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

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 methods. Digital drug assignment (DDA) is a n...

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Published in:World journal of pediatrics : WJP 2023-10, Vol.19 (10), p.992-1008
Main Authors: Vodicska, Barbara, Déri, Júlia, Tihanyi, Dóra, Várkondi, Edit, Kispéter, Enikő, Dóczi, Róbert, Lakatos, Dóra, Dirner, Anna, Vidermann, Mátyás, Filotás, Péter, Szalkai-Dénes, Réka, Szegedi, István, Bartyik, Katalin, Gábor, Krisztina Míta, Simon, Réka, Hauser, Péter, Péter, György, Kiss, Csongor, Garami, Miklós, Peták, István
Format: Article
Language:English
Subjects:
Critical Care Medicine
Imaging
Intensive
Maternal and Child Health
Medicine
Medicine & Public Health
Original
Original Article
Pediatric Surgery
Pediatrics
Radiology
Surgery
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Summary: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 methods. Digital drug assignment (DDA) is a novel computational method to prioritize treatment options by aggregating numerous evidence-based associations between multiple drivers, targets, and targeted agents. DDA has been validated to improve personalized treatment decisions based on the outcome data of adult patients treated in the SHIVA01 clinical trial. The aim of this study was to evaluate the utility of DDA in pediatric oncology. Methods Between 2017 and 2020, 103 high-risk pediatric cancer patients (
ISSN:1708-8569
1867-0687
DOI:10.1007/s12519-023-00700-2