Faculty Bibliography

BACKGROUND:Evading immune surveillance is a hallmark for the development of multiple cancer types. Whether immune evasion contributes to the pathogenesis of high-grade prostate cancer (HGPCa) remains an area of active inquiry. METHODS:Through single-cell RNA sequencing and multicolor flow cytometry of freshly isolated prostatectomy specimens and matched peripheral blood, we aimed to characterize the tumor immune microenvironment (TME) of localized prostate cancer (PCa), including HGPCa and low-grade prostate cancer (LGPCa). RESULTS: TILs. The PCa TME was infiltrated by macrophages but these did not clearly cluster by M1 and M2 markers. CONCLUSIONS:T cell exhaustion in localized PCa, a finding enriched in HGPCa relative to LGPCa. These studies suggest a possible link between the clinical-pathologic risk of PCa and the associated TME. Our results have implications for our understanding of the immunologic mechanisms of PCa pathogenesis and the implementation of immunotherapy for localized PCa.

BACKGROUND:To identify gaps in urologic oncology quality and evidence-based smoking cessation care by assessing how often smoking cessation pharmacotherapy (SCP) is given in the inpatient setting following cystectomy. METHODS:The Premier Healthcare Database (PHD), a deidentified all-payer dataset, was used to generate nationally representative estimates of SCP receipt during hospitalization following cystectomy for patients with bladder cancer who smoke. Regressions were used to model associations between SCP receipt and patient- and hospital-level factors. RESULTS:Of the 21,624 patients who underwent cystectomy for bladder cancer, 3,676 patients (17.0%) were identified as current smokers, representing a weighted estimate of 16,063 admissions. Among these admissions, 27.9% of patients received SCP, the vast majority of which (91.5%) received exclusively nicotine replacement therapy. Rates of SCP receipt varied substantially across hospitals (median: 25.0%, IQR: 20.0-33.3, range: 0.0-60.0). Older age and black race (aOR = 0.59, 95% CI: 0.42-0.82) were associated with lower odds of SCP receipt. Increased patient comorbidity score was associated with higher odds of SCP receipt (aOR = 1.02, 95% CI: 1.01-1.03); specifically, chronic pulmonary disease, alcohol abuse, and depression were independently associated with SCP receipt. Hospital teaching status, bed capacity, and mean annual cystectomy volume were not associated with SCP receipt. SCP receipt was not associated with hospital length of stay nor 90-day readmission or mortality following cystectomy. CONCLUSIONS:SCP is infrequently given to patients who smoke during their hospitalization following cystectomy for bladder cancer, representing a gap in quality urologic oncology care and a missed opportunity to effectively intervene with evidence-based treatment.

BACKGROUND:Three-dimensional (3D) printed anatomic models can facilitate presurgical planning by providing surgeons with detailed knowledge of the exact location of pertinent anatomical structures. Although 3D printed anatomic models have been shown to be useful for pre-operative planning, few studies have demonstrated how these models can influence quantitative surgical metrics. OBJECTIVE:To prospectively assess whether patient-specific 3D printed prostate cancer models can improve quantitative surgical metrics in patients undergoing robotic-assisted radical prostatectomy (RARP). METHODS:Patients with MRI-visible prostate cancer (PI-RADS V2 ≥ 3) scheduled to undergo RARP were prospectively enrolled in our IRB approved study (n = 82). Quantitative surgical metrics included the rate of positive surgical margins (PSMs), operative times, and blood loss. A qualitative Likert scale survey to assess understanding of anatomy and confidence regarding surgical approach was also implemented. RESULTS:The rate of PSMs was lower for the 3D printed model group (8.11%) compared to that with imaging only (28.6%), p = 0.128. The 3D printed model group had a 9-min reduction in operating time (213 ± 42 min vs. 222 ± 47 min) and a 5 mL reduction in average blood loss (227 ± 148 mL vs. 232 ± 114 mL). Surgeon anatomical understanding and confidence improved after reviewing the 3D printed models (3.60 ± 0.74 to 4.20 ± 0.56, p = 0.62 and 3.86 ± 0.53 to 4.20 ± 0.56, p = 0.22). CONCLUSIONS:3D printed prostate cancer models can positively impact quantitative patient outcomes such as PSMs, operative times, and blood loss in patients undergoing RARP.

BACKGROUND:Magnetic resonance imaging (MRI)-targeted prostate biopsy has become an increasingly common method of diagnosing prostate cancer. A previous study from our institution demonstrated that the biopsy global Grade Group (gGG, aggregate GG of all positive cores) and highest Grade Group (hGG in any core) both show substantial concordance with the Grade Group at radical prostatectomy (RPGG) while the discordance predominantly consists of upgrading in gGG and downgrading in hGG. We performed a larger cohort study focused on biopsy cases in which gGG and hGG differ, to determine their relative concordance with RPGG. METHODS:We conducted a retrospective review of radical prostatectomy specimens with prior MRI-targeted biopsies from our institution between 2016 and 2020. Separate gGG and hGG were assigned to each MRI-targeted lesion. Targeted lesions with different gGG versus hGG were segregated from those with identical gGG and hGG. The concordance of biopsy GG with RPGG was evaluated using κ coefficient analysis. RESULTS:Of the 489 lesions with MRI-targeted biopsies, 82 (17%) differed in gGG versus hGG. The gGG of 46 (56%), 33 (40%), and 3 (4%) lesions were unchanged, upgraded, and downgraded at radical prostatectomy, respectively (κ= 0.302, weighted κ = 0.334). The hGG of 24 (29%), 9 (11%), and 49 (60%) lesions were unchanged, upgraded, and downgraded at radical prostatectomy, respectively (κ = 0.040, weighted κ = 0.198). When stratified by the biopsy GG, gGG showed the highest concordance in GG2 (61%) and GG3 (54%) lesions. The hGG resulted in substantial downgrading (60%) with less optimal concordance regardless of the biopsy GG. Neither the prebiopsy prostate specific antigen level nor the PI-RADS score was predictive of upgrading of gGG. CONCLUSIONS:When gGG and hGG differ, gGG method more accurately predicts the RPGG than hGG, particularly in GG2 and GG3 lesions which comprised the majority of targeted lesions.

Introduction: We aimed to determine cancer detection rates following early repeat multiparametric magnetic resonance imaging (mpMRI) and biopsy of Prostate Imaging-Reporting and Data System (PI-RADS), v2.1 4 and 5 regions of interest (ROI) exhibiting no clinically significant prostate cancer (csPCa) on prior biopsy and to identify predictors for these missed csPCa. Methods: Between January 2019 and August 2020, 36 men with 38 PI-RADS 4 or 5 ROI with no evidence of csPCa (defined as Gleason grade group [GGG] >1) on prior MRI fusion target biopsy (MRFTB) + systematic biopsy (SB) were invited to participate in the present prospective study. All men underwent repeat mpMRI and persistent PI-RADS >2 ROI were advised to undergo repeat MRFTB+SB. Cancer detection rates of any and csPCa were determined. Relative risk was calculated to analyze association of baseline variables with the finding of csPCa on repeat biopsy. Results: Of the 38 initial PI-RADS 4 and 5 ROI, on followup mpMRI, 14 were downgraded to PI-RADS 1/2 and, per protocol, did not undergo repeat biopsy and; eight (33%), 12 (50%), and four (17%) were PI-RADS 3, 4, and 5 respectively. Of these 24 persistently suspicious mpMRI ROI, 20 (83%) underwent repeat biopsy and six (30%), six (30%), and eight (40%) were benign, GGG 1, and GGG >1, respectively. Only prostate-specific antigen ≥10 ng/mL was a predictor for missed csPCa. Conclusions: Our prospective study supports a recommendation for early repeat mpMRI of all PI-RADS 4 or 5 ROI exhibiting no csPCa, with repeat MRFTB + SB of persistent PI-RADS >2 ROI .

PURPOSE/OBJECTIVE:F-Fluciclovine) PET/MRI informs the decision to perform an early repeat biopsy of PI-RADS 4/5 region of interest (ROI) exhibiting no clinically significant prostate cancer (csPCa) on initial biopsy. METHODS:This prospective study enrolled men with at least one PI-RADS 4/5 ROI on multi-parametric MRI and no csPCa on prior biopsy defined as Gleason grade group (GGG) > 1. All men underwent an Axumin PET/MRI and only-persistent PI-RADS > 2 ROI were advised to undergo a repeat biopsy. A PET cancer suspicion score (PETCSS) was internally developed to stratify PET avid lesions according to their suspicion of harboring csPCa. The sensitivity, specificity, positive (PPV) and negative predictive value (NPV) of the PETCSS for predicting csPCa were assessed. Relative risk was calculated to analyze the association of baseline variables with csPCa on repeat biopsy. RESULTS:Thirty-eight ROI on 36 enrolled men were analyzed. Fourteen (36.8%) were downgraded to PI-RADS 1/2 and were not subjected to repeat biopsy. Thirteen (92.9%) of these downgraded scans also exhibited low-risk PETCSS. Overall, 18/22 (81.2%) subjects underwent a repeat per protocol biopsy. Of the 20 ROI subjected to repeat biopsy, eight (40%) were found to harbour csPCa. The sensitivity, specificity, PPV and NPV of the PETCSS were 50, 50, 40, and 60%, respectively. No predictor of csPCa was found in the risk analysis. CONCLUSION/CONCLUSIONS:Our pilot study showed that both MRI and PET sequences have limited performance for identifying those persistently suspicious PI-RADS 4/5 ROI that are found to harbor csPCa on repeat biopsy.

PURPOSE/OBJECTIVE:Timely and appropriate discharge placement for patients who have undergone radical cystectomy (RC) remains challenging. Our objective was to improve the discharge planning process by creating a machine learning model that helps to predict the need for non-home hospital discharge to a higher level of care. MATERIALS AND METHODS/METHODS:Patients undergoing elective radical cystectomy for bladder cancer from 2014-2019 were identified in the ACS-NSQIP database. A gradient boosted decision tree was trained on selected predischarge variables to predict discharge location, dichotomized into home and non-home. We used threshold-moving to calibrate model predictions and evaluated model performance on a testing set using receiver operating characteristic and precision recall curves. Model performance was further examined in subgroups of interest. RESULTS AND CONCLUSIONS/CONCLUSIONS:A total of 11,881 patients met inclusion criteria with a mean age of 68.6 years. 10.6% of patients undergoing RC had non-home discharges. Our model predicting non-home discharge achieved an area under the receiver operating characteristic curve of 0.80 and an average precision of 0.33. After threshold-moving, our model had a recall of 0.757 and a precision of 0.211. Top variables by importance were septic shock occurrence, ventilator-use greater than 48 hours, organ space surgical site infection and unplanned intubation. Our model shows strong performance in identifying patients who required non-home discharge to higher levels of care, outperforming commonly used clinical indices and prior work. Modern machine learning techniques may be applied to support more timely and appropriate clinical decision making.

Purpose/UNASSIGNED:The goal of partial gland ablation (PGA) is to eradicate focal lesions of clinically significant prostate cancer (csPCa) with minimal adverse impact on functional outcomes. The primary objective of this study is to characterize the performance of 18F-Fluciclovine PET imaging for detection of prostate cancer following PGA. Materials and Methods/UNASSIGNED:Subjects 2 years following primary partial gland cryoablation (PPGCA) were invited to participate in an IRB-approved study providing they met the following inclusion criteria: a single reported mpMRI region of interest (ROI) concordant with biopsy Gleason Grade Group (GGG) < 4, no gross extra-prostatic extension on mpMRI, and no GGG > 1 or GGG 1 with a core length > 6 mm on contralateral systematic biopsy. 18F-Fluciclovine PET MRI imaging of the prostate was performed followed by in and out-of-field biopsies. Results/UNASSIGNED:Twenty-seven men who met eligibility criteria participated in the prospective study. In-field and out-of-field csPCa recurrence rate was 7.4% and 22.2%, respectively. The sensitivity and positive predictive value of mpMRI and PET imaging did not reach performance to reliably inform who should undergo prostate biopsy. Conclusion/UNASSIGNED:At 2 years following PPGCA, the rate of in-field csPCa was exceedingly low indicating a limited role for imaging to inform in-field biopsy decisions. The csPCa detection rate of out-of-field recurrence was 22% which provides an opportunity for imaging to inform out-of-field biopsy decisions. Based on our findings, 18F-Fluciclovine PET MRI cannot be used to inform who should undergo out-of-field prostate biopsy at 2 years following PPGCA.