SAFE: Multi-institutional study of time to complications after robot-assisted partial nephrectomy, selection of a population eligible for outpatient management (UroCCR 90).

INTRODUCTION: The average hospital length of stay after robotic-assisted partial nephrectomy (RAPN) is 3 days, with a current trend towards outpatient cases, although no population has been identified. The main objective of the study was to analyze the time to onset of post-operative complications, identify risk factors for significant early complications in order to define a population eligible for outpatient case. MATERIAL AND METHOD: The study included 3342 patients with clinically localized renal tumors who underwent RAPN surgery between 2010 and 2021. The primary endpoint was the occurrence of significant complications (SC) (Clavien Dindo>2 (CD)). A CS-free survival analysis was performed. A multivariate logistic regression model was fitted to predict the risk of early significant complications (ESC) after RAPN. RESULTS: The rates of total complications and SC were 14.99% and 3.59% respectively. Median time to SC was significantly longer at 3 days [3.9 - 5.7] versus 2 days [2.4 - 3] for total complications (p=0.012). The majority of complications occurred within the first 72 hours, and the risk factors for early SC (<72h ) (ESC) were clamping time (p= 0.04) and ASA>2 score (p= 0.007). Analysis of survival without ESC showed a significant impact of clamping time (p=0.043) on complication-free survival. CONCLUSION: Using standard preoperative variables, we were able to determine that the only factor influencing the occurrence of postoperative ESC was ASA score >2 and thus define it as a primary eligibility criterion for an indication of outpatient RAPN subject to a clamp time of less than 20 minutes.

Surgical Experience and Functional Outcomes after Laparoscopic and Robot-Assisted Partial Nephrectomy: Results from a Multi-Institutional Collaboration.

Background: In patients treated with partial nephrectomy, prior evidence showed that peri-operative outcomes, such as complications and ischemia time, improved as a function of the surgical experience of the surgeon, but data on functional outcomes after surgery are still scarce. Methods: We retrospectively analyzed data of 4011 patients with a single, unilateral cT1a-b renal mass treated with laparoscopic or robot-assisted partial nephrectomy. The operations were performed by 119 surgeons at 22 participating institutions between 1997 and 2022. Multivariable models investigated the association between surgical experience (number of prior operations) and acute kidney injury (AKI) and recovery of at least 90% of baseline estimated glomerular filtration rate (eGFR) 1 yr after partial nephrectomy. The adjustment for case mix included age, Body Mass Index, preoperative serum creatinine, clinical T stage, PADUA score, warm ischemia time, pathologic tumor size, and year of surgery. Results: A total of 753 (19%) and 3258 (81%) patients underwent laparoscopic and robot-assisted partial nephrectomy, respectively. Overall, 37 (31%) and 55 (46%) surgeons contributed only to laparoscopic and robotic learning curves, respectively, whereas 27 (23%) contributed to the learning curves of both approaches. In the laparoscopic group, 8% and 55% of patients developed AKI and recovered at least 90% of their baseline eGFR, respectively. After adjusting for confounders, we did not find evidence of an association between surgical experience and AKI after laparoscopic partial nephrectomy (odds ratio [OR]: 0.9992; 95% confidence interval [CI]: 0.9963, 1.0022; p = 0.6). Similar results were found when 1-year renal function was the outcome of interest (OR: 0.9996; 95% CI: 0.9988, 1.0005; p = 0.5). Among patients who underwent robot-assisted partial nephrectomy, AKI occurred in 11% of patients, whereas 54% recovered at least 90% of their baseline eGFR. On multivariable analyses, the relationship between surgical experience and AKI after surgery was not statistically significant (OR: 1.0015; 95% CI: 0.9992, 1.0037; p = 0.2), with similar results when the outcome of interest was renal function one year after surgery (OR: 1.0001; 95% CI: 0.9980, 1.0022; p = 0.9). Virtually the same findings were found on sensitivity analyses. Conclusions: In patients treated with laparoscopic or robot-assisted partial nephrectomy, our data suggest that the surgical experience of the operating surgeon might not be a key determinant of functional recovery after surgery. This raises questions about the use of serum markers to assess functional recovery in patients with two kidneys and opens the discussion on what are the key steps of the procedure that allowed surgeons to achieve optimal outcomes since their initial cases.

Prognostic models for predicting oncological outcomes after surgical resection of a nonmetastatic renal cancer: A critical review of current literature.

Prognostic models can be valuable for clinicians in counseling and monitoring patients after the surgical resection of nonmetastatic renal cell carcinoma (nmRCC). Over the years, several risk prediction models have been developed, evolving significantly in their ability to predict recurrence and overall survival following surgery. This review comprehensively evaluates and critically appraises current prognostic models for nm-RCC after nephrectomy. The last 2 decades have witnessed a notable increase in the development of various prognostic risk models for RCC, incorporating clinical, pathological, genomic, and molecular factors, primarily using retrospective data. Only a limited number of these models have been developed using prospective data, and their performance has been less effective than expected when applied to broader, real-life patient populations. Recently, artificial intelligence (AI), especially machine learning and deep learning algorithms, has emerged as a significant tool in creating survival prediction models. However, their widespread application remains constrained due to limited external validation, a lack of cost-effectiveness analysis, and unconfirmed clinical utility. Although numerous models that integrate clinical, pathological, and molecular data have been proposed for nm-RCC risk stratification, none have conclusively demonstrated practical effectiveness. As a result, current guidelines do not endorse a specific model. The ongoing development and validation of AI algorithms in RCC risk prediction are crucial areas for future research.

Long-term consequences of positive surgical margin after partial nephrectomy for renal cell carcinoma: multi-institutional analysis.

INTRODUCTION: The aim of the study was to determine the impact of positive surgical margins (PSM) after PN on very long-term recurrence in a contemporary cohort. METHODS: Patients who underwent PN for a localized renal tumour were included. Patients were stratified according to the presence of PSM. Data on patients' characteristics, the tumour, the peri- and postoperative events were collected. Disease-free survival (DFS) and overall survival (OS) were assessed by the Kaplan-Meier method and compared by the log-rank test. Sensitivity analyses using weighted propensity score analysis was performed to account for potential selection biases arising from the nonrandom allocation of patients to different groups. RESULTS: A total of 1115 patients were included in the study. The incidence of PSM was 5.4% (n = 61). The median follow-up time was 51 months for the PSM group and 61 months for the NSM group (p = 0.31). Recurrence rates were significantly higher in the PSM group (13%, n = 8) compared to the NSM group (7%, n = 73) (p = 0.05). This resulted in a significant reduction in DFS in the PSM group (p = 0.004), particularly pronounced in patients with clear cell renal cell carcinoma. Additionally, OS was significantly lower in the PSM group (p < 0.01). Propensity score analysis confirmed a decrease in DFS for the PSM group (p = 0.05), while there was no significant difference in OS between the two groups (p = 0.49). CONCLUSION: In this retrospective multicenter study, PSM impact on oncological outcomes, increasing recurrence, but no difference in OS was observed post-adjustment for biases.

Stereotactic body radiation therapy for primary renal cell carcinoma: A review on behalf of the CC-AFU.

INTRODUCTION: The incidence of localized renal cell carcinoma (RCC) is on the rise among individuals aged 70 and older. While the gold standard for treatment remains surgical resection, some elderly and frail patients with comorbidities are not eligible for this procedure. In selected cases, percutaneous thermal ablation, such as cryotherapy, microwave and radiofrequency, offers less invasive options. General anesthesia is sometimes necessary for such treatments, but most of the procedures can be conducted using mild or deep conscious sedation. This approach is preferably recommended for small cT1a tumors situated at a distance from the renal hilum and/or ureter. Active surveillance remains an alternative in the case of small low grade RCC although it may induce anxiety in certain patients. Recent research has highlighted the potentials of stereotactic ablative body radiotherapy (SABR) as a noninvasive, well-tolerated, and effective treatment for small renal tumors. This narrative review aims to explore recent advances in SABR for localized RCC, including appropriate patient selection, treatment modalities and administration, as well as efficacy and tolerance assessment. MATERIAL AND METHODS: We conducted a literature review using the terms [kidney cancer], [renal cell carcinoma], [stereotactic radiotherapy], [SBRT], and [SABR] in the Medline, PubMed, and Embase databases, focusing on prospective and relevant retrospective studies published in English. RESULTS: Studies report local control rates ranging from 70% to 100% with SABR, highlighting its efficacy in treating RCC. The decline in glomerular filtration rate (GFR) is approximately -5 to -17mL/min over the years following SABR. Common toxicities are rare, primarily CTCAE grade 1, include fatigue, nausea, chest or back pain, diarrhea, or gastritis. CONCLUSION: Stereotactic ablative body radiotherapy (SABR) may be considered as a viable option for patients with localized RCC who are not suitable candidates for surgery with a high local control rate and a favorable safety profile. This approach should be discussed in a multidisciplinary meeting and results from ongoing clinical trials are awaited.

Open versus robotic partial nephrectomy in obese patients: a multi-institutional propensity score-matched analysis (UroCCR 43-Robese study).

INTRODUCTION: There is limited evidence on the outcomes of robotic partial nephrectomy (RPN) and open partial nephrectomy (OPN) in obese patients (BMI ≥ 30 kg/m2). In this study, we aimed to compare perioperative and oncological outcomes of RPN and OPN. METHODS: We relied on data from patients who underwent PN from 2009 to 2017 at 16 departments of urology participating in the UroCCR network, which were collected prospectively. In an effort to adjust for potential confounders, a propensity-score matching was performed. Perioperative outcomes were compared between OPN and RPN patients. Disease-free survival (DFS) and overall survival (OS) were estimated using the Kaplan-Meier method and compared using the log-rank test. RESULTS: Overall, 1277 obese patients (932 robotic and 345 open were included. After propensity score matching, 166 OPN and 166 RPN individuals were considered for the study purposes; no statistically significant difference among baseline demographic or tumor-specific characteristics was present. A higher overall complication rate and major complications rate were recorded in the OPN group (37 vs. 25%, p = 0.01 and 21 vs. 10%, p = 0.007; respectively). The length of stay was also significantly longer in the OPN group, before and after propensity-score matching (p < 0.001). There were no significant differences in Warm ischemia time (p = 0.66), absolute change in eGFR (p = 0.45) and positive surgical margins (p = 0.12). At a median postoperative follow-up period of 24 (8-40) months, DFS and OS were similar in the two groups (all p > 0.05). CONCLUSIONS: In this study, RPN was associated with better perioperative outcomes (improvement of major complications rate and LOS) than OPN. The oncological outcomes were found to be similar between the two approaches.

Robotic YV plasty outcomes for bladder neck contracture vs. vesico-urethral anastomotic stricture.

PURPOSE: To compare the outcomes of patients undergoing robotic YV plasty for bladder neck contracture (BNC) vs. vesico-urethral anastomotic stricture (VUAS). METHODS: A retrospective study included male patients who underwent robotic YV plasty for BNC after endoscopic treatment of BPH or VUAS between August 2019 and March 2023 at a single academic center. The primary assessed was the patency rate at 1 month post-YV plasty and during the last follow-up visit. RESULTS: A total of 21 patients were analyzed, comprising 6 in the VUAS group and 15 in the BNC group. Patients with VUAS had significantly longer operative times (277.5 vs. 146.7 min; p = 0.008) and hospital stay (3.2 vs. 1.7 days; p = 0.03). Postoperative complications were more common in the VUAS group (66.7% vs. 26.7%; p = 0.14). All patients resumed spontaneous voiding postoperatively. Five patients (23.8%) who developed de novo stress urinary incontinence had already an AUS (n = 1) or required concomitant AUS implantation (n = 3), all of whom were in the VUAS group (83.3% vs. 0%; p < 0.0001). The proportion of patients improved was similar in both groups (PGII = 1 or 2: 83.3% vs. 80%; p = 0.31). Stricture recurrence occurred in 9.5% of patients in the whole cohort, with no significant difference between the groups (p = 0.50). Long-term reoperation was required in three VUAS patients, showing a statistically significant difference between the groups (p = 0.05). CONCLUSION: Robotic YV plasty is feasible for both VUAS and BNC. While functional outcomes and stricture-free survival may be similar for both conditions, the perioperative outcomes were less favorable for VUAS patients.

The Impact of Histological Variants on Oncological Outcomes After Surgical Resection of a Nonmetastatic Renal Cell Carcinoma with Tumor Thrombus: A Multi-institutional Study.

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 < 0.05). In a multivariable analysis, pRCC was independently associated with worse disease-free survival and OS (hazard ratio [HR]: 1.71; p = 0.01 and HR: 1.24; p = 0.04), while chRCC was associated with more favorable outcomes than ccRCC (HR: 0.05; p < 0.001 and HR: 0.02; p < 0.001). A limitation of the study is its retrospective nature. Conclusions: In this multicentric series, HVs appeared to impact the medium-term oncological prognosis of kidney cancer with TT. Patient summary: This study investigated the differences in oncological outcomes among histological variants (clear cell, papillary, and chromophobe) in a cohort of nonmetastatic renal cell carcinoma patients with venous tumor thrombus extension. We observed that these histological variants within this specific subgroup exhibit distinct outcomes, with papillary renal cell carcinoma being associated with the worst prognosis.

UroPredict: Machine learning model on real-world data for prediction of kidney cancer recurrence (UroCCR-120).

Renal cell carcinoma (RCC) is most often diagnosed at a localized stage, where surgery is the standard of care. Existing prognostic scores provide moderate predictive performance, leading to challenges in establishing follow-up recommendations after surgery and in selecting patients who could benefit from adjuvant therapy. In this study, we developed a model for individual postoperative disease-free survival (DFS) prediction using machine learning (ML) on real-world prospective data. Using the French kidney cancer research network database, UroCCR, we analyzed a cohort of surgically treated RCC patients. Participating sites were randomly assigned to either the training or testing cohort, and several ML models were trained on the training dataset. The predictive performance of the best ML model was then evaluated on the test dataset and compared with the usual risk scores. In total, 3372 patients were included, with a median follow-up of 30 months. The best results in predicting DFS were achieved using Cox PH models that included 24 variables, resulting in an iAUC of 0.81 [IC95% 0.77-0.85]. The ML model surpassed the predictive performance of the most commonly used risk scores while handling incomplete data in predictors. Lastly, patients were stratified into four prognostic groups with good discrimination (iAUC = 0.79 [IC95% 0.74-0.83]). Our study suggests that applying ML to real-world prospective data from patients undergoing surgery for localized or locally advanced RCC can provide accurate individual DFS prediction, outperforming traditional prognostic scores.

Updated systematic review and network meta-analysis of first-line treatments for metastatic renal cell carcinoma with extended follow-up data.

Immune checkpoint inhibitor (ICI)-based combination therapies are the recommended first-line treatment for metastatic renal cell carcinoma (mRCC). However, no head-to-head phase-3 randomized controlled trials (RCTs) have compared the efficacy of different ICI-based combination therapies. Here, we compared the efficacy of various first-line ICI-based combination therapies in patients with mRCC using updated survival data from phase-3 RCTs. Three databases were searched in June 2023 for RCTs that analyzed oncologic outcomes in mRCC patients treated with ICI-based combination therapies as first-line treatment. A network meta-analysis compared outcomes including overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and complete response (CR) rate. Subgroup analyses were based on the International mRCC Database Consortium risk classification. The treatment ranking analysis of the entire cohort showed that nivolumab + cabozantinib (81%) had the highest likelihood of improving OS, followed by nivolumab + ipilimumab (75%); pembrolizumab + lenvatinib had the highest likelihood of improving PFS (99%), ORR (97%), and CR (86%). These results remained valid even when the analysis was limited to patients with intermediate/poor risk, except that nivolumab + ipilimumab had the highest likelihood of achieving CR (100%). Further, OS benefits of ICI doublets were not inferior to those of ICI + tyrosine kinase inhibitor combinations. Recommendation of combination therapies with ICIs and/or tyrosine kinase inhibitors based on survival benefits and patient pretreatment risk classification will help advance personalized medicine for mRCC.

Prognostic Significance of Grade Discrepancy Between Primary Tumor and Venous Thrombus in Nonmetastatic Clear-cell Renal Cell Carcinoma: Analysis of the REMEMBER Registry and Implications for Adjuvant Therapy.

BACKGROUND: Further stratification of the risk of recurrence of clear-cell renal cell carcinoma (ccRCC) with venous tumor thrombus (VTT) will facilitate selection of candidates for adjuvant therapy. OBJECTIVE: To assess the impact of tumor grade discrepancy (GD) between the primary tumor (PT) and VTT in nonmetastatic ccRCC on disease-free survival (DFS), overall survival (OS), and cancer-specific survival (CSS). DESIGN, SETTING, AND PARTICIPANTS: This was a retrospective analysis of a multi-institutional nationwide data set for patients with pT3N0M0 ccRCC who underwent radical nephrectomy and thrombectomy. OUTCOMES MEASUREMENTS AND STATISTICAL ANALYSIS: Pathology slides were centrally reviewed. GD, a bidirectional variable (upgrading or downgrading), was numerically defined as the VTT grade minus the PT grade. Multivariable models were built to predict DFS, OS, and CSS. RESULTS AND LIMITATIONS: We analyzed data for 604 patients with median follow-up of 42 mo (excluding events). Tumor GD between VTT and PT was observed for 47% (285/604) of the patients and was an independent risk factor with incremental value in predicting the outcomes of interest (all p < 0.05). Incorporation of tumor GD significantly improved the performance of the ECOG-ACRIN 2805 (ASSURE) model. A GD-based model (PT grade, GD, pT stage, PT sarcomatoid features, fat invasion, and VTT consistency) had a c index of 0.72 for DFS. The hazard ratios were 8.0 for GD = +2 (p < 0.001), 1.9 for GD = +1 (p < 0.001), 0.57 for GD = -1 (p = 0.001), and 0.22 for GD = -2 (p = 0.003) versus GD = 0 as the reference. According to model-converted risk scores, DFS, OS, and CSS significantly differed between subgroups with low, intermediate, and high risk (all p < 0.001). CONCLUSIONS: Routine reporting of VTT upgrading or downgrading in relation to the PT and use of our GD-based nomograms can facilitate more informed treatment decisions by tailoring strategies to an individual patient's risk of progression. PATIENT SUMMARY: We developed a tool to improve patient counseling and guide decision-making on other therapies in addition to surgery for patients with the clear-cell type of kidney cancer and tumor invasion of a vein.

Clinical Application of Digital and Computational Pathology in Renal Cell Carcinoma: A Systematic Review.

CONTEXT: Computational pathology is a new interdisciplinary field that combines traditional pathology with modern technologies such as digital imaging and machine learning to better understand the diagnosis, prognosis, and natural history of many diseases. OBJECTIVE: To provide an overview of digital and computational pathology and its current and potential applications in renal cell carcinoma (RCC). EVIDENCE ACQUISITION: A systematic review of the English-language literature was conducted using the PubMed, Web of Science, and Scopus databases in December 2022 according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PROSPERO ID: CRD42023389282). Risk of bias was assessed according to the Prediction Model Study Risk of Bias Assessment Tool. EVIDENCE SYNTHESIS: In total, 20 articles were included in the review. All the studies used a retrospective design, and all digital pathology techniques were implemented retrospectively. The studies were classified according to their primary objective: detection, tumor characterization, and patient outcome. Regarding the transition to clinical practice, several studies showed promising potential. However, none presented a comprehensive assessment of clinical utility and implementation. Notably, there was substantial heterogeneity for both the strategies used for model building and the performance metrics reported. CONCLUSIONS: This review highlights the vast potential of digital and computational pathology for the detection, classification, and assessment of oncological outcomes in RCC. Preliminary work in this field has yielded promising results. However, these models have not yet reached a stage where they can be integrated into routine clinical practice. PATIENT SUMMARY: Computational pathology combines traditional pathology and technologies such as digital imaging and artificial intelligence to improve diagnosis of disease and identify prognostic factors and new biomarkers. The number of studies exploring its potential in kidney cancer is rapidly increasing. However, despite the surge in research activity, computational pathology is not yet ready for widespread routine use.

Can Simplified PADUA Renal (SPARE) Nephrometry scoring system help predict renal function outcomes after robot-assisted partial nephrectomy? (UroCCR study 93).

BACKGROUND: The SPARE Nephrometry Score (NS) is described as easier to implement than the RENAL and PADUA NSs, currently more widely used. Our objective was to compare the accuracy of SPARE NS in predicting renal function outcomes following RAPN. METHODS: A multicentric retrospective study was conducted using French kidney cancer network (UroCCR, NCT03293563) database. All patients included had RAPN for cT1 renal tumors between May 2010 and March 2021. SPARE was compared to RENAL, PADUA and Tumor Size to predict postoperative acute kidney injury (AKI), chronic kidney disease (CKD) upstaging, de novo CKD at 3-6 months follow-up and Trifecta failure. The ability of the different NSs and tumor size to predict renal function outcomes was evaluated using uni- and multivariate logistic regression models. RESULTS: According to our study criteria, 1171 patients were included. Mean preoperative tumor size and estimated glomerular filtration rate (eGFR) were 3.4±1.4 cm and 85.8 mL/min/1.73 m2. In total, 266 (22.7%), 87 (7.4%), 94 (8%), and 624 (53.3%) patients had AKI, de novo CKD, CKD upstaging, and Trifecta failure, respectively. In multivariate analysis, all three NSs and tumor size were independent predictors of AKI, CKD de novo, CKD upgrade and Trifecta failure. There was no significant difference between all three NS and tumor sizes in predicting renal function outcomes. CONCLUSIONS: SPARE Score seems to be a valid alternative to predict renal function outcomes after RAPN. Nevertheless, in our study, tumor size was as accurate as NSs in predicting postoperative outcomes and, therefore, seems to be the logical choice for surgical decisions.

Clinical trial protocol for P-NeLoP: a randomized controlled trial comparing the feasibility and outcomes of robot-assisted partial nephrectomy with low insufflation pressure using AirSeal versus standard insufflation pressure (UroCCR no. 85 study).

Robot-assisted partial nephrectomy (RAPN) is the standard of care for small, localized kidney tumors. This surgery is conducted within a short hospital stay and can even be performed as outpatient surgery in selected patients. In order to allow early rehabilitation of patients, an optimal control of postoperative pain is necessary. High-pressure pneumoperitoneum during surgery seems to be the source of significant pain during the first hours postoperatively. Our study is a prospective, randomized, multicenter, controlled study which aims to compare post-operative pain at 24 h between patients undergoing RAPN at low insufflation pressure (7 mmHg) and those operated on at standard pressure (12 mmHg) using the AirSeal system.This trial is registered in the US National Library of Medicine Trial Registry (NCT number: NCT05404685).

Deep Learning Methodologies Applied to Digital Pathology in Prostate Cancer: A Systematic Review.

Deep learning (DL), often called artificial intelligence (AI), has been increasingly used in Pathology thanks to the use of scanners to digitize slides which allow us to visualize them on monitors and process them with AI algorithms. Many articles have focused on DL applied to prostate cancer (PCa). This systematic review explains the DL applications and their performances for PCa in digital pathology. Article research was performed using PubMed and Embase to collect relevant articles. A Risk of Bias (RoB) was assessed with an adaptation of the QUADAS-2 tool. Out of the 77 included studies, eight focused on pre-processing tasks such as quality assessment or staining normalization. Most articles (n = 53) focused on diagnosis tasks like cancer detection or Gleason grading. Fifteen articles focused on prediction tasks, such as recurrence prediction or genomic correlations. Best performances were reached for cancer detection with an Area Under the Curve (AUC) up to 0.99 with algorithms already available for routine diagnosis. A few biases outlined by the RoB analysis are often found in these articles, such as the lack of external validation. This review was registered on PROSPERO under CRD42023418661.

Late complications and 5 years outcomes of robotic partial nephrectomy in France: prospective assessment in the French Kidney Cancer Research Network (UroCCR 10).

PURPOSE: To describe the practice of robotic-assisted partial nephrectomy (RAPN) in France and prospectively assess the late complications and long-term outcomes. METHODS: Prospective, multicenter (n = 16), observational study including all patients diagnosed with a renal tumor who underwent RAPN. Preoperative, intraoperative, postoperative, and follow-up data were collected and stored in the French research network for kidney cancer database (UroCCR). Patients were included over a period of 12 months, then followed for 5 years. RESULTS: In total, 466 patients were included, representing 472 RAPN. The mean tumor size was 3.4 ± 1.7 cm, most of moderate complexity (median PADUA and RENAL scores of 8 [7-10] and 7 [5-9]). Indication for nephron-sparing surgery was relative in 7.1% of cases and imperative in 11.8%. Intraoperative complications occurred in 6.8% of patients and 4.2% of RAPN had to be converted to open surgery. Severe postoperative complications were experienced in 2.3% of patients and late complications in 48 patients (10.3%), mostly within the first 3 months and mainly comprising vascular, infectious, or parietal complications. At 5 years, 29 patients (6.2%) had chronic kidney disease upstaging, 21 (4.5%) were diagnosed with local recurrence, eight (1.7%) with contralateral recurrence, 25 (5.4%) with metastatic progression, and 10 (2.1%) died of the disease. CONCLUSION: Our results reflect the contemporary practice of French expert centers and is, to our knowledge, the first to provide prospective data on late complications associated with RAPN. We have shown that RAPN provides good functional and oncologic outcomes while limiting short- and long-term morbidity. TRIAL REGISTRATION: NCT03292549.

Nephrectomy for kidney tumour increases the risk of de novo arterial hypertension.

OBJECTIVE: To evaluate prospectively the effects of surgical excision of renal tumours on blood pressure (BP). PATIENTS AND METHODS: In a multicentre prospective study, we evaluated 200 patients who underwent nephrectomy for renal tumour between 2018 and 2020 at seven departments of the French Network for Kidney Cancer, the UroCCR. All patients had localized cancer without pre-existing hypertension (HTN). Blood pressure was measured the week before nephrectomy, and at 1 month and 6 months after nephrectomy, according to the recommendations for home BP monitoring. Plasma renin was measured 1 week before surgery and 6 months after surgery. The primary endpoint was the occurrence of de novo HTN. The secondary endpoint was clinically significant increase in BP at 6 months, defined by an increase in systolic and/or diastolic ambulatory BP ≥10 mmHg or requirement for medical antihypertensive treatment. RESULTS: Blood pressure and renin measurements were available for 182 (91%) and 136 patients (68%), respectively. We excluded from the analysis 18 patients who had undeclared HTN detected on preoperative measurements. At 6 months, 31 patients (19.2%) had de novo HTN and 43 patients (26.3%) had a significant increase in their BP. Type of surgery was not associated with an increased risk of HTN (21.7% partial nephrectomy [PN] vs 15.7% radical nephrectomy [RN]; P = 0.59). There was no difference between plasmatic renin levels before and after surgery (18.5 vs 16; P = 0.46). In multivariable analysis, age (odds ratio [OR] 1.07, 95% confidence interval [CI] 1.02-1.12; P = 0.03) and body mass index (OR 1.14, 95% CI 1.03-1.26; P = 0.01) were the only predictors of de novo HTN. CONCLUSION: Surgical treatment of renal tumours is associated with significant changes in BP, with de novo HTN occurring in almost 20% of the patients. These changes are not impacted by the type of surgery (PN vs RN). Patients who are scheduled to undergo kidney cancer surgery should be informed of these findings and have their BP closely monitored after the operation.