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Introduction: How renal mass biopsy (RMB) impacts patient management with T1 renal masses (T1RM) is unclear. We explore the association between RMB and utilization of active surveillance (AS), nephron-sparing interventions (NSI), and radical nephrectomy (RN)., Methods: Data were analyzed retrospectively using the MUSIC-KIDNEY registry. Treatment received was analyzed using a fitted mixed-effects multinomial logistic-regression model., Results: Of 4062 patients, 19.6% underwent RMB. Factors associated with RMB included younger age, higher Charlson comorbidity score, tumor size > 2.0 cm and higher complexity tumors. AS was selected by 88%, 68%, and 27% of patients with benign, indeterminate, and malignant RMB findings. Non-malignant pathology at surgery was significantly ( P < .0001) more common without RMB (vs after RMB): 14.8% vs 7.2% of PN and 10.2% vs 1.7% of RN. Patients with T1bRM managed without or with RMB, AS was chosen by 22% vs 34%, NSI by 31% vs 35%, and RN by 47% vs 32% ( P = .0027). An interaction between tumor stage (T1a vs T1b) and RMB remained in multivariable analyses accounting for practice-level variation and other confounding variables. The risk-adjusted RN rate for T1bRM was 41.4% without RMB vs 27.8% with RMB; 7.4 RMB are needed to avoid one RN (number needed to treat) for benign or indolent disease., Conclusions: Treatments received by T1RM patients undergoing RMB are different than when RMB is omitted, based on RMB results and several confounders. T1RM patients benefit from reduction in intervention for non-malignant disease, particularly when RN is planned. For every 7 biopsies of T1bRM performed, one RN was avoided.

Introduction: Postoperative length of stay (LOS) after robot-assisted radical prostatectomy (RARP) is a potentially modifiable aspect of prostate cancer care. Our objective was to evaluate the use of same-day discharge (SDD) RARP and compare pre- and perioperative characteristics of these men with those who underwent hospitalization postoperatively., Methods: Perioperative outcomes for patients undergoing RARP were evaluated from the Michigan Urological Surgery Improvement Collaborative (MUSIC) registry. Men were classified by hospital LOS: SDD, 1 day, and 2 days. Practice and surgeon-level variation of SDD and the change in SDD use over time were assessed. The primary outcome was 30-day readmission after RARP., Results: We identified 10,249 men undergoing RARP in MUSIC from 2018 to 2022. Most patients had 1-day LOS (79.6%), with 2.8% undergoing SDD. The proportion of patients undergoing RARPs with SDD rose from 0.6% in 2018 to 1.2% in 2019 and 4.4% for 2020 to 2022. At least one SDD was performed in 12 of 28 MUSIC practices (42.9%) and by 52 of 138 urologists (37.7%). In multivariable analysis, odds of 30-day readmission were not significantly different between patients .undergoing SDD and LOS 1 day (OR: 1.72, 95% CI: 0.92-3.22, P = .090). Limitations include retrospective, registry-based observational study with nonuniform utilization of SDD., Conclusions: Although more patients have undergone SDD after RARP beginning in 2018, rates across Michigan have remained < 5% annually. Importantly, patients undergoing SDD RARP did not experience significantly more readmissions compared to hospitalized patients. SDD appears safe and feasible for select patients who are motivated by this approach.

Objective: Life expectancy models are useful tools to support clinical decision-making. Prior models have not been used widely in clinical practice for patients with renal masses. We sought to develop and validate a model to predict life expectancy following the detection of a localized renal mass suspicious for renal cell carcinoma., Materials and Methods: Using retrospective data from 2 large centers, we identified patients diagnosed with clinically localized renal parenchymal masses from 1998 to 2018. After 2:1 random sampling into a derivation and validation cohort stratified by site, we used age, sex, log-transformed tumor size, simplified cardiovascular index and planned treatment to fit a Cox regression model to predict all-cause mortality from the time of diagnosis. The model's discrimination was evaluated using a C-statistic, and calibration was evaluated visually at 1, 5, and 10 years., Results: We identified 2,667 patients (1,386 at Corewell Health and 1,281 at Johns Hopkins) with renal masses. Of these, 420 (16%) died with a median follow-up of 5.2 years (interquartile range 2.2-8.3). Statistically significant predictors in the multivariable Cox regression model were age (hazard ratio [HR] 1.04; 95% confidence interval [CI] 1.03-1.05); male sex (HR 1.40; 95% CI 1.08-1.81); log-transformed tumor size (HR 1.71; 95% CI 1.30-2.24); cardiovascular index (HR 1.48; 95% CI 1.32-1.67), and planned treatment (HR: 0.10, 95% CI: 0.06-0.18 for kidney-sparing intervention and HR: 0.20, 95% CI: 0.11-0.35 for radical nephrectomy vs. no intervention). The model achieved a C-statistic of 0.74 in the derivation cohort and 0.73 in the validation cohort. The model was well-calibrated at 1, 5, and 10 years of follow-up., Conclusions: For patients with localized renal masses, accurate determination of life expectancy is essential for decision-making regarding intervention vs. active surveillance as a primary treatment modality. We have made available a simple tool for this purpose., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: KS's institution receives grant funding from the National Institute of Diabetes and Digestive and Kidney Diseases, Blue Cross Blue Shield of Michigan, and Teva Pharmaceuticals for unrelated work. KS previously served on a scientific advisory board for Flatiron Health. All other authors have no conflicts of interest., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Objective: Understanding the relationship between comorbidities and life expectancy is important in cancer patients who carry risks of cancer and noncancer-related mortality. Comorbidity indices (CI) are tools to provide an objective measure of competing risks of death. We sought to determine which CI might be best incorporated into clinical practice for patients with suspected renal cancer., Materials and Methods: 1572 patients diagnosed with renal masses (stage I-IV) between 1998 and 2016 were analyzed for this study. Patient data were gathered from a community-based health center. Comorbidities were evaluated individually, and with 1 of 4 CI: Charlson (CCI), updated CCI (uCCI), age-adjusted CCI (aCCI), and simplified cardiovascular index (CVI). Cox-proportional hazard analysis of all-cause mortality was performed using the four CI, adjusting for the 4 CI, adjusting for age, gender, race, tumor size, and tumor stage., Results: Univariable analyses revealed the four CI were significant predictors of mortality (P < 0.05), as were age, gender, tumor size, and stage. Comorbid conditions at diagnosis included hypertension (47.8%), diabetes mellitus (47.2%), coronary artery disease (41.1%), chronic kidney disease (31.8%), peripheral vascular disease (8.0%), congestive heart failure (5.7%), chronic obstructive pulmonary disease (5.7%), and cerebrovascular disease (2.0%). When analyzing the 4 CI in multivariable survival analyses accounting for factors available at diagnosis, and analyses incorporating pathologic and recurrence data, only CVI score and uCCI remained statistically significant (P < 0.05). Limitations of this work are the retrospective nature of data collection and data from a single institution, limiting the generalizability., Conclusion: Increasing comorbidity, age, tumor size, and cM stage are predictors of ACM for suspected renal cancer patients. CVI appears to provide comparable information to various iterations of CCI (uCCI, aCCI) while being the simplest to use. Utilization of CVI may assist clinicians and patients when considering between interventional and noninterventional approaches for suspected renal cancer., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)