World Journal of Pediatrics · 20 authors, 9 centres
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This study evaluated a computational tool (DDA) for interpreting complex molecular profiling in 100 high-risk pediatric cancer patients. The tool identified actionable targeted therapy options in 72% of cases, and a molecular tumor board approved the top-ranked therapy in 78% of those actionable cases.
The study assessed the real-world utility of Digital Drug Assignment (DDA), a computational method for therapeutic decision support, in 100 pediatric high-risk cancer patients (<21 years). Samples underwent whole-exome or targeted panel sequencing, and results were processed by DDA. A molecular tumor board (MTB) evaluated the outputs. DDA identified potential targeted therapy options in 72 of 100 cases. The MTB approved a DDA-top-ranked treatment in 56 of 72 actionable cases (78%), with approved therapies having significantly higher aggregated evidence levels. The study demonstrates that DDA provides feasible and standardized support for interpreting genomic data, impacting clinical decision-making in over half of cases. Limitations include the lack of outcome data, potential generalizability issues from a single-country cohort, and that therapy administration was not tracked.
