Accuracy of the Clinical Diagnosis of Alzheimer Disease at National Institute on Aging Alzheimer's Disease Centers, 2005–2010

By T. Beach, Sarah E. Monsell, L. Phillips, W. Kukull. Journal of Neuropathology and Experimental Neurology, 2012

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Abstract The neuropathologic examination is considered to provide the gold standard for Alzheimer disease (AD). To determine the accuracy of currently used clinical diagnostic methods, clinical and neuropathologic data from the National Alzheimer’s Coordinating Center, which gathers information from the network of National Institute on Aging (NIA)-sponsored Alzheimer Disease Centers (ADCs), were collected as part of the National Alzheimer’s Coordinating Center Uniform Data Set (UDS) between 2005 and 2010. A database search initially included all 1198 subjects with at least one UDS clinical assessment and who had died and been autopsied; 279 were excluded as being not demented or because critical data fields were missing. The final subject number was 919. Sensitivity and specificity were determined based on “probable” and “possible” AD levels of clinical confidence and 4 levels of neuropathologic confidence based on varying neuritic plaque densities and Braak neurofibrillary stages. Sensitivity ranged from 70.9% to 87.3%; specificity ranged from 44.3% to 70.8%. Sensitivity was generally increased with more permissive clinical criteria and specificity was increased with more restrictive criteria, whereas the opposite was true for neuropathologic criteria. When a clinical diagnosis was not confirmed by minimum levels of AD histopathology, the most frequent primary neuropathologic diagnoses were tangle-only dementia or argyrophilic grain disease, frontotemporal lobar degeneration, cerebrovascular disease, Lewy body disease and hippocampal sclerosis. When dementia was not clinically diagnosed as AD, 39% of these cases met or exceeded minimum threshold levels of AD histopathology. Neurologists of the NIA-ADCs had higher predictive accuracy when they diagnosed AD in subjects with dementia than when they diagnosed dementing diseases other than AD. The misdiagnosis rate should be considered when estimating subject numbers for AD studies, including clinical trials and epidemiologic studies.

Subfields: Physiology, Psychiatry and Mental health

View Paper: https://www.semanticscholar.org/paper/59ed18597d0cb2e750fc7f3c928871aedf079d0a

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Citations in the corpus

Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines (2020, methodology): “Leveraging deep learning fusion techniques consistently showed improvements in performance for Alzheimer ’ s disease diagnosis, while physicians struggle with accurate and reliable diagnostics even when multimodality is present, as proven by histopathological correlation 42 .”
CSF biomarkers of Alzheimer’s disease concord with amyloid-β PETand predict clinical progression: A study of fully automated immunoassays in BioFINDER and ADNI cohorts (2018, background): “It is well established, from combined clinical and neuropathologic studies [5,6], and clinical trials using amyloid-b PET scans [7], that the accuracy of clinical criteria is suboptimal.”
Contribution of cerebrovascular disease in autopsy confirmed neurodegenerative disease cases in the National Alzheimer's Coordinating Centre. (2013, background): “For instance, 40% of patients with clinically diagnosed FTD are found to have a neuropathological diagnosis of Alzheimer’s disease on post-mortem examination (Beach et al., 2012; Nelson et al., 2012; Toledo et al., 2012b).”
Biomarkers for Alzheimer's disease: current status and prospects for the future (2018, background): “diagnostic criteria for AD have poor accuracy, with sensitivity and specificity figures of around 7080% when related to neuropathology (21, 22).”
Pathology of Neurodegenerative Diseases. (2017, background): “Studying disease heterogeneity at autopsy is key to understanding discrepancies between clinical and pathological diagnoses (Hughes et al. 1992; Josephs and Dickson 2003; Beach et al. 2012; Adler et al. 2014).”
Defining imaging biomarker cut points for brain aging and Alzheimer's disease (2017, neutral): “Of individuals with clinically diagnosed AD dementia, 10%–30% do not have AD at autopsy [18] or have no biomarker evidence of amyloidosis [19,20].”