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real-world performance analysis of a novel computational method in the precision oncology of pediatric tumors

World Journal of Pediatrics 2023年第10期19卷 992-1008页

作者： Barbara Vodicska Júlia déri dóra Tihanyi Edit Várkondi EnikőKispéter róbert dóczi dóra Lakatos Anna dirner Mátyás Vidermann Péter Filotás réka szalkai-dénes István Szegedi katalin Bartyik Krisztina Míta Gábor réka Simon Péter Hauser György Péter Csongor Kiss Miklós Garami István Peták Oncompass Medicine Hungary Kft Retek Str.34Budapest 1024Hungary division of Pediatric Hematology-Oncology Department of PediatricsFaculty of MedicineUniversity of DebrecenDebrecenHungary department of Pediatrics Albert Szent-Györgyi Medical SchoolUniversity of SzegedSzegedHungary Onco-Hematology department Velkey LászlóPaediatric Health CentreMiskolcHungary department of Paediatrics Semmelweis UniversityBudapestHungary Onco-Hematology department Heim Pál Children’s HospitalBudapestHungary department of Pharmacology and Pharmacotherapy Semmelweis UniversityBudapestHungary department of Pharmaceutical Sciences University of Illinois at ChicagoChicagoUSA Genomate Health CambridgeMAUSA

Background The utility of routine extensive molecular profiling of pediatric tumors is a matter of debate due to the high number of genetic alterations of unknown significance or low evidence and the lack of standardized and personalized decision support *** drug assignment(ddA)is a novel computational method to prioritize treatment options by aggregating numerous evidence-based associations between multiple drivers,targets,and targeted *** has been validated to improve personalized treatment decisions based on the outcome data of adult patients treated in the SHIVA01 clinical *** aim of this study was to evaluate the utility of ddA in pediatric *** Between 2017 and 2020,103 high-risk pediatric cancer patients(rs)were involved in our precision oncology program,and samples from 100 patients were eligible for further *** or blood samples were analyzed by whole-exome(WES)or targeted panel sequencing and other molecular diagnostic modalities and processed by a software system using the ddA algorithm for therapeutic decision ***,a molecular tumor board(MTB)evaluated the results to provide therapy *** Of the 100 cases with comprehensive molecular diagnostic data,88 yielded WES and 12 panel sequencing *** identified matching off-label targeted treatment options(actionability)in 72/100 cases(72%),while 57/100(57%)showed potential drug *** reached 88%(29/33)by 2020 due to the continuous updates of the evidence *** approved the clinical use of a ddA-top-listed treatment in 56 of 72 actionable cases(78%).The approved therapies had significantly higher aggregated evidence levels(AELs)than dismissed *** of WES results for targeted panels missed important mutations affecting therapy *** ddA is a promising approach to overcome challenges associated with the interpretation of extensive molecular profiling in the routine car

关键词： Computational decision support Pediatric tumors Precision oncology Tumor board

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