External validation of nomograms including MRI features for the prediction of side-specific extraprostatic extension

BACKGROUND

Prediction of side-specific extraprostatic extension (EPE) is crucial in selecting patients for nerve-sparing radical prostatectomy (RP). Multiple nomograms, which include magnetic resonance imaging (MRI) information, are available predict side-specific EPE. It is crucial that the accuracy of these nomograms is assessed with external validation to ensure they can be used in clinical practice to support medical decision-making.

METHODS

Data of prostate cancer (PCa) patients that underwent robot-assisted RP (RARP) from 2017 to 2021 at four European tertiary referral centers were collected retrospectively. Four previously developed nomograms for the prediction of side-specific EPE were identified and externally validated. Discrimination (area under the curve [AUC]), calibration and net benefit of four nomograms were assessed. To assess the strongest predictor among the MRI features included in all nomograms, we evaluated their association with side-specific EPE using multivariate regression analysis and Akaike Information Criterion (AIC).

RESULTS

This study involved 773 patients with a total of 1546 prostate lobes. EPE was found in 338 (22%) lobes. The AUCs of the models predicting EPE ranged from 72.2% (95% CI 69.1-72.3%) (Wibmer) to 75.5% (95% CI 72.5-78.5%) (Nyarangi-Dix). The nomogram with the highest AUC varied across the cohorts. The Soeterik, Nyarangi-Dix, and Martini nomograms demonstrated fair to good calibration for clinically most relevant thresholds between 5 and 30%. In contrast, the Wibmer nomogram showed substantial overestimation of EPE risk for thresholds above 25%. The Nyarangi-Dix nomogram demonstrated a higher net benefit for risk thresholds between 20 and 30% when compared to the other three nomograms. Of all MRI features, the European Society of Urogenital Radiology score and tumor capsule contact length showed the highest AUCs and lowest AIC.

CONCLUSION

The Nyarangi-Dix, Martini and Soeterik nomograms resulted in accurate EPE prediction and are therefore suitable to support medical decision-making.

The current role of precision surgery in oligometastatic prostate cancer

Oligometastatic prostate cancer (omPCa) is a novel intermediate disease state characterized by a limited volume of metastatic cells and specific locations. Accurate staging is paramount to unmask oligometastatic disease, as provided by prostate-specific membrane antigen-positron emission tomography. Driven by the results of prospective trials employing conventional and/or modern staging modalities, the treatment landscape of omPCa has rapidly evolved over the last years. Several treatment-related questions comprising the concept of precision strikes are under development. For example, beyond systemic therapy, cohort studies have found that cytoreductive radical prostatectomy (CRP) can confer a survival benefit in select patients with omPCa. More importantly, CRP has been consistently shown to improve long-term local symptoms when the tumor progresses across disease states due to resistance to systemic therapies. Metastasis-directed treatments have also emerged as a promising treatment option due to the visibility of oligometastatic disease and new technologies as well as treatment strategies to target the novel PCa colonies. Whether metastases are present at primary cancer diagnosis or detected upon biochemical recurrence after treatment with curative intent, targeted yet decisive elimination of disseminated tumor cell hotspots is thought to improve survival outcomes. One such strategy is salvage lymph node dissection in oligorecurrent PCa which can alter the natural history of progressive PCa. In this review, we will highlight how refinements in modern staging modalities change the classification and treatment of (oligo-)metastatic PCa. Further, we will also discuss the current role and future directions of precision surgery in omPCa.

1459 Intravesical Chemohyperthermia Versus Bacillus Calmette-Guerin Instillation for Intermediate- And High-Risk Non-Muscle Invasive Bladder Cancer: A Systematic Review and Meta-Analysis

Introduction

Traditional intravesical chemotherapy instillations under room temperature post trans-urethral resection (TUR) of non-muscle invasive bladder cancer (NMIBC) have lower efficacies than maintenance BCG installations. Intravesical chemo-hyperthermia (CHT) at higher temperatures is developed to improve the efficacy of chemotherapy instillation. This systematic review aims to compare the use of CHT and BCG instillation post-TUR.

Method

The protocol of this review is registered on PROSPERO(CRD42020223277). A comprehensive literature search was performed on Medline, EMBASE, and Cochrane CENTRAL to identify studies comparing CHT and BCG post-TUR for intermediate- or high-risk NMIBC. Primary outcomes include recurrence-free survival (RFS) and progression-free survival (PFS). Secondary outcomes include adverse events (AE).

Results

From 2,375 identified records, four randomised control trials incorporating 327 patients were included for meta-analysis. The use of CHT was found to be non-inferior to BCG in RFS, PFS and AEs (Grades 1-3) (p > 0.05). Sensitivity analysis, excluding patients with BCG failures, show 24-36 months recurrence rate to be significantly lower in CHT group (RR 0.64, 95% CI 0.42-0.98, p = 0.04) compared to the BCG group. In patients without carcinoma in situ (CIS), RFS is also significantly better in CHT patients (HR 0.52, 95% CI 0.32- 0.85, p < 0.01). Safety profile remains non-inferior to the BCG group in sensitivity analyses. Quality of evidence across all outcomes ranged from moderate to low.

Conclusions

In well-selected patients, intravesical CHT has superior oncological outcomes and non-inferior safety profile when compared to BCG maintenance therapy for patients with intermediate- and high-risk NMIBC. CHT is a possible alternative treatment during BCG shortage.

Outcome of immune checkpoint inhibitors in metastatic renal cell carcinoma across different treatment lines

BACKGROUND

Immune checkpoint inhibitors (ICIs) have led to a paradigm change in the management of metastatic renal cell carcinoma (mRCC). Prospective trials have focused on ICI treatment in the first or second line. The aim of this analysis is to evaluate the benefit of ICI across different treatment lines.

PATIENTS AND METHODS

This is a single-center retrospective study that included mRCC patients who received ICIs in various treatment lines. Objective response rates (ORR), progression-free survival (PFS) and overall survival (OS) were evaluated.

RESULTS

Ninety-four patients were eligible for full evaluation. Patients were classified as International mRCC Database Consortium (IMDC) risk group categorization as good, intermediate and poor risk in 26.8%, 61.6% and 14.8% of cases, respectively. They were treated with ICI monotherapy, dual ICI therapy and ICI + tyrosine kinase inhibitor in 59%, 20% and 21% of cases, respectively. ORR, median PFS and OS for the entire cohort was 39.4%, 9.67 months [95% confidence interval (CI) 6.9-12.4 months] and 23.6 months (95% CI 13.3-33.9 months), respectively. The ORR by treatment line was 33% in first, 40.4% in the second, 35% in the third and 43.5% in the fourth line and beyond. Median PFS by treatment line was 8.6, 10.3, 7.9 and 7.23 months, respectively. The median OS was not reached in first-line treatment and was 26.2, 18.1 and 20.7 months in the second, third and fourth line and beyond, respectively.

CONCLUSIONS

ICIs or ICI combinations are active in all treatment lines and should also be offered in heavily pretreated patients. Patient selection based on tumor and patient factors allows for maximal benefit from ICI-based therapies.

Risk factors for residual disease at re-TUR in a large cohort of T1G3 patients

INTRODUCTION AND OBJECTIVES

The goals of transurethral resection of a bladder tumor (TUR) are to completely resect the lesions and to make a correct diagnosis in order to adequately stage the patient. It is well known that the presence of detrusor muscle in the specimen is a prerequisite to minimize the risk of under staging. Persistent disease after resection of bladder tumors is not uncommon and is the reason why the European Guidelines recommended a re-TUR for all T1 tumors. It was recently published that when there is muscle in the specimen, re-TUR does not influence progression or cancer specific survival. We present here the patient and tumor factors that may influence the presence of residual disease at re-TUR.

MATERIAL AND METHODS

In our retrospective cohort of 2451 primary T1G3 patients initially treated with BCG, pathology results for 934 patients (38.1%) who underwent re-TUR are available. 74% had multifocal tumors, 20% of tumors were more than 3 cm in diameter and 26% had concomitant CIS. In this subgroup of patients who underwent re-TUR, there was no residual disease in 267 patients (29%) and residual disease in 667 patients (71%): Ta in 378 (40%) and T1 in 289 (31%) patients. Age, gender, tumor status (primary/recurrent), previous intravesical therapy, tumor size, tumor multi-focality, presence of concomitant CIS, and muscle in the specimen were analyzed in order to evaluate risk factors of residual disease at re-TUR, both in univariate analyses and multivariate logistic regressions.

RESULTS

The following were not risk factors for residual disease: age, gender, tumor status and previous intravesical chemotherapy. The following were univariate risk factors for presence of residual disease: no muscle in TUR, multiple tumors, tumors > 3 cm, and presence of concomitant CIS. Due to the correlation between tumor multi-focality and tumor size, the multivariate model retained either the number of tumors or the tumor diameter (but not both), p < 0.001. The presence of muscle in the specimen was no longer significant, while the presence of CIS only remained significant in the model with tumor size, p < 0.001.

CONCLUSIONS

The most significant factors for a higher risk of residual disease at re-TUR in T1G3 patients are multifocal tumors and tumors more than 3 cm. Patients with concomitant CIS and those without muscle in the specimen also have a higher risk of residual disease.

Supervised machine learning enables non-invasive lesion characterization in primary prostate cancer with [68Ga]Ga-PSMA-11 PET/MRI

PURPOSE

Risk classification of primary prostate cancer in clinical routine is mainly based on prostate-specific antigen (PSA) levels, Gleason scores from biopsy samples, and tumor-nodes-metastasis (TNM) staging. This study aimed to investigate the diagnostic performance of positron emission tomography/magnetic resonance imaging (PET/MRI) in vivo models for predicting low-vs-high lesion risk (LH) as well as biochemical recurrence (BCR) and overall patient risk (OPR) with machine learning.

METHODS

Fifty-two patients who underwent multi-parametric dual-tracer [18F]FMC and [68Ga]Ga-PSMA-11 PET/MRI as well as radical prostatectomy between 2014 and 2015 were included as part of a single-center pilot to a randomized prospective trial (NCT02659527). Radiomics in combination with ensemble machine learning was applied including the [68Ga]Ga-PSMA-11 PET, the apparent diffusion coefficient, and the transverse relaxation time-weighted MRI scans of each patient to establish a low-vs-high risk lesion prediction model (MLH). Furthermore, MBCR and MOPR predictive model schemes were built by combining MLH, PSA, and clinical stage values of patients. Performance evaluation of the established models was performed with 1000-fold Monte Carlo (MC) cross-validation. Results were additionally compared to conventional [68Ga]Ga-PSMA-11 standardized uptake value (SUV) analyses.

RESULTS

The area under the receiver operator characteristic curve (AUC) of the MLH model (0.86) was higher than the AUC of the [68Ga]Ga-PSMA-11 SUVmax analysis (0.80). MC cross-validation revealed 89% and 91% accuracies with 0.90 and 0.94 AUCs for the MBCR and MOPR models respectively, while standard routine analysis based on PSA, biopsy Gleason score, and TNM staging resulted in 69% and 70% accuracies to predict BCR and OPR respectively.

CONCLUSION

Our results demonstrate the potential to enhance risk classification in primary prostate cancer patients built on PET/MRI radiomics and machine learning without biopsy sampling.