cormio nomogram can be used to predict the risk of PCa in patients at increased risk. Implementation of the nomogram in clinical practice will better define its role in the patient's counselling before prostate biopsy.