Center for Drug Clinical Research, Shanghai University of Traditional Chinese Medicine, No. 1200 Cailun Road, Shanghai, 201203, China.
Alzheimers Res Ther. 2020 May 26;12(1):64. doi: 10.1186/s13195-020-00630-5.
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.
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.
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.
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.
我们的目的是建立阿尔茨海默病(AD)认知衰退的疾病进展模型,并确定 AD 的疾病进展是否与发表年份、附加试验设计和地理区域有关。
在公共数据库中系统地搜索安慰剂对照的 AD 临床试验。提取纵向安慰剂反应(AD 评估量表认知子量表[ADAS-cog]从基线的平均变化)和相应的人口统计学信息,以建立疾病进展模型。进行了协变量筛选和亚组分析,以确定影响疾病进展率的潜在因素。
本基于模型的荟萃分析共纳入 134 篇文献(140 项试验)。典型的疾病进展率为每年 5.82 分。使用倒 U 型函数将基线 ADAS-cog 评分纳入最终模型。年龄与疾病进展率呈负相关。在校正基线 ADAS-cog 评分和年龄效应后,发现 2008 年前和 2008 年后发表的试验以及使用附加设计和不使用附加设计的试验之间,疾病进展率没有显著差异。然而,不同试验区域之间存在显著差异。东亚国家的试验显示出最慢的下降率和最大的安慰剂效应。
我们的模型通过整合基线 ADAS-cog 评分和年龄作为重要预测因素,成功地量化了 AD 疾病的进展。在优化未来试验设计和进行临床结果的间接比较时,应考虑这些因素和地理位置。