The role of Prostate Imaging Reporting and Data System score in Gleason 3 + 3 active surveillance candidates enrollment: a diagnostic meta-analysis

Machine learning prediction of Gleason grade group upgrade between in-bore biopsy and radical prostatectomy pathology

This study aimed to enhance the accuracy of Gleason grade group (GG) upgrade prediction in prostate cancer (PCa) patients who underwent MRI-guided in-bore biopsy (MRGB) and radical prostatectomy (RP) through a combined analysis of prebiopsy and MRGB clinical data. A retrospective analysis of 95 patients with prostate cancer diagnosed by MRGB was conducted where all patients had undergone RP. Among the patients, 64.2% had consistent GG results between in-bore biopsies and RP, whereas 28.4% had upgraded and 7.4% had downgraded results. GG1 biopsy results, lower biopsy core count, and fewer positive cores were correlated with upgrades in the entire patient group. In patients with GG > 1 , larger tumor sizes and fewer biopsy cores were associated with upgrades. By integrating MRGB data with prebiopsy clinical data, machine learning (ML) models achieved 85.6% accuracy in predicting upgrades, surpassing the 64.2% baseline from MRGB alone. ML analysis also highlighted the value of the minimum apparent diffusion coefficient ( ADC min ) for GG > 1 patients. Incorporation of MRGB results with tumor size, ADC min value, number of biopsy cores, positive core count, and Gleason grade can be useful to predict GG upgrade at final pathology and guide patient selection for active surveillance.

The current role of MRI for guiding active surveillance in prostate cancer

Active surveillance (AS) is the recommended treatment option for low-risk and favourable intermediate-risk prostate cancer management, preserving oncological and functional outcomes. However, active monitoring using relevant parameters in addition to the usual clinical, biological and pathological considerations is necessary to compensate for initial undergrading of the tumour or to detect early progression without missing the opportunity to provide curative therapy. Indeed, several studies have raised concerns about inadequate biopsy sampling at diagnosis. However, the implementation of baseline MRI and targeted biopsy have led to improved initial stratification of low-risk disease; baseline MRI correlates well with disease characteristics and AS outcomes. The use of follow-up MRI during the surveillance phase also raises the question of the requirement for serial biopsies in the absence of radiological progression and the possibility of using completely MRI-based surveillance, with triggers for biopsies based solely on MRI findings. This concept of a tailored-risk, imaging-based monitoring strategy is aimed at reducing invasive procedures. However, the abandonment of serial biopsies in the absence of MRI progression can probably not yet be recommended in routine practice, as the data from real-life cohorts are heterogeneous and inconclusive. Thus, the evolution towards a routine, fully MRI-guided AS pathway has to be preceded by ensuring quality programme assessment for MRI reading and by demonstrating its safety in prospective trials.

Diagnostic Accuracy of Contemporary Selection Criteria in Prostate Cancer Patients Eligible for Active Surveillance: A Bayesian Network Meta-Analysis

Background

Several active surveillance (AS) criteria have been established to screen insignificant prostate cancer (insigPCa, defined as organ confined, low grade and small volume tumors confirmed by postoperative pathology). However, their comparative diagnostic performance varies. The aim of this study was to compare the diagnostic accuracy of contemporary AS criteria and validate the absolute diagnostic odds ratio (DOR) of optimal AS criteria.

Methods

First, we searched Pubmed and performed a Bayesian network meta-analysis (NMA) to compare the diagnostic accuracy of contemporary AS criteria and obtained a relative ranking. Then, we searched Pubmed again to perform another meta-analysis to validate the absolute DOR of the top-ranked AS criteria derived from the NMA with two endpoints: insigPCa and favorable disease (defined as organ confined, low grade tumors). Subgroup and meta-regression analyses were conducted to identify any potential heterogeneity in the results. Publication bias was evaluated.

Results

Seven eligible retrospective studies with 3,336 participants were identified for the NMA. The diagnostic accuracy of AS criteria ranked from best to worst, was as follows: Epstein Criteria (EC), Yonsei criteria, Prostate Cancer Research International: Active Surveillance (PRIAS), University of Miami (UM), University of California-San Francisco (UCSF), Memorial Sloan-Kettering Cancer Center (MSKCC), and University of Toronto (UT). I² = 50.5%, and sensitivity analysis with different insigPCa definitions supported the robustness of the results. In the subsequent meta-analysis of DOR of EC, insigPCa and favorable disease were identified as endpoints in ten and twenty-two studies, respectively. The pooled DOR for insigPCa and favorable disease were 0.44 (95%CI, 0.31–0.58) and 0.66 (95%CI, 0.61–0.71), respectively. According to a subgroup analysis, the DOR for favorable disease was significantly higher in US institutions than that in other regions. No significant heterogeneity or evidence of publication bias was identified.

Conclusions

Among the seven AS criteria evaluated in this study, EC was optimal for positively identifying insigPCa patients. The pooled diagnostic accuracy of EC was 0.44 for insigPCa and 0.66 when a more liberal endpoint, favorable disease, was used.

Systematic Review Registration

[https://www.crd.york.ac.uk/prospero/], PROSPERO [CRD42020157048].

The Impact of Visible Tumor (PI-RADS ≥ 3) on Upgrading and Adverse Pathology at Radical Prostatectomy in Low Risk Prostate Cancer Patients: A Biopsy Core Based Analysis

BACKGROUND

The objective of this study was to investigate the impact of the characteristics of a single visible tumor (Prostate Imaging-Reporting and Data System [PI-RADS]≥3) on upgrading and adverse pathology at radical prostatectomy (RP) in biopsy naïve low risk prostate cancer (PCa) patients.

MATERIALS AND METHODS

We retrospectively reviewed 64 biopsy naïve patients from 3 different referral centers between 2018 and 2020 with a PSA<10, cT1c disease, a single PI-RADS≥ 3 index lesion in multiparametric-MRI (mp-MRI), all bearing a GG 1 tumor sampled software fusion biopsy, who underwent RP. Preoperative clinical variables including the localization, number and tumor burden of positive cores for each PI-RADS category were related to upgrading and adverse pathology (GG>2 and/or pT3 and/or lymph node positive disease) at RP.

RESULTS

Overall 37 patients (57.8%) were upgraded with a significant difference of upgrading in PI-RADS3 (30.0%) versus PI-RADS 4 (67.6%) (P = .007) and PI-RADS 4-5 (70.5%) lesions (P = .002). Thirty-three of 37 GG1 tumors were upgraded to GG2, while 6 of these 33 (18.2%) had adverse pathology as well. Overall 9 patients (14.1%) had adverse pathology at RP all harboring PI-RADS4-5 lesions. The number of positive cores differed significantly between the upgraded and nonupgraded patients. Adverse pathology group had significantly higher tumor volume at RP.

CONCLUSION

PI-RADS4-5 lesions are the independent predictors of upgrading and adverse pathology in low risk PCa with visible tumors. Upgrading and adverse pathology were closely related to the number of positive combined cores reflecting the role of tumor volume. This should be kept in mind in shared decision making of an individual patient with low risk disease and a visible tumor.

MRI-derived radiomics model for baseline prediction of prostate cancer progression on active surveillance

Nearly half of patients with prostate cancer (PCa) harbour low- or intermediate-risk disease considered suitable for active surveillance (AS). However, up to 44% of patients discontinue AS within the first five years, highlighting the unmet clinical need for robust baseline risk-stratification tools that enable timely and accurate prediction of tumour progression. In this proof-of-concept study, we sought to investigate the added value of MRI-derived radiomic features to standard-of-care clinical parameters for improving baseline prediction of PCa progression in AS patients. Tumour T2-weighted imaging (T2WI) and apparent diffusion coefficient radiomic features were extracted, with rigorous calibration and pre-processing methods applied to select the most robust features for predictive modelling. Following leave-one-out cross-validation, the addition of T2WI-derived radiomic features to clinical variables alone improved the area under the ROC curve for predicting progression from 0.61 (95% confidence interval [CI] 0.481-0.743) to 0.75 (95% CI 0.64-0.86). These exploratory findings demonstrate the potential benefit of MRI-derived radiomics to add incremental benefit to clinical data only models in the baseline prediction of PCa progression on AS, paving the way for future multicentre studies validating the proposed model and evaluating its impact on clinical outcomes.

Advances in the selection of patients with prostate cancer for active surveillance

Early identification and management of prostate cancer completely changed with the discovery of prostate-specific antigen. However, improved detection has also led to overdiagnosis and consequently overtreatment of patients with low-risk disease. Strategies for the management of patients using active surveillance - the monitoring of clinically insignificant disease until intervention is warranted - were developed in response to this issue. The success of this approach is critically dependent on the accurate selection of patients who are predicted to be at the lowest risk of prostate cancer mortality. The Epstein criteria for clinically insignificant prostate cancer were first published in 1994 and have been repeatedly validated for risk-stratification and selection for active surveillance over the past few decades. Current active surveillance programmes use modified criteria with 30-50% of patients receiving treatment at 10 years. Nonetheless, tools for prostate cancer diagnosis have continued to evolve with improvements in biopsy format and targeting, advances in imaging technologies such as multiparametric MRI, and the identification of serum-, tissue- and urine-based biomarkers. These advances have the potential to further improve the identification of men with low-risk disease who can be appropriately managed using active surveillance.

Complementing the active surveillance criteria with multiparametric magnetic resonance imaging

PURPOSE

To evaluate the usefulness of multiparametric magnetic resonance imaging (mpMRI) to avoid misclassification of patients with clinically significant prostate cancer (PCa) into active surveillance (AS).

MATERIALS AND METHODS

Patients with Gleason grade group (GG) 1 PCa on systematic biopsy who underwent mpMRI before radical prostatectomy (RP) were included. mpMRI and pathologic results were compared between the AS and NOT-AS candidates. Unfavorable disease was defined as the identification of T3-4 disease or GG upgrade in the RP specimen. We established an ideal cutoff Prostate Imaging Reporting and Data System (PI-RADS) score for predicting unfavorable disease, and analyzed the location of index lesions on mpMRI.

RESULTS

PI-RADS scores were not significantly different between AS candidates (n=64) and NOT-AS candidates (n=136; p=0.629). Among 64 AS candidates, GG upgrading and unfavorable disease were diagnosed after RP in 24 (37.5%) and 25 (39.1%) patients, respectively. The rate of unfavorable disease was greater for patients with a PI-RADS score of 5 (83.3%) than in those with a score ≤4 (34.5%; p=0.030). Moreover, most PI-RADS 5 lesions in AS candidates were located in the anterior half of the prostate, with GG upgrading on targeted biopsy in 75.0% of cases.

CONCLUSIONS

Among the patients with GG 1 PCa, PI-RADS scores did not differ significantly between AS and NOT-AS candidates. Nonetheless, AS candidates with PI-RADS 5 lesions were diagnosed with unfavorable disease in >80% of RP specimens. Significant cancer located in the anterior half of the prostate including the transitional zone can be missed by systematic biopsy.

Five-year Outcomes of Magnetic Resonance Imaging-based Active Surveillance for Prostate Cancer: A Large Cohort Study

Background

Although the use of multiparametric magnetic resonance imaging (mpMRI) in active surveillance (AS) for prostate cancer is of increasing interest, existing data are derived from small cohorts.

Objective

We describe clinical, histological, and radiological outcomes from an established AS programme, where protocol-based biopsies were omitted in favour of MRI-led monitoring.

Design, setting, and participants

Data on 672 men enrolled in AS between August 2004 and November 2017 (inclusion criteria: Gleason 3 + 3 or 3 + 4 localised prostate cancer, presenting prostate-specific antigen <20 ng/ml, and baseline mpMRI) were collected from the University College London Hospital (UCLH) database.

Outcome measurements and statistical analysis

Primary outcomes were event-free survival (EFS; event defined as prostate cancer treatment, transition to watchful waiting, or death) and treatment-free survival (TFS). Secondary outcomes included rates of all-cause or prostate cancer–related mortality, metastasis, and upgrading to Gleason ≥4 + 3. Data on radiological and histological progression were also collected.

Results and limitations

More than 3800 person-years (py) of follow-up were accrued (median: 58 mo; interquartile range 37–82 mo). Approximately 84.7% (95% confidence interval [CI]: 82.0–87.6) and 71.8% (95% CI: 68.2–75.6) of patients remained on AS at 3 and 5 yr, respectively. EFS and TFS were lower in those with MRI-visible (Likert 4–5) disease or secondary Gleason pattern 4 at baseline (log-rank test; p <  0.001). In total, 216 men were treated. There were 24 deaths, none of which was prostate cancer related (6.3/1000 py; 95% CI: 4.1–9.5). Metastases developed in eight men (2.1 events/1000 py; 95% CI: 1.0–4.3), whereas 27 men upgraded to Gleason ≥4 + 3 on follow-up biopsy (7.7 events/1000 py; 95% CI: 5.2–11.3).

Conclusions

The rates of discontinuation, mortality, and metastasis in MRI-led surveillance are comparable with those of standard AS. MRI-visible disease and/or secondary Gleason grade 4 at baseline are associated with a greater likelihood of moving to active treatment at 5 yr. Further research will concentrate on optimising imaging intervals according to baseline risk.

Patient summary

In this report, we looked at the outcomes of magnetic resonance imaging (MRI)-based surveillance for prostate cancer in a UK cohort. We found that this strategy could allow routine biopsies to be avoided. Secondary Gleason pattern 4 and MRI visibility are associated with increased rates of treatment. We conclude that MRI-based surveillance should be considered for the monitoring of small prostate tumours.

Utility of Multiparametric Magnetic Resonance Imaging With PI-RADS, Version 2, in Patients With Prostate Cancer Eligible for Active Surveillance: Which Radiologic Characteristics Can Predict Unfavorable Disease?

BACKGROUND

We investigated the utility of multiparametric magnetic resonance imaging (mpMRI) using Prostate Imaging Reporting and Data System, version 2 (PI-RADSv2), scoring in patients with prostate cancer eligible for active surveillance (AS).

MATERIALS AND METHODS

The medical records of the patients who had undergone mpMRI before radical prostatectomy from 2014 to 2018 were reviewed. All the patients had met the Prostate Cancer Research International AS criteria. PI-RADSv2 scores were assigned to 12 prostate regions. Unfavorable disease was stratified using the American Joint Committee on Cancer (AJCC) prognostic scale as stage IIB (Gleason score [GS], 3+4 and pathologic stage T2) and IIC-III (GS, ≥ 4+3 or pathologic stage T3).

RESULTS

Of 376 eligible patients, 184 (48.9%), 129 (34.3%), and 63 (16.8%) had AJCC stage I, IIB, and IIC-III disease, respectively. The patients with IIC-III disease were older and had a higher prostate-specific antigen density than those with stage I or IIB disease. PI-RADS 5 lesions were more frequent in patients with stage IIC-III than in patients with stage I or IIB disease. Multivariable analysis revealed that ≥ 2 lesions with a PI-RADS 5 score was an independent predictor for unfavorable disease (hazard ratio [HR], 3.612; P < .001 for IIB; HR, 6.562; P < .001 for IIC-III), and PI-RADS score of ≥ 4 was limited for predicting AJCC stage IIB disease (HR, 2.387; P = .01).

CONCLUSION

mpMRI with PI-RADSv2 showed high negative predictive value for patients with prostate cancer eligible for AS. Multiple PI-RADS 4-5 lesions were associated with unfavorable disease compared with solitary lesions. Multiple PI-RADS 5 lesions were strongly associated with GS ≥ 4+3 or pathologic T3 disease. Targeted biopsy or radical treatment should be considered for these patients.