Andrew M Kiselica1, Alyssa N Kaser2, Troy A Webber3, Brent J Small4, Jared F Benge1,5,6. 1. Division of Neuropsychology, Baylor Scott and White Health, Temple, TX, USA. 2. Department of Psychology and Neuroscience, Baylor University, Waco, TX, USA. 3. Michael E. Debakey VAMC, Houston, TX, USA. 4. School of Aging Studies, University of South Florida, Tampa, FL, USA. 5. Plummer Movement Disorders Center, Temple, TX, USA. 6. Texas A&M College of Medicine, Bryan, TX, USA.
Abstract
OBJECTIVE: An increasing focus in Alzheimer's disease and aging research is to identify transitional cognitive decline. One means of indexing change over time in serial cognitive evaluations is to calculate standardized regression-based (SRB) change indices. This paper includes the development and preliminary validation of SRB indices for the Uniform Data Set 3.0 Neuropsychological Battery, as well as base rate data to aid in their interpretation. METHOD: The sample included 1,341 cognitively intact older adults with serial assessments over 0.5-2 years in the National Alzheimer's Coordinating Center Database. SRB change scores were calculated in half of the sample and then validated in the other half of the sample. Base rates of SRB decline were evaluated at z-score cut-points, corresponding to two-tailed p-values of .20 (z = -1.282), .10 (z = -1.645), and .05 (z = -1.96). We examined convergent associations of SRB indices for each cognitive measure with each other as well as concurrent associations of SRB indices with clinical dementia rating sum of box scores (CDR-SB). RESULTS: SRB equations were able to significantly predict the selected cognitive variables. The base rate of at least one significant SRB decline across the entire battery ranged from 26.70% to 58.10%. SRB indices for cognitive measures demonstrated theoretically expected significant positive associations with each other. Additionally, CDR-SB impairment was associated with an increasing number of significantly declined test scores. CONCLUSIONS: This paper provides preliminary validation of SRB indices in a large sample, and we present a user-friendly tool for calculating SRB values.
OBJECTIVE: An increasing focus in Alzheimer's disease and aging research is to identify transitional cognitive decline. One means of indexing change over time in serial cognitive evaluations is to calculate standardized regression-based (SRB) change indices. This paper includes the development and preliminary validation of SRB indices for the Uniform Data Set 3.0 Neuropsychological Battery, as well as base rate data to aid in their interpretation. METHOD: The sample included 1,341 cognitively intact older adults with serial assessments over 0.5-2 years in the National Alzheimer's Coordinating Center Database. SRB change scores were calculated in half of the sample and then validated in the other half of the sample. Base rates of SRB decline were evaluated at z-score cut-points, corresponding to two-tailed p-values of .20 (z = -1.282), .10 (z = -1.645), and .05 (z = -1.96). We examined convergent associations of SRB indices for each cognitive measure with each other as well as concurrent associations of SRB indices with clinical dementia rating sum of box scores (CDR-SB). RESULTS: SRB equations were able to significantly predict the selected cognitive variables. The base rate of at least one significant SRB decline across the entire battery ranged from 26.70% to 58.10%. SRB indices for cognitive measures demonstrated theoretically expected significant positive associations with each other. Additionally, CDR-SB impairment was associated with an increasing number of significantly declined test scores. CONCLUSIONS: This paper provides preliminary validation of SRB indices in a large sample, and we present a user-friendly tool for calculating SRB values.
Authors: RoShunna Lea; Jared F Benge; Charles H Adler; Thomas G Beach; Christine M Belden; Nan Zhang; Holly A Shill; Erika Driver-Dunckley; Shyamal H Mehta; Alireza Atri Journal: J Clin Exp Neuropsychol Date: 2022-02-09 Impact factor: 2.475
Authors: Eva C Alden; Emily S Lundt; Erin L Twohy; Teresa J Christianson; Walter K Kremers; Mary M Machulda; Clifford R Jack; David S Knopman; Michelle M Mielke; Ronald C Petersen; Nikki H Stricker Journal: Alzheimers Dement (Amst) Date: 2022-07-15