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You have accessJournal of UrologyCME1 May 2022MP59-02 APPLICATION OF A MULTIPLEX URINALYSIS TEST FOR THE PREDICTION OF INTRAVESICAL BCG TREATMENT RESPONSE: A PILOT STUDY Kaoru Murakami, Ashish M. Kamat, Yunfeng Dai, Ian Pagano, Runpu Chen, Yijun Sun, Amit Gupta, Nari Kim, Steve Goodison, Charles J. Rosser, and Hideki Furuya Kaoru MurakamiKaoru Murakami More articles by this author , Ashish M. KamatAshish M. Kamat More articles by this author , Yunfeng DaiYunfeng Dai More articles by this author , Ian PaganoIan Pagano More articles by this author , Runpu ChenRunpu Chen More articles by this author , Yijun SunYijun Sun More articles by this author , Amit GuptaAmit Gupta More articles by this author , Nari KimNari Kim More articles by this author , Steve GoodisonSteve Goodison More articles by this author , Charles J. RosserCharles J. Rosser More articles by this author , and Hideki FuruyaHideki Furuya More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002642.02AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Intravesical Bacillus Calmette-Guerin (BCG), a live attenuated tuberculosis vaccine that acts as a non-specific immune system stimulant, is the most effective adjuvant treatment for patients with intermediate or high-risk non-muscle-invasive bladder cancer (NMIBC). However, to date, there are no reliable tests that are predictive of BCG treatment response. In this study, we evaluated the performance of OncuriaTM, a bladder cancer detection test, to predict response to intravesical BCG. METHODS: OncuriaTM data was evaluated in voided urine samples obtained from a prospectively collected cohort of 64 subjects with intermediate or high risk NMIBC prior to treatment with intravesical BCG. The OncuriaTM test, which measures 10 cancer-associated biomarkers was performed in an independent clinical laboratory. The ability of the test to identify those patients in whom BCG is ineffective against tumor recurrence was tested. Predictive models were derived using supervised learning and cross-validation analyses. Model performance was assessed using ROC curves. RESULTS: Pre-treatment urinary concentrations of MMP9, VEGFA, CA9, SDC1, PAI1, APOE, A1AT, ANG and MMP10 were increased in patients who developed disease recurrence. A combinatorial predictive model of treatment outcome achieved an AUROC 0.89 [95% CI: 0.80–0.99], outperforming any single biomarker, with a test sensitivity of 81.8% and a specificity of 84.9%. Hazard ratio analysis revealed that patients with higher urinary levels of ANG, CA9 and MMP10 had a significantly higher risk of disease recurrence. CONCLUSIONS: Monitoring the urinary levels of a cancer-associated biomarker panel enabled the discrimination of patients who did not respond to intravesical BCG therapy. With further study, the multiplex OncuriaTM test may be applicable for the clinical evaluation of bladder cancer patients considering intravesical BCG treatment. We are currently performing a validation study with a larger retrospective cohort of ∼120 subjects with intermediate or high risk NMIBC prior to treatment with intravesical BCG. The results will be presented in the AUA 2022. Source of Funding: NIH/NCI R01CA198887 (CJR) © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e1001 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Kaoru Murakami More articles by this author Ashish M. Kamat More articles by this author Yunfeng Dai More articles by this author Ian Pagano More articles by this author Runpu Chen More articles by this author Yijun Sun More articles by this author Amit Gupta More articles by this author Nari Kim More articles by this author Steve Goodison More articles by this author Charles J. Rosser More articles by this author Hideki Furuya More articles by this author Expand All Advertisement PDF DownloadLoading ...

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