Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA, USA.
Alzheimers Dement. 2011 Jul;7(4):e84-93. doi: 10.1016/j.jalz.2010.08.233.
It is becoming increasingly important to study common and distinct etiologies, clinical and pathological features, and mechanisms related to neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and frontotemporal lobar degeneration. These comparative studies rely on powerful database tools to quickly generate data sets that match diverse and complementary criteria set by them.
In this article, we present a novel integrated neurodegenerative disease (INDD) database, which was developed at the University of Pennsylvania (Penn) with the help of a consortium of Penn investigators. Because the work of these investigators are based on Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and frontotemporal lobar degeneration, it allowed us to achieve the goal of developing an INDD database for these major neurodegenerative disorders. We used the Microsoft SQL server as a platform, with built-in "backwards" functionality to provide Access as a frontend client to interface with the database. We used PHP Hypertext Preprocessor to create the "frontend" web interface and then used a master lookup table to integrate individual neurodegenerative disease databases. We also present methods of data entry, database security, database backups, and database audit trails for this INDD database.
Using the INDD database, we compared the results of a biomarker study with those using an alternative approach by querying individual databases separately.
We have demonstrated that the Penn INDD database has the ability to query multiple database tables from a single console with high accuracy and reliability. The INDD database provides a powerful tool for generating data sets in comparative studies on several neurodegenerative diseases.
研究神经退行性疾病(如阿尔茨海默病、帕金森病、肌萎缩侧索硬化症和额颞叶痴呆)的常见和独特病因、临床和病理特征以及相关机制变得越来越重要。这些比较研究依赖于强大的数据库工具,以便根据他们设定的不同和互补标准快速生成数据集。
本文介绍了一种新的综合神经退行性疾病(INDD)数据库,该数据库由宾夕法尼亚大学(Penn)的研究人员在一个联盟的帮助下开发。由于这些研究人员的工作基于阿尔茨海默病、帕金森病、肌萎缩侧索硬化症和额颞叶痴呆,因此我们得以实现为这些主要神经退行性疾病开发 INDD 数据库的目标。我们使用 Microsoft SQL Server 作为平台,内置“向后”功能,将 Access 作为前端客户端与数据库接口。我们使用 PHP Hypertext Preprocessor 创建“前端”Web 界面,然后使用主查找表来集成各个神经退行性疾病数据库。我们还介绍了 INDD 数据库的数据录入、数据库安全、数据库备份和数据库审计跟踪方法。
使用 INDD 数据库,我们通过单独查询各个数据库来比较生物标志物研究的结果。
我们已经证明 Penn INDD 数据库具有从单个控制台查询多个数据库表的能力,具有高精度和可靠性。INDD 数据库为比较几种神经退行性疾病的研究生成数据集提供了强大的工具。