The long-term goal of this project is to develop a comprehensive set of standardized Amyotrophic Lateral Sclerosis (ALS) clinical predictors that can be used to successfully characterize, diagnose, prognose, manage, and treat this devastating neurodegenerative disease. Specifically, the goal of this proposal is to identify and prioritize potential clinical predictors by exploring the relationships among measures and data recorded in retrospective ALS clinic patient records.
The specific aims of this proposal are to: 1) Construct a multi-variate relational ALS patient database that organizes and translates raw records, both on a patient and per-visit basis, into unified structures required for data mining analyses;2) Assess correlations of ALS patient clinic measures using standard parametric/non-parametric analyses as well as novel, dynamic relational analyses capable of revealing temporal changes/patterns with disease progression. The primary outcomes of this R21 proposal are a prioritized list of promising ALS clinical predictors and the developed plans by which to pursue them in future in-depth statistical studies. The secondary outcome is one of the largest, detailed, and all- inclusive data sets on clinical ALS.
This project is highly relevant to public health as it seeks to identify demographic, onset, prognostic, and treatment clinical predictors that aid clinicians in the management and intervention of the neurodegenerative disease Amyotrophic Lateral Sclerosis (ALS).