Longitudinal Standards for Mid-life Cognitive Performance: Identifying Abnormal Within-Person Changes in the Wisconsin Registry for Alzheimer's Prevention

Abstract

Objectives: A major challenge in cognitive aging is differentiating preclinical disease-related cognitive decline from changes associated with normal aging. Neuropsychological test authors typically publish single time-point norms, referred to here as unconditional reference values. However, detecting significant change requires longitudinal, or conditional reference values, created by modeling cognition as a function of prior performance. Our objectives were to create, depict, and examine preliminary validity of unconditional and conditional reference values for ages 40-75 years on neuropsychological tests.

Method: We used quantile regression to create growth-curve-like models of performance on tests of memory and executive function using participants from the Wisconsin Registry for Alzheimer's Prevention. Unconditional and conditional models accounted for age, sex, education, and verbal ability/literacy; conditional models also included past performance on and number of prior exposures to the test. Models were then used to estimate individuals' unconditional and conditional percentile ranks for each test. We examined how low performance on each test (operationalized as <7th percentile) related to consensus-conference-determined cognitive statuses and subjective impairment.

Results: Participants with low performance were more likely to receive an abnormal cognitive diagnosis at the current visit (but not later visits). Low performance was also linked to subjective and informant reports of worsening memory function.

Conclusions: The percentile-based methods and single-test results described here show potential for detecting troublesome within-person cognitive change. Development of reference values for additional cognitive measures, investigation of alternative thresholds for abnormality (including multi-test criteria), and validation in samples with more clinical endpoints are needed. (JINS, 2019, 25, 1-14).

Keywords: Cognitive aging; Conditional standards; Executive function; Memory; Preclinical cognitive decline; Quantile regression.

Figure 1.

Longitudinal performance of three individuals (green) on each of three cognitive tests. Performances are plotted against demographically-adjusted unconditional standard lines for several percentiles (grey). Circles (red) indicate abnormal conditional performance (ACP). Additional case details: Figure 1a: Full-scale IQ=107 (68th percentile); has been involved with caregiving for family members since enrollment (including a parent with AD from Visits 1 to 3); worked as a manager at enrollment and retired between Visits 3 and 4. No self-report of significant history of mental health problems; CES-D scores in normal range for all visits. Significant back pain at Visit 5 required a minor testing accommodation. Figure 1b: Full scale IQ 113 (88th percentile); retired teacher/coach at enrollment; history of depression and anxiety (began taking buproprion between Visits 3 and 4); most recent CES-D score was 34, indicating moderate depressive symptomatology; also reports hearing difficulty (evident in testing at Visit 4). Figure 1c: Full-scale IQ of 133 (99th percentile); works as a management consultant (full-time at enrollment, part-time at and after Visit 2); no self-report of significant mental health history, and normal CES-D scores at all WRAP visits; stroke between Visits 2 and 3. Figure 1d: Full-scale IQ of 114 (81st percentile); former director of a company (retired between visits 3 and 4); treated for a tick-borne illness prior to third WRAP visit and diagnosed with cancer shortly after third visit. No behavioral observations noted during visits other than patient having time constraints.

Figure 2.

Confidence intervals on odds ratio estimates for ordinal regression predicting cognitive status from concurrent ACP.

Figure 3.

Predicted probability plots for models of ACP (first panel) and AUP (second panel) on AVLT Total as a function of subjective memory performance (x-axis). The linear predictor is shown in red, and the observed proportions at Visit 3 in black; the label indicates the total N observed at Visit 3 for each x-value.

Figure 4.

Proportions in each of four groups (Normal, AUP Only, ACP Only, ACP and AUP) with a final consensus diagnosis indicating a clinical status (MCI or Dementia). 95% confidence intervals were calculated using Wilson’s method (Brown et al., 2001).