Biological and prognostic implications of biopsy upgrading for high-grade upper tract urothelial carcinoma at nephroureterectomy

Objectives Technical limitations of ureteroscopic (URS) biopsy has been considered responsible for substantial upgrading rate in upper tract urothelial carcinoma (UTUC). However, the impact of tumor specific factors for upgrading remain uninvestigated. Methods Patients who underwent URS biopsy were included between 2005 and 2020 at 13 institutions. We assessed the prognostic impact of upgrading (low-grade on URS biopsy) versus same grade (high-grade on URS biopsy) for high-grade UTUC tumors on radical nephroureterectomy (RNU) specimens. Results This study included 371 patients, of whom 112 (30%) and 259 (70%) were biopsy-based low- and high-grade tumors, respectively. Median follow-up was 27.3 months. Patients with high-grade biopsy were more likely to harbor unfavorable pathologic features, such as lymphovascular invasion (p < 0.001) and positive lymph nodes (LNs; p < 0.001). On multivariable analyses adjusting for the established risk factors, high-grade biopsy was significantly associated with worse overall (hazard ratio [HR] 1.74; 95% confidence interval [CI], 1.10-2.75; p = 0.018), cancer-specific (HR 1.94; 95% CI, 1.07-3.52; p = 0.03), and recurrence-free survival (HR 1.80; 95% CI, 1.13-2.87; p = 0.013). In subgroup analyses of patients with pT2-T4 and/or positive LN, its significant association retained. Furthermore, high-grade biopsy in clinically non-muscle invasive disease significantly predicted upstaging to final pathologically advanced disease (>= pT2) compared to low-grade biopsy. Conclusions High tumor grade on URS biopsy is associated with features of biologically and clinically aggressive UTUC tumors. URS low-grade UTUC that becomes upgraded to high-grade might carry a better prognosis than high-grade UTUC on URS. Tumor specific factors are likely to be responsible for upgrading to high-grade on RNU

Comparing Oncological and Perioperative Outcomes of Open versus Laparoscopic versus Robotic Radical Nephroureterectomy for the Treatment of Upper Tract Urothelial Carcinoma: A Multicenter, Multinational, Propensity Score-Matched Analysis

OBJECTIVES To identify correlates of survival and perioperative outcomes of upper tract urothelial carcinoma (UTUC) patients undergoing open (ORNU), laparoscopic (LRNU), and robotic (RRNU) radical nephroureterectomy (RNU). METHODS We conducted a retrospective, multicenter study that included non-metastatic UTUC patients who underwent RNU between 1990-2020. Multiple imputation by chained equations was used to impute missing data. Patients were divided into three groups based on their surgical treatment and were adjusted by 1:1:1 propensity score matching (PSM). Survival outcomes per group were estimated for recurrence-free survival (RFS), bladder recurrence-free survival (BRFS), cancer-specific survival (CSS), and overall survival (OS). Perioperative outcomes: Intraoperative blood loss, hospital length of stay (LOS), and overall (OPC) and major postoperative complications (MPCs; defined as Clavien-Dindo > 3) were assessed between groups. RESULTS Of the 2434 patients included, 756 remained after PSM with 252 in each group. The three groups had similar baseline clinicopathological characteristics. The median follow-up was 32 months. Kaplan-Meier and log-rank tests demonstrated similar RFS, CSS, and OS between groups. BRFS was found to be superior with ORNU. Using multivariable regression analyses, LRNU and RRNU were independently associated with worse BRFS (HR 1.66, 95% CI 1.22-2.28, p = 0.001 and HR 1.73, 95%CI 1.22-2.47, p = 0.002, respectively). LRNU and RRNU were associated with a significantly shorter LOS (beta -1.1, 95% CI -2.2-0.02, p = 0.047 and beta -6.1, 95% CI -7.2-5.0, p < 0.001, respectively) and fewer MPCs (OR 0.5, 95% CI 0.31-0.79, p = 0.003 and OR 0.27, 95% CI 0.16-0.46, p < 0.001, respectively). CONCLUSIONS In this large international cohort, we demonstrated similar RFS, CSS, and OS among ORNU, LRNU, and RRNU. However, LRNU and RRNU were associated with significantly worse BRFS, but a shorter LOS and fewer MPCs

Machine learning in renal cell carcinoma research: the promise and pitfalls of ’renal-izing’ the potential of artificial intelligence

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Artificial intelligence in functional urology: how it may shape the future

International audiencePurpose of review The aim of the present manuscript is to provide an overview on the current state of artificial intelligence (AI) tools in either decision making, diagnosis, treatment options, or outcome prediction in functional urology. Recent findings Several recent studies have shed light on the promising potential of AI in functional urology to investigate lower urinary tract dysfunction pathophysiology but also as a diagnostic tool by enhancing the existing evaluations such as dynamic magnetic resonance imaging or urodynamics. AI may also improve surgical education and training because of its automated performance metrics recording. By bringing prediction models, AI may also have strong therapeutic implications in the field of functional urology in the near future. AI may also be implemented in innovative devices such as e-bladder diary and electromechanical artificial urinary sphincter and could facilitate the development of remote medicine. Over the past decade, the enthusiasm for AI has been rising exponentially. Machine learning was well known, but the increasing power of processors and the amount of data available has provided the platform for deep learning tools to expand. Although the literature on the applications of AI technology in the field of functional urology is relatively sparse, its possible uses are countless especially in surgical training, imaging, urodynamics, and innovative devices

Can Molecular Classifications Help Tailor First-line Treatment of Metastatic Renal Cell Carcinoma? A Systematic Review of Available Models

International audienceCONTEXT: The advent of immune check inhibitors (ICIs) has tremendously changed the prognosis of metastatic renal cell carcinoma (mRCC), adding an unseen substantial overall survival benefit. These agents could be administered alone or in combination with anti-vascular endothelial growth factor (anti-VEGF) therapies. So far, treatment allocation is based only on clinical stratification risk models. OBJECTIVE: Herein, we aimed to report the different molecular classifications reported in the first-line treatment of mRCC and discuss the awaited clinical implications in terms of treatment selection. EVIDENCE ACQUISITION: Medline database as well as European Society for Medical Oncology (ESMO)/American Society of Clinical Oncology (ASCO) conference proceedings were searched to identify biomarker studies. Inclusion criteria comprised randomized and nonrandomized clinical trials that included patients treated in the first line of mRCC setting, patients treated with anti-VEGF therapies or ICIs, biological modeling, and available survival outcomes. EVIDENCE SYNTHESIS: Four classification models were identified with subsequent clinical implications: Beuselinck model (34 gene signatures), IMmotion150, Hakimi, and JAVELIN 101 model. Tumor profiling shows distinct outcomes when treated with one or other combination. Patients are clustered into two gene signatures: angiogenic and proinflammatory (as per JAVELIN). The first is more likely to respond to therapy that includes anti-VEGF agents, while the best outcomes are obtained with an ICI combination with the second. CONCLUSIONS: The findings presented here were mostly derived from ancillary registered studies of new drugs in the setting of mRCC. Further validation is needed, which sets new paradigms for investigation in clinical research based on tumor biology for treatment allocation and not only on clinical stratification tools. PATIENT SUMMARY: First-line treatment of metastatic kidney includes immunotherapy alone or in combination with antiangiogenic therapy. However, clinical practice demonstrated that the &quot;one treatment fits all&quot; strategy might not be the best approach. In fact, recent studies showed that the addition of immunotherapy agents will not benefit all patients equally, and some still respond either equally to or better than anti-vascular endothelial growth factor alone. This review revealed biomarker modeling that impacts treatment selection. Recent tumor profiling into &quot;angiogenic signature&quot; more sensitive to angiogenic agents versus &quot;immune signature&quot; more likely to achieve the best response with immunotherapy should be validated. Tumor biology features might be more powerful than clinical classification for a tailored treatment approach

Radiomic analysis of liver grafts from brain-dead donors can predict early allograft dysfunction following transplantation: a proof-of-concept study

International audienceBACKGROUND: Selection of liver grafts suitable for transplantation (LT) mainly depends on a surgeon’s subjective assessment. This study aimed to investigate the role of radiomic analysis of donor-liver CTs after brain death (DBD) to predict the occurrence of early posttransplant allograft dysfunction (EAD). METHODS: We retrospectively extracted and analyzed the left lobe radiomic features from CT scans of DBD livers in training and validation cohorts. Multivariate analysis was performed to identify predictors of EAD. RESULTS: From 126 LTs included in the study in the training cohort, 27 (21.4%) had an EAD. For each patient, 279 radiomic features were extracted of which 5 were associated with EAD (AUC = 0.81) (95% CI 0.72-0.89). Among donor and recipient clinical characteristics, cardiac arrest, steatosis on donor’s CT, cold ischemic time and age of recipient were also identified as independent risk factors for EAD. Combined radiomic signature and clinical risk factors showed a strong predictive performance for EAD with a C-index of 0.90 (95% CI 0.84-0.96). A validation cohort of 23 patients confirmed these results. CONCLUSION: Radiomic signatures extracted from donor CT scan, independently or combined with clinical risk factors is an objective and accurate biomarker for prediction of EAD after LT

Localisations tumorales secondaires testiculaires

National audienceTestis tumors are uncommon in oncology, and testicular metastasis from distant solid tumors are even rarer. We present two cases encountered in our department of pathology in CHU de Rennes, France. Moreover, we collected all reported cases in the Medline/PubMed databases of non-hematopoietic secondary testis tumors in adults, excluding autopsy studies, to propose an integrative study on this topic. In total, we report 98 cases of secondary testis lesions to prostate (n=38, 38.77 %), colorectal (n=19, 19.39%), gastric (n=12, 12.24%), kidney (n=7, 7.14%), lung (n=6, 6.12%) and other primary cancers. The median age at diagnosis was 66.5 years. We identified significantly more prostate adenocarcinoma (P&lt;0.0001) when the primary tumor was known and significantly more colorectal adenocarcinoma (P=0.035) and pancreatic adenocarcinoma (P=0.002) when the primary tumor was unknown. The age at diagnosis was older when the primary tumor was known (P=0.007). We present the challenges for the diagnosis and propose some elements for diagnosis orientation. Finally, we discuss the possible ways of metastatic dissemination from primary site to testis, as illustrated by the two cases we present

Impact of routine imaging in the diagnosis of recurrence for patients with localized and locally advanced renal tumor treated with nephrectomy

International audienceObjective - Modalities of surveillance to detect recurrence after nephrectomy for localized or locally advanced renal tumor are not standardized. The aim was to assess the impact of surveillance scheme on oncological outcomes. Methods - Patients treated for localized or locally advanced renal tumor with total or partial nephrectomy between 2006 and 2010 in an academic institution were included retrospectively. According to the University of California Los Angeles Integrated Staging System (UISS) protocol, follow-up was considered adequate or not. Symptoms, location and number of lesions at recurrence diagnosis were collected. Recurrence-free, cancer-specific and overall survivals were estimated using the Kaplan-Meier method and compared with the log-rank test. Cox proportional hazards regression models were calculated to identify prognostic factors. Results - A total of 267 patients were included. Median follow-up was 72 months. Recurrence rate was 23.2% (62/267 patients). Recurrences were local (16%), single metastatic (23%), oligo-metastatic (15%) or multi-metastatic (46%). 72.6% of the recurrences occurred within the 3 years after surgery. No recurrence was diagnosed by chest X-ray or abdominal ultrasound. One hundred and twenty-one patients had inadequate follow-up. They had similar recurrence-free survival, cancer-specific survival and overall survival as patients with adequate follow-up. In multivariable analysis, the presence of multi-metastatic lesions was an independent prognostic factor of worse cancer-specific mortality after recurrence diagnosis (HR = 10.15, 95% CI: 2.29-44.82, p = 0.002). Conclusion - Role of chest X-ray and abdominal ultrasound for the detection of recurrences is limited. Rigorous follow-up according to the UISS protocol does not improve oncological outcomes. Follow-up schedules with less frequent imaging should be discussed

Role of quantitative computed tomography texture analysis in the prediction of adherent perinephric fat

International audienceObjective - To assess the performance of computed tomography (CT) texture analysis to predict the presence of adherent perinephric fat (APF). Materials and methods - Seventy patients with small renal tumors treated with robot-assisted partial nephrectomy were included. Patients were divided into two groups according to the presence of APF. We extracted 15 image features from unenhanced CT and contrast-enhanced CT corresponding to first-order and second-order Haralick textural features. Predictors of APF were evaluated by univariable and multivariable analysis. Receiver operating characteristic (ROC) analysis was performed and the area under the ROC curve (AUC) to predict APF was calculated for the independent predictors. Results - APF was observed in 26 patients (37%). We identified entropy (p = 0.01), sum entropy (p = 0.02) and difference entropy (p = 0.05) as significant independent predictors of APF. In the portal phase, we identified correlation (p = 0.03), inverse difference moment (p = 0.01), sum entropy (p = 0.02), entropy (p = 0.01), difference variance (p = 0.04) and difference entropy (p = 0.02) as significant independent predictors of APF. Combining these parameters yielded to an ROC-AUC of 0.82 (95% CI 0.65-0.86). Conclusion - Results from this preliminary study suggest that CT texture analysis might be a promising quantitative imaging tool that helps urologist to identify APF

MP75-08 COULD PERIRENAL FAT BE MORE IMPORTANT THAN THE TUMOR ITSELF? THE MAP SCORE BETTER PREDICTS PERIOPERATIVE MORBIDITY THAN THE RENAL SCORE

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