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Predicting the progression of Alzheimer's

Date:
March 4, 2010
Source:
BioMed Central
Summary:
An assessment has been developed which reliably predicts future performance in cognition and activities of daily living for patients with Alzheimer's disease. Researchers followed 597 patients over 15 years to identify factors associated with slow, intermediate and rapid progression.
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An assessment has been developed which reliably predicts future performance in cognition and activities of daily living for patients with Alzheimer's disease. Researchers writing in BioMed Central's open access journal Alzheimer's Research & Therapy followed 597 patients over 15 years to identify factors associated with slow, intermediate and rapid progression.

Professor Rachelle Doody worked with a team of researchers from Baylor College of Medicine, Texas, US, to carry out the study. She said, "Patients and families frequently ask clinicians to predict expected rates of cognitive and functional decline, and clinicians currently have little basis for making such decisions. We've found that a simple, calculated progression rate at the initial visit gives reliable information regarding performance over time. The slowest progression group also survives longer."

The research team used a wide combination of standardized tests and scales to assess the ability of their method to predict abilities including memory, language, arithmetic and judgment/problem solving as well as the performance of daily skills over time. In addition to potential use in clinical practice, the team's classification methodology may also have research applications.

They write, "Currently, parallel group studies count on randomization to yield comparable placebo and treatment groups. Pre-progression rates are not assessed, yet imbalances across the treatment groups in this important variable could obscure or create treatment differences. Future clinical trials may benefit from gathering systematic data regarding individual symptom onset in order to perform a formal estimate of duration and to calculate pre-progression rates."


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Materials provided by BioMed Central. Note: Content may be edited for style and length.


Journal Reference:

  1. Rachelle S Doody, Valory Pavlik, Paul Massman, Susan D Rountree, Eveleen Darby and Wenyaw Chan. Predicting progression of Alzheimer's disease. Alzheimer's Research & Therapy, 2010; (in press) [abstract]

Cite This Page:

BioMed Central. "Predicting the progression of Alzheimer's." ScienceDaily. ScienceDaily, 4 March 2010. <www.sciencedaily.com/releases/2010/02/100222200858.htm>.
BioMed Central. (2010, March 4). Predicting the progression of Alzheimer's. ScienceDaily. Retrieved June 21, 2024 from www.sciencedaily.com/releases/2010/02/100222200858.htm
BioMed Central. "Predicting the progression of Alzheimer's." ScienceDaily. www.sciencedaily.com/releases/2010/02/100222200858.htm (accessed June 21, 2024).

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