Design and analysis of neurological and stroke studies have been challenged by the lack of a single primary outcome that can comprehensively assess the multidimensional impairments and symptoms associated with the disease. For example, it is known that individual outcome measures for Parkinson's disease (PD), even the MDS-UPDRS, cannot comprehensively capture the full spectrum of PD signs and symptoms. The global per- centile outcome offers an ef?cient and stable way to integrate multiple individual outcomes, providing a single metric of the global disease severity. The O'Brien's global rank-sum test allows two or K-group comparisons for the global percentile outcome and has been successfully applied in many clinical trials, including the Neuropro- tection Exploratory Trials in Parkinson's Disease (NET-PD) Long-term Study 1 (LS-1) and FS-ZONE. However, rigorous statistical tools have been lacking for regression modeling of the global percentile outcome, preventing systematic explorations of risk factors for global disease burden and global disease progression. Motivated by these challenges and opportunities, (Aim 1) we propose a novel and rigorous regression framework to explicitly link the global percentile outcome to multiple risk factors, under minimal modeling assumptions regarding the link function and the error distribution. Our estimation procedure exploits information in the ranks to achieve robust estimation, yielding a risk score that is in maximum concordance with global disease severity. Next, (Aim 2) we will develop a sensible regression framework for exploring the time-trend of the global percentile outcome with longitudinal data, to speci?cally detect risk factors that lead to accelerated progression in global ranks. We further extend our methods to accommodate the common dropout mechanisms of missing completely at random and missing at random. Furthermore, (Aim 3) we will apply the proposed methods to systematically an- alyze risk factors of global disease severity and global disease progression in the LS-1 study and the FS-ZONE study. Our methods bear substantial practical utility for researchers in neurological diseases and many other ?elds. We will provide user-friendly software for all statistical tools to the general research community.

Public Health Relevance

Design and analysis of neurological and stroke studies have been challenged by the lack of a single primary outcome that can comprehensively assess the multidimensional impairments and symptoms. New statistical tools are proposed to overcome newly emerging challenges for global percentile outcome, to facilitate unified and conclusive explorations of risk factors for global disease burden and global disease progression. The clinical findings by applying the proposed methods will potentially improve practice guidelines for neurological diseases and to better inform health policy.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Small Research Grants (R03)
Project #
1R03NS108136-01A1
Application #
9745447
Study Section
Biostatistical Methods and Research Design Study Section (BMRD)
Program Officer
Gilbert, Peter R
Project Start
2019-04-01
Project End
2021-03-31
Budget Start
2019-04-01
Budget End
2020-03-31
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Texas Health Science Center Houston
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
800771594
City
Houston
State
TX
Country
United States
Zip Code
77030