{"doi":"10.3233/jad-240081","title":"Mayo Normative Studies: Amyloid and Neurodegeneration Negative Normative Data for the Auditory Verbal Learning Test and Sex-Specific Sensitivity to Mild Cognitive Impairment/Dementia","abstract":"Background: Conventional normative samples include individuals with undetected Alzheimer's disease neuropathology, lowering test sensitivity for cognitive impairment. Objective: We developed Mayo Normative Studies (MNS) norms limited to individuals without elevated amyloid or neurodegeneration (A-N-) for Rey's Auditory Verbal Learning Test (AVLT). We compared these MNS A-N- norms in female, male, and total samples to conventional MNS norms with varying levels of demographic adjustments. Methods: The A-N- sample included 1,059 Mayo Clinic Study of Aging cognitively unimpaired (CU) participants living in Olmsted County, MN, who are predominantly non-Hispanic White. Using a regression-based approach correcting for age, sex, and education, we derived fully-adjusted T-score formulas for AVLT variables. We validated these A-N- norms in two independent samples of CU (n = 261) and mild cognitive impairment (MCI)/dementia participants (n = 392) > 55 years of age. Results: Variability associated with age decreased by almost half in the A-N- norm sample relative to the conventional norm sample. Fully-adjusted MNS A-N- norms showed approximately 7- 9% higher sensitivity to MCI/dementia compared to fully-adjusted MNS conventional norms for trials 1- 5 total and sum of trials. Among women, sensitivity to MCI/dementia increased with each normative data refinement. In contrast, age-adjusted conventional MNS norms showed greatest sensitivity to MCI/dementia in men. Conclusions: A-N- norms show some benefits over conventional normative approaches to MCI/dementia sensitivity, especially for women. We recommend using these MNS A-N- norms alongside MNS conventional norms. Future work is needed to determine if normative samples that are not well characterized clinically show greater benefit from biomarker-refined approaches.","journal":"Journal of Alzheimer s Disease","year":2024,"id":465923,"datarank":0.2747377319668671,"base_score":1.6094379124341003,"endowment":1.6094379124341003,"self_citation_contribution":0.24141568686511508,"citation_network_contribution":0.03332204510175204,"self_endowment_contribution":0.24141568686511508,"citer_contribution":0.03332204510175204,"corpus_percentile":42.6549083313994,"corpus_rank":7414,"citation_count":4,"citer_count":2,"citers_with_citation_signal":1,"citers_with_endowment":1,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.8394,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":462439,"name":"Teresa J. Christianson","orcid":null,"position":1,"is_corresponding":false},{"id":1056431,"name":"Shehroo B. Pudumjee","orcid":"0000-0002-4969-9321","position":2,"is_corresponding":false},{"id":259154,"name":"Angelina J. Polsinelli","orcid":"0000-0002-7738-9574","position":3,"is_corresponding":false},{"id":318778,"name":"Emily S. Lundt","orcid":"0000-0002-4754-8642","position":4,"is_corresponding":false},{"id":292107,"name":"Ryan D. Frank","orcid":"0000-0002-5561-0637","position":5,"is_corresponding":false},{"id":253903,"name":"Walter K. Kremers","orcid":"0000-0001-5714-3473","position":6,"is_corresponding":false},{"id":259156,"name":"Mary M. Machulda","orcid":"0000-0003-4834-5967","position":7,"is_corresponding":false},{"id":253904,"name":"Julie A. Fields","orcid":"0000-0002-1282-9866","position":8,"is_corresponding":false},{"id":49956,"name":"Clifford R. Jack","orcid":"0000-0001-7916-622X","position":9,"is_corresponding":false},{"id":49955,"name":"David S. Knopman","orcid":"0000-0002-6544-066X","position":10,"is_corresponding":false},{"id":66487,"name":"Jonathan Graff-Radford","orcid":null,"position":11,"is_corresponding":false},{"id":226058,"name":"Prashanthi Vemuri","orcid":"0000-0003-4286-0589","position":12,"is_corresponding":false},{"id":228538,"name":"Michelle M. Mielke","orcid":"0000-0001-7177-1185","position":13,"is_corresponding":false},{"id":27599,"name":"Ronald C. Petersen","orcid":"0000-0002-8178-6601","position":14,"is_corresponding":false},{"id":651188,"name":"Nikki H. Stricker","orcid":"0000-0001-9034-1252","position":0,"is_corresponding":true}],"reference_count":46,"raw_metadata":null,"created_at":"2026-07-19T02:04:50.328230Z","pmid":"38995784","pmcid":"PMC11307010","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}