Story recall performance and AT classification via positron emission tomography: A comparison of logical memory and Craft Story 21

Early detection of Alzheimer's disease (AD) is one of the critical components of the global response to the growing dementia crisis. Analysis of serial position performance in story recall tests has yielded sensitive metrics for the prediction of AD at low cost. In this study, we examined whether serial position markers in two story recall tests (the logical memory test, LMT, and the Craft Story 21 test, CST) were sensitive to cross-sectional biomarker-based assessment of in vivo neuropathology.

Participants were selected from the Wisconsin Registry of Alzheimer's Prevention (n = 288; WRAP) and the Alzheimer's Disease Research Center (n = 156; ADRC), both from the University of Wisconsin-Madison. Average age at PET was 68.9 (6.7) and 67.0 (8.0), respectively. Data included tau and PiB PET, and LMT for WRAP participants and CST for ADRC participants. Two sets of Bayesian analyses (logistic regressions and ANCOVAs) were conducted within each cohort, separately.

Results indicated that the A+T+ classification was best predicted, cross-sectionally, by the recency ratio (Rr), indexing how much of the end of the story was forgotten between initial learning and delayed assessment. Rr outperformed traditional scores and discriminated between A+T+ and A+T-/A-T-, in both cohorts.

Overall, this study confirms that serial position analysis of LMT and CST data, and particularly Rr as an index of recency loss, is a valuable tool for the identification of in vivo tau pathology in individuals free of dementia. Diagnostic considerations are discussed.