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- W2766195306 abstract "The development of effective drugs in Alzheimer's disease has been challenging. Recently, several promising drugs have failed to show efficacy. Measurements at baseline and during the study to assess the efficacy of the drug depend on consistent, standard administration of scoring instruments. However, when the interviews and assessments of subjects during a clinical study are independently monitored, administration and scoring errors by the persons performing the assessments (the “raters”) are frequently detected. In a large, global clinical trial, 13,408 ADAS-Cogs and 8,904 MMSE from 5 study visits were reviewed for administration and scoring errors by doctoral-level clinicians for scoring and administrative accuracy. Forty-three percent of the visits were found to have at least one administrative or scoring error in the application of the measurement instrument. If efficacy in a clinical trial is defined as a 3-point change in the ADAS-Cog, identifying 29% of the scale administrations that led to a scoring correction drastically improve the quality of the data. Data Surveillance was effective at identifying administration and scoring errors, retraining raters and correcting erroneous scores resulting in improved data quality. Raters in a large, global Alzheimer's disease trail were screened for previous experience with the MMSE and the ADAS-Cog. Raters were provided training and required to submit a mock interview that was assessed for accuracy of administraion. Screening visits were video tapped and reviewed along with worksheets by doctoral level clinicians for administration and scoring accuracy. Subsequent visits scoresheets were reviewed for accuracy. Forty-three percent of all visits had a least one scoring or administrive error. Raters tended to not make the same error but continued to make minor errors. 29% of errors on the ADAS-Cog and 19% of errors on the MMSE led to a scoring change recommendation which were accepted by the raters 98% of the time. Correcting errors in a large number of visits has significant impact on data. Data surveillance remains critical to data quality for all clinician rated outcome measures. Streamlining surveillances methodology and improving electronic data capture tools will further improve data quality." @default.
- W2766195306 created "2017-11-10" @default.
- W2766195306 creator A5019880958 @default.
- W2766195306 date "2017-07-01" @default.
- W2766195306 modified "2023-09-27" @default.
- W2766195306 title "[P4-283]: DATA SURVEILLANCE TO IMPROVE ADAS-COG AND MMSE ASSESSMENT IN GLOBAL ALZHEIMER's DISEASE CLINICAL TRIALS" @default.
- W2766195306 doi "https://doi.org/10.1016/j.jalz.2017.06.2152" @default.
- W2766195306 hasPublicationYear "2017" @default.
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