Abdul‐Muhsin, Haidar

412 Background: Previously we have reported comparative effectiveness data regarding survival of first line (1L) treatment options in mRCC. However, it is not known how the life-prolonging frontline combinations compare to patient-reported outcomes. Methods: Electronic databases including MEDLINE and EMBASE were searched from each database’s inception through July 1st 2023. Phase III randomized controlled trials (RCTs) assessing 1L immune-checkpoint inhibitor (ICI) combination therapies for mRCC and reporting HrQoL were included. Small sample size adjusted standardized mean differences (SMD; Hedges’ g) with 95% confidence intervals (CI) were computed for global, physical, functional, and emotional QoL. Positive SMD indicated an improvement. A network meta-analysis was conducted to assess the comparative HrQoL across different treatment options. P-scores were computed to assess relative treatment rankings. Results: Of 5770 citations identified, five trials (nine references) were included in this analysis. Patient-reported outcomes have not been reported in the JAVELIN Renal 101 or COSMIC-313 trials yet. Global QoL was significantly improved with cabozantinib-nivolumab (CaboNivo) as compared to Nivo-ipilimumab (SMD 2.74, 95% CI 2.54; 2.93), lenvatinib-pembrolizumab (LenPem; 2.79, 2.53; 3.06), sunitinib (2.87, 2.72; 3.03), Pem-axitinib (PemAxi; 3.09, 2.89; 3.30) and atezolizumab-bevacizumab (AteBev; 3.24, 3.04; 3.45). Global QoL improvement was also observed with NivoIpi compared to sunitinib (0.14, 0.02; 0.25), PemAxi (0.36, 0.18; 0.54) and AteBev (0.51, 0.33; 0.68). Physical QoL improvement were consistent with CaboNivo. Likewise, LenPem significantly improved QoL compared to sunitinib (0.26, 0.04; 0.47), PemAxi (0.38, 0.13; 0.64) and NivoIpi (0.51, 0.27; 0.76). Significant functional QoL benefits were only observed with CaboNivo (0.32, 0.17; 0.48) and NivoIpi (0.19, 0.08; 0.31) compared to sunitinib. No significant mixed treatment comparisons were observed for emotional QoL, however, currently available data suggests that LenPem (rank 1) may potentially improve QoL (Table). Conclusions: CaboNivo and NivoIpi as 1L therapy may offer an improved overall HrQoL compared to other contemporary treatment options in mRCC. [Table: see text]

e16550 Background: Improved computational power and modern algorithms have generated significant interest in radiomics for cancer diagnosis and staging. Here we assess the performance of deep learning (DL) models as a means for feature extraction in combination with supervised machine learning (ML) algorithms for accurate staging and chemotherapy response assessment of bladder cancer. Methods: Deidentified grayscale CT images from bladder cancer patients scheduled to undergo radical cystectomy were included in this retrospective study. These images were manually annotated with two regional masks (normal region and cancer region). Five DL models- namely, AlexNet, GoogleNet, InceptionV3, ResNet-50, and XceptionNet pre-trained on the ImageNet dataset, a public dataset, were then fine-tuned on our bladder CT scan data to extract features. Through feature selection process, the subset of the features was used to build ML classifiers for classification. The classification was performed using five different ML classifiers, namely k-Nearest Neighbor (KNN), Naïve-Bayes (NB), Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), and Decision Tree (DT). The classification task was performed with 10-fold cross-validation, and each of the experiments contained a different but not mutually exclusive subset of samples. The evaluation metrics include accuracy, sensitivity, specificity, precision, and F1-score. Results: A total of 200 deidentified grayscale CT images of 100 patients with histologically proven bladder cancer, were included in this study. For experiment (1) normal vs. cancer, the LDA classifier on XceptionNet based features provides the best performance with an accuracy of 86.07%, sensitivity of 96.75%, specificity of 69.65%, precision of 83.07%, and F1-score of 89.39%. For experiment (2) non-muscle invasive Cancer (NMIBC) vs. muscle invasive bladder cancer (MIBC), the LDA classifier on XceptionNet based features provided the best performance with an accuracy of 79.72%, sensitivity of 66.62%, specificity of 87.39%, precision of 75.58%, and F1-score of 70.81%. For experiment (3) T0 lesion vs. MIBC, the LDA classifier on XceptionNet based features provides the best performance with an accuracy of 74.96%, sensitivity of 80.51%, specificity of 70.22%, precision of 69.78%, and F1-score of 74.73%. Conclusions: Our proposed model has shown good results in differentiating normal vs cancer and promising performance in differentiating T0 vs MIBC after chemotherapy treatment. We are expanding our dataset to further improve the performance in differentiating T0 vs MIBC. In addition, we will investigate the applicability of GAN for data augmentation to address data limit. We believe the hybrid DL and ML framework may facilitates radiologists' decisions and clinical decision-making in patients with bladder cancer.

536 Background: The management of malignant mesothelioma of the tunica vaginalis of the testes (MMTVT) is not clearly defined, though retroperitoneal lymph node dissection has been reported as a diagnostic and potentially therapeutic option. Herein we present our experience with robot assisted retroperitoneal lymph node dissection (RARPLND) in a series of patients with MMTVT. Methods: The Mayo Clinic cancer registry was queried from 1972-present for all patients who had a diagnosis of MMTVT. Six patients were identified, five of whom were treated with RPLND, where four underwent RARPLND. Data was collected on pertinent demographic, preoperative, perioperative, postoperative outcomes and follow-up oncological data. Results: In five patients who underwent RPLND, the median age was 50 years (IQR 34-51), median BMI was 26.9 (IQR 26.4-30.6). Four patients originally presented with right sided symptomatic hydroceles, while one presented with right sided chronic epididymitis. Orchiectomy (one simple, two inguinal radical) was performed in three patients and hydrocelectomy in the other two patients prior to presentation. Preoperative cross-sectional imaging, including PET-CT scan in three patients, was negative for lymphadenopathy or metastasis. RARPLND was performed in 4/5 (80%) cases and concomitant hemiscrotectomy in 4/5 (80%) cases. Full bilateral template was performed in three patients and right modified template was performed in the remaining two. Median lymph node yield was 29 (IQR 22-32) and median blood loss was 275 cc (IQR 200-300). Positive retroperitoneal lymph nodes were found in 3/5 (60%) cases. Final margins of hemiscrotectomy were negative in all four cases. All patients who underwent RARPLND were discharged home on postoperative day one. One patient received four cycles of adjuvant Cisplatin and Pemetrexed. Mean follow-up was 27 months (range 2-47). No patients recurred. Conclusions: MMTVT is a very rare malignancy with high potential for retroperitoneal lymph node dissemination. Regardless of the approach, RPLND may provide both a diagnostic and therapeutic benefit, with the robotic approach affording a potentially expedited recovery.

AbstractRobotic surgical techniques are now being applied in the setting of retroperitoneal lymphadenectomy (RPLND) for testicular cancer. While laparoscopic RPLND has not been widely accepted, reports of robot assisted RPLND (RARPLND) are emerging. This manuscript will review the application of RPLND for testicular cancer, evolution of minimally invasive techniques, the controversies, and current status of RARPLND. J. Surg. Oncol. 2015;112:736–740. © 2015 Wiley Periodicals, Inc.