Now, an international team led by researchers at Dana-Farber Cancer Institute has developed an artificial intelligence model that may help doctors make those decisions with greater precision.
The findings are published in Nature Genetics.
The study describes MANTIS (Methylation profiling and Artificial Neural networks for Time-dependent Individualized Survival predictions), an AI model that uses DNA methylation profiling, a test already used to help diagnose brain tumors, to generate personalized survival predictions for children with medulloblastoma and ependymoma.
The researchers found that MANTIS outperformed current risk-prediction approaches for many patients across several large validation cohorts.
Rather than assigning patients to broad risk groups, the model estimates how survival probability changes over time based on the unique biology of each child's tumor.
When the researchers adapted MANTIS to estimate the likely effects of different radiation doses, the model suggested that more than half of children with average-risk medulloblastoma may be candidates for lower-dose craniospinal irradiation.
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