Testing whether the progression of Alzheimer’s disease changes with the year of publication, additional design, and geographical area: a modeling analysis of literature aggregate data

Autor: Ningyuan Zhang, Xijun Zheng, Hongxia Liu, Qingshan Zheng, Lujin Li
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Alzheimer’s Research & Therapy, Vol 12, Iss 1, Pp 1-12 (2020)
Druh dokumentu: article
ISSN: 1758-9193
DOI: 10.1186/s13195-020-00630-5
Popis: Abstract Background Our objectives were to develop a disease progression model for cognitive decline in Alzheimer’s disease (AD) and to determine whether disease progression of AD is related to the year of publication, add-on trial design, and geographical regions. Methods Placebo-controlled randomized AD clinical trials were systemically searched in public databases. Longitudinal placebo response (mean change from baseline in the cognitive subscale of the Alzheimer’s Disease Assessment Scale [ADAS-cog]) and the corresponding demographic information were extracted to establish a disease progression model. Covariate screening and subgroup analyses were performed to identify potential factors affecting the disease progression rate. Results A total of 134 publications (140 trials) were included in this model-based meta-analysis. The typical disease progression rate was 5.82 points per year. The baseline ADAS-cog score was included in the final model using an inverse U-type function. Age was found to be negatively correlated with disease progression rate. After correcting the baseline ADAS-cog score and the age effect, no significant difference in the disease progression rate was found between trials published before and after 2008 and between trials using an add-on design and those that did not use an add-on design. However, a significant difference was found among different trial regions. Trials in East Asian countries showed the slowest decline rate and the largest placebo effect. Conclusions Our model successfully quantified AD disease progression by integrating baseline ADAS-cog score and age as important predictors. These factors and geographic location should be considered when optimizing future trial designs and conducting indirect comparisons of clinical outcomes.
Databáze: Directory of Open Access Journals
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