Presented at the 31st International Symposium on ALS/MND, December 9, 2020.
Background: The ongoing COVID-19 pandemic has made it difficult in some clinical settings to measure vital capacity for the purpose of eligibility determination. We developed a machine learning survival model without the use of baseline vital capacity measures and asked whether it could stratify clinical trial patients and a wider ALS patient population derived from a tertiary care ALS center (Emory University).
- A survival model that doesn’t use baseline vital capacity as a predictor can be built using machine learning
- Model degrades little compared to model that includes VC
- Model remains useful for stratification
- The “VC-free” survival model returns useful predictions for a clinical trial population as well as a broad ALS clinic population
- The model can be used to stratify ALS patients for ALS clinical trials in the absence of baseline vital capacity measurements
- Useful for inclusion/exclusion during COVID19 pandemic
Authors: Danielle Beaulieu, Jonavelle Cuerdo, David L. Ennist2020-12-09-ALS-MND-VC-Free-Model-ORIGENT