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Background: There is no definitive evidence of the prognosis impact of histological variants (HVs) in patients who undergo surgical resection of a nonmetastatic renal cell carcinoma (nm-RCC) with venous tumor thrombus (TT). Objective: To investigate the impact of HVs on the prognosis of patients with nm-RCC with TT after radical surgery. Design, setting, and participants: Patients who underwent radical nephrectomy with the removal of the venous TT for an nm-RCC were included in a retrospective study. Outcome measurements and statistical analysis: Three groups were identified: clear cell (ccRCC), papillary (pRCC), and chromophobe (chRCC) RCC. The primary outcome measures (disease-free and overall survival [OS]) were assessed using the Kaplan-Meier method and compared using the log-rank test. Univariate and multivariate Cox proportional hazard models were used to study the impact of HVs on survival. Results and limitations: A total of 873 patients were included. The histological subtypes were distributed as follows: ccRCC in 780 cases, pRCC in 58 cases, and chRCC in 35 cases. At the time of data analysis, 612 patients were recurrence free and 228 had died. A survival analysis revealed significant differences in both OS and recurrence-free survival across histological subtypes, with the poorest outcomes observed in pRCC patients (p

Background: Current literature does not provide large-scale data regarding clinical outcomes of robot-assisted (RAPN) versus open (OPN) partial nephrectomy. Moreover, data assessing predictors of long-term oncologic outcomes after RAPN are scarce. Objective: To compare perioperative, functional, and oncologic outcomes of RAPN versus OPN, and to investigate the predictors of oncologic outcomes after RAPN. Design, setting, and participants: This study included 3467 patients treated with OPN (n = 1063) or RAPN (n = 2404) for a single cT1–2N0M0 renal mass from 2004 to 2018 at nine high-volume European, North American, and Asian institutions. Outcome measurements and statistical analysis: The study outcomes were short-term postoperative, functional, and oncologic outcomes. Regression models investigated the effect of surgical approach (open vs Robot assisted) on study outcomes, and interaction tests were used for subgroup analyses. Propensity score matching for demographic and tumor characteristics was used in sensitivity analyses. Multivariable Cox-regression analyses identified predictors of oncologic outcomes after RAPN. Results and limitations: Baseline characteristics were similar between patients receiving RAPN and OPN, with only few differences. After adjusting for confounding, RAPN was associated with lower odds of intraoperative (odds ratio [OR]: 0.39, 95% confidence interval [CI]: 0.22, 0.68) and Clavien-Dindo ≥2 postoperative (OR: 0.29, 95% CI: 0.16, 0.50) complications (both p 0.05 on interaction tests). On multivariable analyses, we found no differences between the two techniques with respect to functional and oncologic outcomes (all p > 0.05). Overall, there were 63 and 92 local recurrences and systemic progressions, respectively, with a median follow-up after surgery of 32 mo (interquartile range: 18, 60). Among patients receiving RAPN, we assessed predictors of local recurrence and systemic progression with discrimination accuracy (ie, C-index) that ranged from 0.73 to 0.81. Conclusions: While cancer control and long-term renal function did not differ between RAPN and OPN, we found that the intra- and postoperative morbidity—especially in terms of complications—was lower after RAPN than after OPN. Our predictive models allow surgeons to estimate the risk of adverse oncologic outcomes after RAPN, with relevant implications for preoperative counseling and follow-up after surgery. Patient summary: In this comparative study on robotic versus open partial nephrectomy, functional and oncologic outcomes were similar between the two techniques, with lower morbidity—especially in terms of complications—for robot-assisted surgery. The assessment of prognosticators for patients receiving robot-assisted partial nephrectomy may help in preoperative counseling and provides relevant data to tailor postoperative follow-up.

Background: The coronavirus disease 2019 (COVID-19) pandemic has greatly affected health care priorities. Objective: To explore and analyse trends in public online search for urological cancers. Design, setting, and participants: We performed a retrospective analysis using the Google Health Trends online tool. Data related to urological cancer terms (“prostate cancer”, “kidney cancer”, and “bladder cancer”) were extracted. We analysed trends for the whole world and for five countries: Italy, the UK, France, Sweden, and the USA. Outcome measurements and statistical analysis: A join-point regression model was used to define significant changes in trends over time. Week percentage changes (WPCs) were estimated to summarise linear trends. The Mann-Whitney test was used to compare the search volume during the COVID-19 pandemic period (from January 2020 to April 2021) and the equivalent period of 2018 and 2019. Results and limitations: During COVID-19, worldwide online interest decreased significantly for all urological cancers, especially prostate cancer (WPC: –13.9%, p = 0.004; WPC: –5.4%, p < 0.001; and WPC: –4.3%, p < 0.001, for prostate, kidney, and bladder cancers, respectively). The most important decline was observed in the USA. The interest for all cancers was significantly less during the COVID-19 pandemic than in the same periods of 2018 and 2019. Conclusions: Online interest in urological cancers decreased significantly during the COVID-19 pandemic. Future studies will tell us whether this will translate into worse oncological outcomes. Patient summary: Patients are increasingly searching the Internet to get information on cancer. We explored Google queries during the COVID-19 pandemic and found that online interest decreased significantly for all urological cancers, especially prostate cancer. We do not know yet whether this will translate into worse prognosis for patients.

A prognostic model based on the population of the ASSURE phase 3 trial has recently been described. The ASSURE model stratifies patients into risk groups to predict survival after surgical resection of intermediate- and high-risk localised kidney cancer. We evaluated this model in an independent cohort of 1372 patients using discrimination, calibration, and decision curve analysis. Regarding disease-free survival, the ASSURE model showed modest discrimination (65%), miscalibration, and poor net benefit compared with the UCLA Integrated Staging System (UISS) and Leibovich 2018 models. Similarly, the ability of the ASSURE model to predict overall survival was poor in terms of discrimination (63%), with overestimation on calibration plots and a modest net benefit for the probability threshold of between 10% and 40%. Overall, our results show that the performance of the ASSURE model was less optimistic than expected, and not associated with a clear improvement in patient selection and clinical usefulness in comparison to with available models. We propose an updated version using the recalibration method, which leads to a (slight) improvement in performance but should be validated in another external population. Patient summary: The recent ASSURE model evaluates survival after surgery for nonmetastatic kidney cancer. We found no clear improvement in patient classification when we compared ASSURE with older models, so use of this model for patients with nonmetastatic kidney cancer still needs to be clarified.