Clinical factors associated with neurofibromatosis type 1

Takeaway

  • Machine learning models were able to accurately predict those patients with a diagnosis of optic pathway glioma (OPG) or attention-deficit/hyperactivity disorder (ADHD) based on readily available clinical and demographic data in children with neurofibromatosis type 1 (NF1).

Why this matters

  • NF1 is a common genetic condition affecting around 1 in every 3,000 births with extreme clinical variability. Currently, clinicians are unable to predict the disease course in an individual child and tailored care is challenging.

  • OPG and ADHD are both known manifestations of NF1. It is unclear whether any clinical or demographic factors are associated with increased risk of developing these complications, and whether a machine learning approach based on this data could help to predict disease course in an individual child.