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.

Purpose: The Alzheimer’s Continuum (AC) includes 2 preclinical stages defined by subjective cognitive complaints, transitional cognitive declines, and neurobehavioral symptoms. Operationalization of these stages is necessary for them to be applied in research. Methods: Cognitively normal individuals with known amyloid biomarker status were selected from the National Alzheimer’s Coordinating Center Uniform Data Set. Participants and their caregivers provided information on subjective cognitive complaints, neurobehavioral features, and objective cognitive functioning. Patients: The sample included 101 amyloid positive (A+) and 447 amyloid negative (A−) individuals. Results: Rates of subjective cognitive complaints (A+: 34.90%, A−: 29.90%) and neurobehavioral symptoms (A+: 22.40%, A−: 22.40%) did not significantly differ between A+/− individuals. However, the frequency of transitional cognitive decline was significantly higher among A+ (38.00%) than A− participants (24.90%). We explored various empirical definitions for defining the early stages of the AC among A+ participants. Rates of classification into AC stage 1 versus AC stage 2 varied depending on the number of symptoms required: 57.40% versus 42.60% (1 symptom), 28.70% versus 71.30% (2 symptoms), and 6.90% versus 93.10% (all 3 symptoms). Conclusion: The presence of 2 of the proposed symptom classes to separate AC stage 2 from stage 1 seems to provide a good empirical balance.

We examined the impact of conventional versus robust normative approaches on cognitive characterization and clinical classification of MCI versus dementia. The sample included participants from the National Alzheimer's Coordinating Center Uniform Data Set. Separate demographically adjusted z‐scores for cognitive tests were derived from conventional (n = 4273) and robust (n = 602) normative groups. To assess the impact of deriving scores from a conventional versus robust normative group on cognitive characterization, we examined likelihood of having a low score on each neuropsychological test. Next, we created receiver operating characteristic (ROC) curves for the ability of normed scores derived from each normative group to differentiate between MCI (n = 3570) and dementia (n = 1564). We examined the impact of choice of normative group on classification accuracy by comparing sensitivity and specificity values and areas under the curves (AUC). Compared with using a conventional normative group, using a robust normative group resulted in a higher likelihood of low cognitive scores for individuals classified with MCI and dementia. Comparison of the classification accuracy for distinguishing MCI from dementia did not suggest a statistically significant advantage for either normative approach (Z = −0.29, p = .77; AUC = 0.86 for conventional and AUC = 0.86 for robust). In summary, these results indicate that using a robust normative group increases the likelihood of characterizing cognitive performance as low. However, there is not a clear advantage of using a robust over a conventional normative group when differentiating between MCI and dementia.

Objective Subjective and objective cognitive declines are given equal weight as symptoms of pre-mild cognitive impairment in Alzheimer’s disease by recent research criteria. However, the overlap of these constructs is unclear. We used standardized regression-based (SRB) change to define subtle objective cognitive decline across serial neuropsychological assessments. We then examined the associations between objective change and subjective cognitive complaints. Finally, we investigated the impact of different symptom combinations on rates of classification for the early stages of the Alzheimer’s Continuum. Method Data from 1,341 cognitively intact older adults with serial Uniform Data Set 3.0 Neuropsychological Battery assessments (6–24-month follow-ups) were used to compute SRB declines at the following z-scores cut-points: −1.282, −1.645, and − 1.96. We used Chi-square tests and Cohen’s kappa statistics to evaluate the relationship between SRB change and presence/absence of subjective cognitive decline at follow-up. We also examined the prevalence rates of different symptom combinations in an amyloid positive sample (n = 29). Results The base rate of having at least one significant SRB decline ranged from 26.00% to 59.40%. Subjective cognitive decline was positively associated with SRB-defined decline in the normative sample, though agreement was limited (= − .01–.10). SRB decline with no subjective decline occurred in 0.0–37.90% of amyloid positive participants, while 3.40–37.90% had subjective but not objective decline. 37.90–79.30% of amyloid positive participants exhibited either SRB or subjective decline. Conclusions Subjective and objective cognitive declines appear to represent unique symptom classes and should be separately considered when staging patients on the Alzheimer’s Continuum.

Background: The concept of mild cognitive impairment (MCI) has evolved since its original conception. So, too, have MCI diagnostic methods, all of which have varying degrees of success in identifying individuals at risk of conversion to dementia. The neuropsychological actuarial method is a straightforward diagnostic approach that has shown promise in large datasets in identifying individuals with MCI who are likely to have progressive courses. This method has been increasingly applied in various iterations and samples, raising questions of how best to apply this method and when caution should be used. Objective: Our objective was to review the literature investigating use of the neuropsychological actuarial method to diagnose MCI to identify strengths and weaknesses of this approach, as well as highlight areas for further research. Methods: Databases PubMed and PsychInfo were systematically searched for studies that compared the neuropsychological actuarial method to some other diagnostic method. Results: We identified 13 articles and extracted relevant study characteristics and findings. Existing literature was reviewed and integrated, with focus on the neuropsychological actuarial method’s performance relative to existing diagnostic methods/criteria as well as associations with longitudinal outcomes and biomarkers. Tables with pertinent methodological information and general findings are also provided. Conclusion: The neuropsychological actuarial method to diagnose MCI has shown utility some in large-scale homogenous databases compared to research criteria. However, its standing relative to consensus diagnostic methods is unclear, and emerging evidence suggests the neuropsychological actuarial method may be more prone to diagnostic errors in more demographically diverse populations.