Longitudinal Tumor-informed Circulating Tumor DNA Status Predicts Disease Upstaging and Poor Prognosis for Patients Undergoing Radical Cystectomy.

BACKGROUND AND OBJECTIVE: Decision-making on the use of neoadjuvant and adjuvant treatment for patients with bladder cancer undergoing radical cystectomy (RC) currently depends on assessment of clinical and pathological features, which lack sensitivity. Circulating tumor DNA (ctDNA) has emerged as a possible novel prognostic biomarker in the field. Our aim was to assess whether ctDNA status before RC is predictive of pathological and oncological outcomes. We also evaluated the dynamic changes in ctDNA status after RC in relation to recurrence-free survival (RFS). METHODS: We analyzed data for patients who underwent RC during 2021-2023 for whom prospective tumor-informed ctDNA analyses were conducted before and after RC. RFS was evaluated using the Kaplan-Meier method. Predictors for disease recurrence were assessed using Cox proportional-hazards models. Pathological outcomes associated with detectable ctDNA before RC were assessed in univariable and multivariable regression analyses. KEY FINDINGS AND LIMITATIONS: We included 112 patients in the analysis. Median follow-up was 8 mo (interquartile range 4-13). ctDNA was detected before RC in 59 patients (53%) and was associated with poor RFS (log-rank p < 0.0001). Detectable ctDNA before RC was associated with poor outcomes regardless of clinical stage (

Contemporary outcomes of patients undergoing robotic-assisted radical cystectomy: A comparative analysis between intracorporeal ileal conduit and neobladder urinary diversions.

Objective: We aimed to compare perioperative and oncologic outcomes for patients undergoing robotic-assisted radical cystectomy (RARC) with intracorporeal ileal conduit (IC) and neobladder (NB) urinary diversion. Methods: Patients undergoing RARC with intracorporeal urinary diversion between January 2017 and January 2022 at the Icahn School of Medicine at Mount Sinai, New York, NY, USA were indexed. Baseline demographics, clinical characteristics, perioperative, and oncologic outcomes were analyzed. Survival was estimated with Kaplan-Meier plots. Results: Of 261 patients (206 [78.9%] male), 190 (72.8%) received IC while 71 (27.2%) received NB diversion. Median age was greater in the IC group (71 [interquartile range, IQR 65-78] years vs. 64 [IQR 59-67] years, p<0.001) and BMI was 26.6 (IQR 23.2-30.4) kg/m2. IC group was more likely to have prior abdominal or pelvic radiation (15.8% vs. 2.8%, p=0.014). American Association of Anesthesiologists scores were comparable between groups. The IC group had a higher proportion of patients with pathological tumor stage 2 (pT2) tumors (34 [17.9%] vs. 10 [14.1%], p=0.008) and pathological node stages pN2-N3 (28 [14.7%] vs. 3 [4.2%], p<0.001). The IC group had less median operative time (272 [IQR 246-306] min vs. 341 [IQR 303-378] min, p<0.001) and estimated blood loss (250 [150-500] mL vs. 325 [200-575] mL, p=0.002). Thirty- and 90-day complication rates were 44.4% and 50.2%, respectively, and comparable between groups. Clavien-Dindo grades 3-5 complications occurred in 27 (10.3%) and 34 (13.0%) patients within 30 and 90 days, respectively, with comparable rates between groups. Median follow-up was 324 (IQR 167-552) days, and comparable between groups. Kaplan-Meier estimate for overall survival at 24 months was 89% for the IC cohort and 93% for the NB cohort (hazard ratio 1.23, 95% confidence interval 1.05-2.42, p=0.02). Kaplan-Meier estimate for recurrence-free survival at 24 months was 74% for IC and 87% for NB (hazard ratio 1.81, 95% confidence interval 0.82-4.04, p=0.10). Conclusion: Patients undergoing intracorporeal IC urinary diversion had higher postoperative cancer stage, increased nodal involvement, similar complications outcomes, decreased overall survival, and similar recurrence-free survival compared to patients undergoing RARC with intracorporeal NB urinary diversion.

Eliminating the routine use of postoperative drain placement in patients undergoing robotic-assisted radical cystectomy with intracorporeal urinary diversion.

INTRODUCTION: Perioperative management of patients undergoing radical cystectomy and urinary diversion utilizing both open and minimally invasive techniques have routinely included the use of drains in the operative field. We herein demonstrate the safety of robotic-assisted radical cystectomy (RARC) without the routine use of postoperative drains. METHODS: Patients who underwent drainless RARC with intracorporeal urinary diversion between 2017 and 2022 at our institution were reviewed. Baseline and clinical characteristics as well as perioperative and postoperative outcomes were analyzed. The primary study outcome was incidence of postoperative urinary leak or intra-abdominal infectious collections within 90 days of RARC. A univariate and multivariable logistic regression analysis was performed to determine associations between study variables and the primary outcome. RESULTS: Of 381 patients, 298 (78.2%) were male and median age and BMI were 68 (63, 76) and 26.2 [23.0, 29.8], respectively. Overall 30 and 90-day complication rates were 39.6% and 50.4%, respectively. Twenty-one (5.5%) patients experienced a urine leak or intra-abdominal infectious collections. Sub-group analysis of patients who experienced the primary outcome demonstrated median postoperative day of presentation was day 19, and this group required 16 total additional procedures. On multivariable logistic regression analysis, only prior radiation therapy was associated with the development of the primary outcome of urinary leak or intra-abdominal infectious collection (odds ratio: 15.12, 95% confidence interval [1.52-156.8], p = 0.02). CONCLUSION: Drainless RARC with totally intracorporeal urinary diversion achieved competitive perioperative and complications outcomes compared to prior open and robotic series. In the context of a larger enhanced recovery after surgery protocol in RARC patients, the routine use of drains may be safely omitted.

Radiogenomics in Clear Cell Renal Cell Carcinoma: A Review of the Current Status and Future Directions.

Radiogenomics is a field of translational radiology that aims to associate a disease's radiologic phenotype with its underlying genotype, thus offering a novel class of non-invasive biomarkers with diagnostic, prognostic, and therapeutic potential. We herein review current radiogenomics literature in clear cell renal cell carcinoma (ccRCC), the most common renal malignancy. A literature review was performed by querying PubMed, Medline, Cochrane Library, Google Scholar, and Web of Science databases, identifying all relevant articles using the following search terms: "radiogenomics", "renal cell carcinoma", and "clear cell renal cell carcinoma". Articles included were limited to the English language and published between 2009-2021. Of 141 retrieved articles, 16 fit our inclusion criteria. Most studies used computed tomography (CT) images from open-source and institutional databases to extract radiomic features that were then modeled against common genomic mutations in ccRCC using a variety of machine learning algorithms. In more recent studies, we noted a shift towards the prediction of transcriptomic and/or epigenetic disease profiles, as well as downstream clinical outcomes. Radiogenomics offers a platform for the development of non-invasive biomarkers for ccRCC, with promising results in small-scale retrospective studies. However, more research is needed to identify and validate robust radiogenomic biomarkers before integration into clinical practice.

The Role of 3D Models Obtained from Multiparametric Prostate MRI in Performing Robotic Prostatectomy.

Background: Multiparametric prostate MRI (mpMRI) can provide important information for surgical planning, yet its interpretation is not immediate and imaging consultation at the time of surgery can result in interruptions and delay. The use of three-dimensional (3D) models based on mpMRI might obviate these issues. We aimed to evaluate the role of the prospective integration of 3D models from mpMRI in the robotic console in reducing the rate of positive surgical margins (PSMs). Materials and Methods: PSMs at our center are evaluated intraoperatively using the Neurovascular Structure Adjacent Frozen Section Examination method. Based on the rate of PSMs on frozen section during the year before the implementation of 3D models during surgery (22.5%), we estimated that 151 subjects were needed to detect a statistically significant difference of at least 40%. Patients with biopsy-proven prostate cancer (PCa) who received a 3T mpMRI at our institution and had a PIRADS ≥3 on mpMRI were included. Results: One hundred fifty-one patients were included. Overall, 17 (11.3%) patients had a PSM, 6 (35%) of them had PSM in an area where the mpMRI did not demonstrate any lesions. The rates of PSMs on both frozen (22.5% vs 11.3%) and permanent section (13.1% vs 6.6%) were significantly lower (p ≤ 0.03) compared with the cohort of patients operated during 2018 (n = 358). No significant differences among clinical characteristics were found between the study cohort and the 2018 cohort (all p > 0.05). Conclusions: The use of 3D models at the time of surgery was shown to reduce the PSM rate on both frozen and permanent section. Integrating 3D models in the robotic console could lead to improved PCa outcomes.

Defining Risk Categories for a Significant Decline in Estimated Glomerular Filtration Rate After Robotic Partial Nephrectomy: Implications for Patient Follow-up.

Following partial nephrectomy (PN), it is important to prevent any deterioration in estimated glomerular filtration rate (eGFR). At present there are no evidence-based recommendations on when a nephrology consultation should be requested and how to adjust postoperative management when the risk of renal function decline is high. In an effort to address this void, we used our previously published nomogram to define risk groups for a significant decline in eGFR at 3-15 mo after PN. We used the nomogram-derived probability as the independent variable for the classification and regression tree and identified four risk groups: low (0-10%), intermediate (10-21%), high (21-65%), and very high (65-100%). Overall, 336 (34%), 386 (39%), 243 (24%), and 34 (4%) patients fell in the low, intermediate, high, and very high risk groups, respectively. The rates of significant eGFR decline across the low, intermediate, high, and very high risk groups were 4%, 14%, 29%, and 79%. With the low risk category as a reference, the hazard ratio for eGFR decline was 3.21 (95% confidence interval [CI] 1.83-5.64) for the intermediate, 7.80 (95% CI 4.52-13.48) for the high, and 27.24 (95% CI 13.8-53.8) for the very high risk group (all p<0.001). These prognostic risk categories can be used to design postoperative follow-up schedules. A multidisciplinary approach can be considered for patients at high and very high risk of eGFR decline. PATIENT SUMMARY: We propose a new stratification system to identify individuals at high risk of a decline in renal function after robotic partial nephrectomy.

Development of a model to predict prostate cancer at the apex (PCAP model) in patients undergoing robot-assisted radical prostatectomy.

PURPOSE: To develop a model based on preoperative variables to predict apical prostate cancer. METHODS: We performed a retrospective analysis of 459 patients who underwent a robotic assisted radical prostatectomy (RALP) between January 2016 and September 2017. All patients had a preoperative biopsy and mpMRI of the prostate. Significant apical pathology (SAP) was defined as those patients who had a dominant nodule at the apex with a Gleason score > 6 and/or ECE at the apex. Binary logistic regression analyses were adopted to predict SAP. Variables included in the model were PSA, apical lesions prostate imaging reporting and data system (PI-RADS) score and apical biopsy Gleason score. The area under the curve (AUC) of the model was computed. RESULTS: A total of 121 (43.2%) patients had SAP. On univariable analysis, all apex-specific variables investigated emerged as predictors of SAP (all p < 0.05). On multivariable analysis PSA and apical PI-RADS score > 3 (all p < 0.05) emerged as significant predictors of SAP. The AUC of the model was 0.722. CONCLUSION: Patients with PI-RADS 3, 4 or 5 lesions at the apex were three times as more likely to have true SAP compared to those who have PI-RADS < 3 or negative mpMRI prior to undergoing RALP.

Clinical implications of prostatic capsular abutment or bulging on multiparametric magnetic resonance imaging.

BACKGROUND: The presence of capsular abutment or bulging can raise concern when planning surgery. In this study we aimed to test the clinical implications of capsular abutment or bulging on preoperative multiparametric magnetic resonance imaging (mpMRI). METHODS: We analyzed the data of 291 patients who underwent radical prostatectomy (RP) for a cT1-2N0 prostate cancer in a single surgeon series. All patients underwent preoperative staging with mpMRI. PIRADS v2 was used for characterizing lesions. The role of capsular abutment or bulging was tested in a multivariable logistic regression adjusting for prostate-specific antigen and highest ipsilateral biopsy Gleason grade. The presence of focal versus extensive extracapsular extension (ECE) was investigated. RESULTS: Overall, ECE on final pathology was documented in 35 (12%) cases and ECE was focal in 32 (91%) patients. Overall, mpMRI demonstrated capsule bulging or abutment in 12 (24%) cases. After adjusting for confounders, capsule bulging or abutment on mpMRI emerged as predictor for ECE (OR=6.70; 95% CI: 2.97-15.12, P<0.001). The sensitivity and specificity of capsule abutment or bulging in predicting ECE were 43% and 95%, respectively. Sensitivity and specificity were 36% and 48% respectively to predict focal ECE. CONCLUSIONS: The PIRADS v2 scoring system has a grey zone concerning ECE as defined by capsule abutment or bulging. We found an increased risk of ECE and specifically focal ECE when capsule bulging or abutment on mpMRI are documented.

A transcriptomic signature of tertiary Gleason 5 predicts worse clinicopathological outcome.

OBJECTIVE: To investigate the genomic features of tertiary pattern 5 (TP5) on radical prostatectomy specimens in an effort to explain the poor clinical outcomes associated with this disease subtype. PATIENTS AND METHODS: Data from 159 men with Gleason Grade Group (GGG) 3 or 4 were considered. All patients had Decipher diagnostic testing with transcript profiles and single-channel array normalisation (SCAN)-normalised expression of coding genes. The relationship between Decipher and TP5 was investigated by linear and binary logistic regressions. A differential transcriptomic analysis between patients with and without TP5 was performed. The prognostic role of these genes on progression-free survival (PFS) and overall survival (OS) was evaluated using The Cancer Genome Atlas. RESULTS: In all, 52/159 (33%) patients had GGG 3-4 with TP5 disease. TP5 was associated with a higher Decipher score (ß 0.07, 95% confidence interval [CI] 0.02-0.13; P = 0.04) and higher likelihood of falling within the intermediate- or high-risk categories (odds ratio 3.34, 95% CI 1.34-8.35; P = 0.01). Analysis of microarray data revealed an 18-gene signature that was differentially expressed in patients with TP5; 13 genes were over- and five under-expressed in the TP5 cohort. The overexpression of cyclin dependent kinase inhibitor 2B (CDKN2B), polo-like kinase 1 (PLK1), or cell division cycle 20 (CDC20) was associated with worse PFS. The group harbouring overexpression of at least one gene had a 5-year PFS rate of 50% vs 74% in the group without overexpression (P < 0.001). CONCLUSIONS: Our studies have elucidated unique genomic features of TP5, whilst confirming previous clinical findings that patients harbouring TP5 tend to have worse prognosis. This is the first RNA-based study to investigate the molecular diversity of TP5 and the first correlating CDKN2B to poorer prognosis in patients with prostate cancer.

Downgrading of Grade Group After Radical Prostatectomy: Comparison of Multiparametric Magnetic Resonance Imaging Guided Fusion Biopsy and Standard 12-Core Biopsy.

OBJECTIVE: To analyze the factors associated with Grade group (GG) downgrading post-radical prostatectomy. PATIENTS AND METHODS: We performed a retrospective analysis of 536 patients who underwent robot-assisted laparoscopic radical prostatectomy from February 2014 to October 2015. We have analyzed the clinical, radiological, and pathologic factors associated with GG downgrading in final pathology. Downgrading was defined as those patients who downgraded from GG 3, 4, or 5 on biopsy to GG 1 or 2 on final pathology as well as patients who downgraded from GG 2 on biopsy to GG 1 on final pathology. Categorical values were compared with chi-square and Fischer's exact tests. Mann-Whitney U and Kruskal-Wallis were used for analysis of independent variables associated with GG downgrading. RESULTS: Ninety-three patients underwent fusion biopsy (FB) and 443 underwent the standard 12 core biopsy. Baseline clinical characteristics were similar between the 2 groups except for race (P = .009). Downgrading was observed in 76 patients (14.1%). Rate of downgrading was higher in the FB group (n = 22, 23.7% vs n = 54, 12.2%, P = .008). In multivariable logistic regression analysis, FB (OR:2.39, P = .004) and maximum percentage of core involvement (OR:1.01, P = .013) were associated with downgrading after robot-assisted laparoscopic radical prostatectomy. After 1:2 propensity score matching, FB was still associated with an increased rate of downgrading (P = .034). Downgrading had no significant effect on pathologic outcome. CONCLUSION: FB and maximum percentage of core involvement are the only factors associated with GG downgrading in final pathology. However, downgrading did not influence surgical outcome.

Defining Prostate Cancer at Favorable Intermediate Risk: The Potential Utility of Magnetic Resonance Imaging and Genomic Tests.

PURPOSE: We determined whether prostate multiparametric magnetic resonance imaging and genomic biomarkers might help further define patients with favorable intermediate risk prostate cancer which could safely be considered suitable for active surveillance. MATERIALS AND METHODS: From our institutional database we identified 509 patients who underwent radical prostatectomy with preoperative magnetic resonance imaging and a postoperative Decipher® prostate cancer test. According to the NCCN® (National Comprehensive Cancer Network®) risk stratification 125 men had favorable intermediate and 171 had unfavorable intermediate risk disease. Univariable and multivariable binary logistic regression analyses were done to test the utility of different variables in predicting adverse pathology, defined as Gleason Grade Group greater than 2, pT3b or pN1. RESULTS: On univariable analysis favorable intermediate risk, multiparametric magnetic resonance imaging and the prostate cancer test significantly predicted adverse pathology. On multivariable analysis favorable intermediate risk and the prostate cancer test maintained independent predictive value while multiparametric magnetic resonance imaging did not meet statistical significance (p = 0.059). The 19 patients at favorable intermediate risk with high genomic risk had an adverse pathology rate slightly higher than patients at unfavorable intermediate risk (42.1% vs 39.8%, p = 0.56). Those at low genomic risk had an adverse pathology rate slightly lower than patients at very low or low risk (7.5% vs 10.2%, p = 0.84). The 31 patients at favorable intermediate risk but at high multiparametric magnetic resonance imaging and genomic risk had an adverse pathology rate slightly lower than patients at unfavorable intermediate risk (25.8% vs 39.8%, p = 0.14). Those at low multiparametric magnetic resonance imaging and genomic risk had an adverse pathology rate slightly lower than patients at very low or low risk (8.5% vs 10.2%, p = 0.89). CONCLUSIONS: Multiparametric magnetic resonance imaging and the Decipher test allowed us to better define the risk of adverse pathology in patients at favorable intermediate risk who were diagnosed with prostate cancer.

Novel nomogram for the prediction of seminal vesicle invasion including multiparametric magnetic resonance imaging.

OBJECTIVES: To create a model that predicts side-specific seminal vesicle invasion using clinical, biopsy and multiparametric magnetic resonance imaging data. METHODS: We analyzed data from 544 patients who underwent robot-assisted radical prostatectomy at a single institution. To develop a side-specific predictive model, we ultimately considered four variables: prostate-specific antigen, highest ipsilateral biopsy Gleason grade, highest ipsilateral percentage core involvement and seminal vesicle invasion on multiparametric magnetic resonance imaging. A binary multivariable logistic regression model was fitted to predict seminal vesicle invasion. A nomogram was then built based on the coefficients of the resulting logit function. The leave-one-out cross validation method was used for internal validation, and the decision curve analysis for the evaluation of the net clinical benefit. RESULTS: We relied on 804 side-specific cases after excluding negative biopsy observations (n = 284). Seminal vesicle invasion was reported on multiparametric magnetic resonance imaging in 41 (5%) cases, and on final pathology in 64 (8%) cases. All variables in the model emerged as predictors of seminal vesicle invasion (all P ≤ 0.001) and were subsequently considered to build a nomogram. The area under the curve of multiparametric magnetic resonance imaging alone in predicting seminal vesicle invasion was 59.1%; whereas one of the clinical variables only was 85.1%. The area under the curve of the nomogram resulting from their combination was 86.5%. After internal validation, this resulted in 84.7%. The model achieved good calibration and the decision curve analysis showed its clinical benefit, especially when compared with relying only on multiparametric magnetic resonance imaging prediction of seminal vesicle invasion. CONCLUSIONS: A nomogram based on clinical and multiparametric magnetic resonance imaging data can predict seminal vesicle invasion and serve as a tool to urologists for surgical planning.

An updated approach to incremental nerve sparing for robot-assisted radical prostatectomy.

OBJECTIVES: To update the algorithm for performing incremental nerve sparing (NS) using our multiparametric magnetic resonance imaging (mpMRI)-based nomogram. PATIENTS AND METHODS: We applied the coefficients of the nomogram to the observations extracted from our population of patients who underwent robot-assisted radical prostatectomy between February 2014 and October 2015 and who received preoperative mpMRI. The information considered were PSA level, highest side-specific biopsy Gleason grade group, highest ipsilateral percentage core involvement with the highest Gleason grade group, and extracapsular extension (ECE) on mpMRI. The nomogram-derived probability [P (%)], after internal validation, was used as the independent variable on a classification tree to identify the most significant thresholds for ECE prediction. Incremental NS was performed as follows: Grade 1 NS: intrafascial dissection between the peri-prostatic veins and the pseudocapsule of the prostate; Grade 2 NS: inter-fascial dissection along the peri-venous plane; Grade 3 NS: inter-fascial dissection through the outer compartment of the lateral prostatic fascia; Grade 4 NS: extrafascial dissection. RESULTS: Data from 561 patients were considered, and 829 prostatic lobes with biopsy-documented tumour were analysed. Overall, 142 lobes presented ECE that was focal in 27 (19%) cases. The classification tree identified four risk categories. In the low- [P (%) ≤10], intermediate- [P (%) 10-21], high [P (%) 21-73] and very-high-risk [P(%) >73] groups, the ECE rates were 3.3%, 16%, 61.6% and 90%, respectively. Amongst those, ECE was focal in 41.7%, 31.7%, 7.9% and 0%, respectively. CONCLUSION: We suggest that Grade 1 NS (intrafascial) should be performed in the low-risk group. The inter-fascial approach, namely grades 2 and 3 NS, should be performed in the intermediate- and high-risk categories, respectively. Grade 4 NS (extrafascial) should be performed in the very-high-risk group. The current algorithm yields a better accuracy than the previous one; however, prospective validation is warranted.

Multiparametric Magnetic Resonance Imaging Features Identify Aggressive Prostate Cancer at the Phenotypic and Transcriptomic Level.

PURPOSE: Multiparametric magnetic resonance imaging is a diagnostic tool for prostate cancer with limited data on prognostic use. We sought to determine whether multiparametric magnetic resonance could predict aggressive prostate cancer features. MATERIALS AND METHODS: We retrospectively analyzed the records of 206 patients who underwent radical prostatectomy between 2013 and 2017. All patients had available RNA expression data on the final pathology specimen obtained from a location corresponding to a lesion location on multiparametric magnetic resonance imaging. The association between the PIRADS™ (Prostate Imaging Reporting and Data System) score and adverse pathology features were analyzed. We also performed differential transcriptomic analysis between the PIRADS groups. Factors associated with adverse pathology were analyzed using a multivariable logistic regression model. RESULTS: Lesion size (p = 0.03), PIRADS score (p = 0.02) and extraprostatic extension (p = 0.01) associated significantly with the Decipher® score. Multivariable analysis showed that the PIRADS score (referent PIRADS 3, OR 8.1, 95% CI 1.2-57.5, p = 0.04), the Gleason Grade Group (referent 3, OR 5.6, 95% CI 1.5-21.1, p = 0.01) and prostate specific antigen (OR 1.103, 95% CI 1.011-1.203) were risk factors for adverse pathology findings. The difference between PIRADS 4 and 5 did not reach significance (OR 1.9, 95% CI 0.8-4.5, p = 0.12). However, the PI3K-AKT-mTOR, WNT-ß and E2F signaling pathways were more active in PIRADS 5 than in PIRADS 4 cases. CONCLUSIONS: The PIRADS score is associated with adverse pathology results, increased metastatic risk and differential genomic pathway activation.

A Nomogram to Predict Significant Estimated Glomerular Filtration Rate Reduction After Robotic Partial Nephrectomy.

BACKGROUND: Decreased functional outcome after partial nephrectomy is associated with overall mortality. OBJECTIVE: To create a model that predicts ≥25% reduction from baseline estimated glomerular filtration rate (eGFR) in patients undergoing robot-assisted partial nephrectomy (RAPN) and to investigate the role of acute kidney injury (AKI) in this patient population. DESIGN, SETTING, AND PARTICIPANTS: A total of 999 patients were identified from a multi-institutional database. Renal function was defined according to the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines for chronic kidney disease (CKD). AKI was defined as >25% reduction in eGFR from pre-RAPN period to discharge. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: A nomogram to predict significant eGFR reduction (≥25% from baseline) in the time-frame between 3 and 15mo after RAPN was built based on the coefficients of Cox survival function that ultimately included age, sex, Charlson comorbidity index, baseline eGFR, RENAL nephrometry score, AKI in patients with normal baseline renal function, and AKI on CKD. Such landmark analysis was chosen in order to account for eGFR fluctuations occurring within the first 3mo of RAPN. The proportional hazard assumption was evaluated through the Schönfeld test. Internal validation was performed using the leave-one-out cross validation. Calibration was graphically investigated. The decision curve analysis (DCA) was used to evaluate the net clinical benefit. RESULTS AND LIMITATIONS: Median (interquartile range [IQR]) age at surgery was 61yr (51, 68). Overall, 146 patients experienced significant eGFR reduction; median follow-up for survivors was 12.4mo. The 15-mo probability of significant eGFR reduction was 19%. All variables fitted into the model, including AKI in patients with normal renal function (hazard ratio [HR]: 4.51; 95% confidence interval [CI]: 3.12, 6.60; p<0.001) and AKI on CKD (HR: 4.90; 95% CI: 2.17, 11.1; p<0.001), emerged as predictors of significant eGFR reduction (all p≤0.048) and were considered to build a nomogram. The internally validated c index was 73%. The model demonstrated excellent calibration and a net benefit at the DCA with probabilities ≥4%. CONCLUSIONS: We developed a nomogram that accurately predicts significant eGFR reduction after RAPN. This model may serve as a tool for early identification of patients at high risk for significant renal function decline after surgery. PATIENT SUMMARY: We have developed a model for the prediction of renal function loss after partial nephrectomy for renal cancer.

Development and internal validation of a side-specific, multiparametric magnetic resonance imaging-based nomogram for the prediction of extracapsular extension of prostate cancer.

OBJECTIVES: To develop a nomogram for predicting side-specific extracapsular extension (ECE) for planning nerve-sparing radical prostatectomy. MATERIALS AND METHODS: We retrospectively analysed data from 561 patients who underwent robot-assisted radical prostatectomy between February 2014 and October 2015. To develop a side-specific predictive model, we considered the prostatic lobes separately. Four variables were included: prostate-specific antigen; highest ipsilateral biopsy Gleason grade; highest ipsilateral percentage core involvement; and ECE on multiparametric magnetic resonance imaging (mpMRI). A multivariable logistic regression analysis was fitted to predict side-specific ECE. A nomogram was built based on the coefficients of the logit function. Internal validation was performed using 'leave-one-out' cross-validation. Calibration was graphically investigated. The decision curve analysis was used to evaluate the net clinical benefit. RESULTS: The study population consisted of 829 side-specific cases, after excluding negative biopsy observations (n = 293). ECE was reported on mpMRI and final pathology in 115 (14%) and 142 (17.1%) cases, respectively. Among these, mpMRI was able to predict ECE correctly in 57 (40.1%) cases. All variables in the model except highest percentage core involvement were predictors of ECE (all P ≤ 0.006). All variables were considered for inclusion in the nomogram. After internal validation, the area under the curve was 82.11%. The model demonstrated excellent calibration and improved clinical risk prediction, especially when compared with relying on mpMRI prediction of ECE alone. When retrospectively applying the nomogram-derived probability, using a 20% threshold for performing nerve-sparing, nine out of 14 positive surgical margins (PSMs) at the site of ECE resulted above the threshold. CONCLUSION: We developed an easy-to-use model for the prediction of side-specific ECE, and hope it serves as a tool for planning nerve-sparing radical prostatectomy and in the reduction of PSM in future series.