Can data elements collected during routine clinical care be used to characterize people with Neurofibromatosis Type 1 (NF1) as high and low risk for malignancy?
The generation of a self-sustaining, annotated clinical database supports the development of applications such as a predictive nomogram for people with Neurofibromatosis Type 1 (NF1) developing the rare, but aggressive and hard to diagnose sarcoma, MPNST. Such real-life data-driven predictive models will have tremendous value to patients, caregivers, clinicians and third party payers. Development of data-driven predictive tools for rare diseases like NF1, NF2 and schwannomatosis will also improve the efficiency of clinical therapeutic development via targeted enrollment.
Improve diagnostic accuracy for people living with NF1, NF2 and schwannomatosis to reduce health insecurity and its associated stress, eliminate unnecessary testing and associated health care spending and improve the speed and accuracy of diagnosis and treatment with the ultimate goal of improving patient outcomes. The NF PMCOE’s first project is to apply existing clinical and genetic data to create predictive models to determine which individuals with NF1 are at high versus low risk for MPNST.
Questions we're asking that inform us on how to best care for patients include:
Can statistical models built with clinical and genetic data allow creation of accurate prediction calculators for risk of malignancy that can ultimately be used to identify people at high versus low risk of malignancy for more effective screening?
Do data driven predictive calculators improve cost-effectiveness versus current diagnostic approaches for people with NF1?
Patient Care for Neurofibromatosis
The Johns Hopkins Comprehensive Neurofibromatosis (NF) Center is a multidisciplinary clinic that combines the expertise of pediatric and adult neurology, neurosurgery, neuro-oncology and genetics. Find out more about care at the NF Center.
Bronwyn Slobogean, P.A.-C.