Browsing by Author "Sanderson-Cimino, Mark"

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    Development and validation of a harmonized memory score for multicenter Alzheimer's disease and related dementia research
    (medRxiv, 2025-04-03) Sanderson-Cimino, Mark; Gross, Alden L.; Gaynor, Leslie S.; Paolillo, Emily W.; Saloner, Rowan; Albert, Marilyn S.; Apostolova, Liana G.; Boersema, Brooke; Boxer, Adam L.; Boeve, Bradley F.; Casaletto, Kaitlin B.; Hallgarth, Savannah R.; Diaz, Valentina E.; Clark, Lindsay R.; Maillard, Pauline; Eloyan, Ani; Tomaszewski Farias, Sarah; Gonzales, Mitzi M.; Hammers, Dustin B.; La Joie, Renaud; Cobigo, Yann; Wolf, Amy; Hampstead, Benjamin M.; Mechanic-Hamilton, Dawn; Miller, Bruce L.; Rabinovici, Gil D.; Ringman, John M.; Rosen, Howie J.; Ryman, Sephira G.; Prestopnik, Jillian L.; Salmon, David P.; Smith, Glenn E.; DeCarli, Charles; Rajan, Kumar B.; Jin, Lee-Way; Hinman, Jason; Johnson, David K.; Harvey, Danielle; Fornage, Myriam; Kramer, Joel H.; Staffaroni, Adam M.; Neurology, School of Medicine
    Introduction: List-learning tasks are important for characterizing memory in ADRD research, but the Uniform Data Set neuropsychological battery (UDS-NB) lacks a list-learning paradigm; thus, sites administer a range of tests. We developed a harmonized memory composite that incorporates UDS memory tests and multiple list-learning tasks. Methods: Item-banking confirmatory factor analysis was applied to develop a memory composite in a diagnostically heterogenous sample (n=5943) who completed the UDS-NB and one of five list-learning tasks. Construct validity was evaluated through associations with demographics, disease severity, cognitive tasks, brain volume, and plasma phosphorylated tau (p-tau181 and p-tau217). Test-retest reliability was assessed. Analyses were replicated in a racially/ethnically diverse cohort (n=1058). Results: Fit indices, loadings, distributions, and test-retest reliability were adequate. Expected associations with demographics and clinical measures within development and validation cohorts supported validity. Discussion: This composite enables researchers to incorporate multiple list-learning tasks with other UDS measures to create a single metric.