The PRO-ACT database: design, initial analyses, and predictive features

To pool data from completed amyotrophic lateral sclerosis (ALS) clinical trials and create an open-access resource that enables greater understanding of the phenotype and biology of ALS. Clinical trials data were pooled from 16 completed phase II/III ALS clinical trials and one observational study....

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Bibliographic Details
Published in:	Neurology Vol. 83; no. 19; p. 1719
Main Authors:	Atassi, Nazem, Berry, James, Shui, Amy, Zach, Neta, Sherman, Alexander, Sinani, Ervin, Walker, Jason, Katsovskiy, Igor, Schoenfeld, David, Cudkowicz, Merit, Leitner, Melanie
Format:	Journal Article
Language:	English
Published:	United States 04.11.2014
Subjects:	Amyotrophic Lateral Sclerosis - diagnosis Amyotrophic Lateral Sclerosis - physiopathology Amyotrophic Lateral Sclerosis - therapy Clinical Trials as Topic - statistics & numerical data Database Management Systems Datasets as Topic - statistics & numerical data Disease Progression Humans Longitudinal Studies Observational Studies as Topic - statistics & numerical data Predictive Value of Tests Research Design
ISSN:	1526-632X, 1526-632X
Online Access:	Get more information
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Summary:	To pool data from completed amyotrophic lateral sclerosis (ALS) clinical trials and create an open-access resource that enables greater understanding of the phenotype and biology of ALS. Clinical trials data were pooled from 16 completed phase II/III ALS clinical trials and one observational study. Over 8 million de-identified longitudinally collected data points from over 8,600 individuals with ALS were standardized across trials and merged to create the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database. This database includes demographics, family histories, and longitudinal clinical and laboratory data. Mixed effects models were used to describe the rate of disease progression measured by the Revised ALS Functional Rating Scale (ALSFRS-R) and vital capacity (VC). Cox regression models were used to describe survival data. Implementing Bonferroni correction, the critical p value for 15 different tests was p = 0.003. The ALSFRS-R rate of decline was 1.02 (±2.3) points per month and the VC rate of decline was 2.24% of predicted (±6.9) per month. Higher levels of uric acid at trial entry were predictive of a slower drop in ALSFRS-R (p = 0.01) and VC (p < 0.0001), and longer survival (p = 0.02). Higher levels of creatinine at baseline were predictive of a slower drop in ALSFRS-R (p = 0.01) and VC (p < 0.0001), and longer survival (p = 0.01). Finally, higher body mass index (BMI) at baseline was associated with longer survival (p < 0.0001). The PRO-ACT database is the largest publicly available repository of merged ALS clinical trials data. We report that baseline levels of creatinine and uric acid, as well as baseline BMI, are strong predictors of disease progression and survival.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	1526-632X 1526-632X
DOI:	10.1212/WNL.0000000000000951