Faculty Bibliography

PURPOSE/OBJECTIVE:The Studies of Prostate Ablation Related Energy Devices (SPARED) coordinated registry network (CRN) is a private-public partnership between academic and community urologists, the US Food and Drug Administration (FDA), Medical Device Epidemiology Network (MDEpiNet) and device manufacturers to examine safety and effectiveness of technologies for partial gland ablation (PGA) in men with localized prostate cancer. MATERIALS AND METHODS/METHODS:We report on a recent workshop at the FDA with thought leaders to discuss a critical framework for PGA, focusing on patient selection, surgical planning, follow up, study design and appropriate comparators in terms of adverse events and cancer control outcomes. We summarize salient points from experts in urology, oncology, and epidemiology that were presented and discussed in an open forum. RESULTS:Given the challenges in achieving patient and physician equipoise to conduct a randomized trial, as well as an inherent paradigm shift when comparing PGA (inability to assess PSA recurrence) to whole gland treatments, the group focused on objective performance criteria/goals (OPC/OPG) as a platform to guide the creation of single arm studies within the SPARED CRN. CONCLUSIONS:This summit lays the foundation for prospective, multi-center data collection and evaluation of novel medical devices and drug/device combinations for PGA.

BACKGROUND:Patient-specific 3D models are being used increasingly in medicine for many applications including surgical planning, procedure rehearsal, trainee education, and patient education. To date, experiences on the use of 3D models to facilitate patient understanding of their disease and surgical plan are limited. The purpose of this study was to investigate in the context of renal and prostate cancer the impact of using 3D printed and augmented reality models for patient education. METHODS:Patients with MRI-visible prostate cancer undergoing either robotic assisted radical prostatectomy or focal ablative therapy or patients with renal masses undergoing partial nephrectomy were prospectively enrolled in this IRB approved study (n = 200). Patients underwent routine clinical imaging protocols and were randomized to receive pre-operative planning with imaging alone or imaging plus a patient-specific 3D model which was either 3D printed, visualized in AR, or viewed in 3D on a 2D computer monitor. 3D uro-oncologic models were created from the medical imaging data. A 5-point Likert scale survey was administered to patients prior to the surgical procedure to determine understanding of the cancer and treatment plan. If randomized to receive a pre-operative 3D model, the survey was completed twice, before and after viewing the 3D model. In addition, the cohort that received 3D models completed additional questions to compare usefulness of the different forms of visualization of the 3D models. Survey responses for each of the 3D model groups were compared using the Mann-Whitney and Wilcoxan rank-sum tests. RESULTS:All 200 patients completed the survey after reviewing their cases with their surgeons using imaging only. 127 patients completed the 5-point Likert scale survey regarding understanding of disease and surgical procedure twice, once with imaging and again after reviewing imaging plus a 3D model. Patients had a greater understanding using 3D printed models versus imaging for all measures including comprehension of disease, cancer size, cancer location, treatment plan, and the comfort level regarding the treatment plan (range 4.60-4.78/5 vs. 4.06-4.49/5, p < 0.05). CONCLUSIONS:All types of patient-specific 3D models were reported to be valuable for patient education. Out of the three advanced imaging methods, the 3D printed models helped patients to have the greatest understanding of their anatomy, disease, tumor characteristics, and surgical procedure.

INTRODUCTION/BACKGROUND:Penectomy for PC is useful in staging, disease prognosis, and treatment. Limited studies have evaluated its surgical complications. We sought to assess these complications and determine predictive models to create a novel risk score for penectomy complications. PATIENTS AND METHODS/METHODS:A retrospective review of patients undergoing PC surgical management from the 2005-2016 American College of Surgeons National Surgical Quality Improvement Program was performed. Data were queried for partial and total penectomy among those with PC. To develop predictive models of complications, we fit LASSO logistic, random forest, and stepwise logistic models to training data using cross-validation, demographic, comorbidity, laboratory, and wound characteristics as candidate predictors. Each model was evaluated on the test data using receiver operating characteristic curves. A novel risk score was created by rounding coefficients from the LASSO logistic model. RESULTS:A total of 304 cases met the inclusion criteria. Overall incidence of penectomy complications was 19.7%, where urinary tract infection (3.0%), superficial surgical site infection (3.0%), and bleeding requiring transfusion (3.9%) were most common. LASSO logistic, random forest, and stepwise logistic models for predicting complications had area under the curve (AUC) [95% confidence interval] values of 0.66 [0.52-0.81], 0.73 [0.63-0.83], and 0.59 [0.45-0.74], respectively. Eleven variables were included in the risk score. The LASSO model-derived risk score had moderately good performance (area under the curve [95% confidence interval] 0.74 [0.66-0.82]). Using a cutoff point of 6, the score attains sensitivity 0.58, specificity 0.74, and kappa 0.26. CONCLUSION/CONCLUSIONS:PC management through penectomy is associated with appreciable complications rates. Predictive models of penectomy complications performed moderately well. Our novel prognostic risk score may allow for improved preoperative counseling and risk stratification of men undergoing surgical management of PC.

Background/UNASSIGNED:Radical cystectomy for bladder cancer has one of the highest rates of morbidity among urologic surgery, but the ability to predict postoperative complications remains poor. Our study objective was to create machine learning models to predict complications and factors leading to extended length of hospital stay and discharge to a higher level of care after radical cystectomy. Methods/UNASSIGNED:Using the American College of Surgeons National Surgical Quality Improvement Program, peri-operative adverse outcome variables for patients undergoing elective radical cystectomy for bladder cancer from 2005 to 2016 were extracted. Variables assessed include occurrence of minor, infectious, serious, or any adverse events, extended length of hospital stay, and discharge to higher-level care. To develop predictive models of radical cystectomy complications, we fit generalized additive model (GAM), least absolute shrinkage and selection operator (LASSO) logistic, neural network, and random forest models to training data using various candidate predictor variables. Each model was evaluated on the test data using receiver operating characteristic curves. Results/UNASSIGNED:A total of 7557 patients were identified who met the inclusion criteria, and 2221 complications occurred. LASSO logistic models demonstrated the highest area under curve for predicting any complications (0.63), discharge to a higher level of care (0.75), extended length of stay (0.68), and infectious (0.62) adverse events. This was comparable with random forest in predicting minor (0.60) and serious (0.63) adverse events. Conclusions/UNASSIGNED:Our models perform modestly in predicting radical cystectomy complications, highlighting both the complex cystectomy process and the limitations of large healthcare datasets. Identifying the most important variable leading to each type of adverse event may allow for further strategies to model cystectomy complications and target optimization of modifiable variables pre-operative to reduce postoperative adverse events.

PURPOSE/OBJECTIVE:While MRI-Ultrasound Fusion-targeted biopsy (MRF-TB) allows for improved detection of clinically significant prostate cancer (csPCa), concerning numbers of clinically significant disease are still missed. We hypothesize that a number of these are due to the learning curve associated with MRF-TB. We report results of repeat MRF-TB in men with continued suspicion for cancer and the institutional learning curve in detection of csPCa over time. MATERIALS AND METHODS/METHODS:Analysis of 1813 prostate biopsies in a prospectively acquired cohort of men presenting for prostate biopsy over a 4-year period. All men were offered pre-biopsy MRI and assigned a maximum Prostate Imaging - Reporting and Data System version 2 (PI-RADS) score. Biopsy outcomes of men with suspicious region of interest (ROI) were compared. The relationship between time and csPCa detection was analyzed. RESULTS:csPCa detection rate increased 26% over time in men with PI-RADS 4 and 5 (4/5) ROI. On repeat MRF-TB in men with continued suspicion for cancer, 53% of men with PI-RADS 4/5 ROI demonstrated clinically significant discordance from initial MRF-TB, compared to only 23% of men with PI-RADS 1/2 ROI. Significantly less csPCa were missed or under-graded in the most recent biopsies as compared to the earliest biopsies. CONCLUSION/CONCLUSIONS:High upgrade rates on repeat MRF-TB and increasing cancer detection rate over time demonstrate the significant learning curve associated with MRF-TB. Men with low risk or negative biopsies with persistent concerning ROI should be promptly re-biopsied. Improved targeting accuracy with operator experience can help decrease the number of missed csPCa.

BACKGROUND:The number of prostate biopsy cores that need to be taken from each magnetic resonance imaging (MRI) region of interest (ROI) to optimize sampling while minimizing overdetection has not yet been clearly elucidated. OBJECTIVE:To characterize the incremental value of additional MRI-ultrasound (US) fusion targeted biopsy cores in defining the optimal number when planning biopsy and to predict men who might benefit from more than two targeted cores. DESIGN, SETTING, AND PARTICIPANTS/METHODS:This was a retrospective cohort study of MRI-US fusion targeted biopsies between 2015 and 2017. INTERVENTION/METHODS:MRI-US fusion targeted biopsy in which four biopsy cores were directed to each MRI-targeted ROI. OUTCOMES MEASUREMENTS AND STATISTICAL ANALYSIS/UNASSIGNED:The MRI-targeted cores representing the first highest Gleason core (FHGC) and first clinically significant cancer core (FCSC; GS≥3+4) were evaluated. We analyzed the frequency of FHGC and FCSC among cores 1-4 and created a logistic regression model to predict FHGC >2. The number of unnecessary cores avoided and the number of malignancies missed for each Gleason grade were calculated via clinical utility analysis. The level of agreement between biopsy and prostatectomy Gleason scores was evaluated using Cohen's κ. RESULTS AND LIMITATIONS/CONCLUSIONS:A total of 479 patients underwent fusion targeted biopsy with four individual cores, with 615 ROIs biopsied. Among those, FHGC was core 1 in 477 (76.8%), core 2 in 69 (11.6%), core 3 in 48 (7.6%), and core 4 in 24 men (4.0%) with any cancer. Among men with clinically significant cancer, FCSC was core 1 in 191 (77.8%), core 2 in 26 (11.1%), core 3 in 17 (6.2%), and core 4 in 11 samples (4.9%). In comparison to men with a Prostate Imaging-Reporting and Data System (PI-RADS) score of 5, patients were significantly less likely to have FHGS >2 if they had PI-RADS 4 (odds ratio [OR] 0.287; p=0.006), PI-RADS 3 (OR 0.284; p=0.006), or PI-RADS 2 (OR 0.343; p=0.015). Study limitations include a single-institution experience and the retrospective nature. CONCLUSIONS:Cores 1-2 represented FHGC 88.4% and FCSC 88.9% of the time. A PI-RADS score of 5 independently predicted FHGC >2. Although the majority of cancers in our study were appropriately characterized in the first two biopsy cores, there remains a proportion of men who would benefit from additional cores. PATIENT SUMMARY/UNASSIGNED:In men who undergo magnetic resonance imaging-ultrasound fusion targeted biopsy, the first two biopsy cores diagnose the majority of clinically significant cancers. However, there remains a proportion of men who would benefit from additional cores.

OBJECTIVE:To define the rates of common Hospital Acquired Conditions (HACs) in patients undergoing major urological surgery over a period of time encompassing the implementation of the Hospital Acquired Condition Reduction program, and to evaluate whether implementation of the HAC reimbursement penalties in 2008 was associated with a change in the rate of HACs. METHODS:Using American College of Surgeons National Surgical Quality Improvement Program (NSQIP) data, we determined rates of HACs in patients undergoing major inpatient urological surgery from 2005 to 2012. Rates were stratified by procedure type and approach (open vs. laparoscopic/robotic). Multivariable logistic regression was used to determine the association between year of surgery and HACs. RESULTS:We identified 39,257 patients undergoing major urological surgery, of whom 2300 (5.9%) had at least one hospital acquired condition. Urinary tract infection (UTI, 2.6%) was the most common, followed by surgical site infection (SSI, 2.5%) and venous thrombotic events (VTE, 0.7%). Multivariable logistic regression analysis demonstrated that open surgical approach, diabetes, congestive heart failure, chronic obstructive pulmonary disease, weight loss, and ASA class were among the variables associated with higher likelihood of HAC. We observed a non-significant secular trend of decreasing rates of HAC from 7.4% to 5.8% HACs during the study period, which encompassed the implementation of the Hospital Acquired Condition Reduction Program. CONCLUSIONS:HACs occurred at a rate of 5.9% after major urological surgery, and are significantly affected by procedure type and patient health status. The rate of HAC appeared unaffected by national reduction program in this cohort. Better understanding of the factors associated with HACs is critical in developing effective reduction programs.

BACKGROUND:The American Society of Anesthesiologists physical status classification system, modified Charlson Comorbidity Index (mCCI), and modified Frailty Index have been associated with complications after urologic surgery. No study has compared the predictive performance of these indexes for postoperative complications after radical cystectomy (RC) for bladder cancer. MATERIALS AND METHODS/METHODS:Data from 1516 patients undergoing elective RC for bladder cancer were extracted from the 2005 to 2011 American College of Surgeons National Surgical Quality Improvement Program for a retrospective review. The perioperative outcome variables assessed were occurrence of minor adverse events, severe adverse events, infectious adverse events, any adverse event, extended length of hospital stay, discharge to a higher level of care, and mortality. Patient comorbidity indexes and demographic data were assessed for their discriminative ability in predicting perioperative adverse outcomes using an area under the curve (AUC) analysis from the receiver operating characteristic curves. RESULTS:The most predictive comorbidity index for any adverse event was the mCCI (AUC, 0.511). The demographic factors were the body mass index (BMI; AUC, 0.519) and sex (AUC, 0.519). However, the overall performance for all predictive indexes was poor for any adverse event (AUC < 0.52). Combining the most predictive demographic factor (BMI) and comorbidity index (mCCI) resulted in incremental improvements in discriminative ability compared with that for the individual outcome variables. CONCLUSION/CONCLUSIONS:For RC, easily obtained patient mCCI, BMI, and sex have overall similar discriminative abilities for perioperative adverse outcomes compared with the tabulated indexes, which are more difficult to implement in clinical practice. However, both the demographic factors and the comorbidity indexes had poor discriminative ability for adverse events.

INTRODUCTION/BACKGROUND:Nutritional status has been increasingly recognized as an important predictor of prognosis and surgical outcomes for cancer patients. We evaluated the effect of preoperative malnutrition on the development of surgical complications and mortality after radical nephroureterectomy (RNU) for upper tract urothelial carcinoma (UTUC). MATERIALS AND METHODS/METHODS:Using data from the American College of Surgeons National Surgical Quality Improvement Program, we evaluated the association of poor nutritional status with 30-day postoperative complications and overall mortality after RNU from 2005 to 2015. The preoperative variables suggestive of poor nutritional status included hypoalbuminemia (< 3.5 g/dL), weight loss within 6 months before surgery (> 10%), and a low body mass index. RESULTS:A total of 1200 patients were identified who had undergone RNU for UTUC. The overall complication rate was 20.5% (n = 246), and mortality rate was 1.75% (n = 21). On univariate analysis, patients who experienced a postoperative complication were more likely to have hypoalbuminemia (25.0% vs. 11.4%; P < .001) and weight loss (3.7% vs. 1.0%; P = .003). After controlling for baseline characteristics and comorbidities, hypoalbuminemia was found to be a significant independent predictor of postoperative complications (odds ratio, 2.09; 95% confidence interval, 1.29-3.38; P = .003). Hypoalbuminemia was also a significant independent predictor of mortality (odds ratio, 4.31; 95% confidence interval, 1.45-12.79; P = .008) on multivariable regression analysis. CONCLUSION/CONCLUSIONS:Our results have shown that hypoalbuminemia is a significant predictor of surgical complications and mortality after RNU for UTUC. This finding supports the importance of patients' preoperative nutritional status in this population and suggests that effective nutritional interventions in the preoperative setting could improve patient outcomes.