1. Precision of clinical diagnosis in neurodegenerative diseases: an investigation of 455 autopsied cases.
- Author
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Vöglein, Jonathan, Kostova, Irena, Arzberger, Thomas, Herms, Jochen, Roeber, Sigrun, Danek, Adrian, Höglinger, Günter, Giese, Armin, and Levin, Johannes
- Abstract
Background: Accuracy of clinical diagnosis in neurodegenerative diseases is critically important for patient care and study recruitment. We aimed to investigate the precision of clinical diagnosis of various neurodegenerative conditions using neuropathological diagnosis for reference. Method: All 1310 autopsy cases between 1993 and 2017 from the Neurobiobank München (Munich, Germany) were screened for neurodegenerative diagnoses. Neuropathological diagnoses that occurred in at least five cases were included in the study. Real world clinical diagnoses were extracted from medical records of admitting hospitals in Germany and correlated with neuropathological diagnoses. Sensitivity, specificity and accuracy (using receiver operating characteristic (ROC) curves and area under the curve (AUC) analysis) of clinical diagnoses were calculated. Result: The study included 455 cases with neuropathologically diagnosed Alzheimer's disease (AD, n = 132), argyrophilic grain disease (AGD, n = 6), corticobasal degeneration (CBD, n = 20), frontotemporal lobar degeneration (FTLD, n = 47), Huntington's disease (HD, n = 22), Lewy body disease (LBD, n = 104), motor neuron disease (MND, n = 10), multiple system atrophy (MSA, n = 37) and progressive supranuclear palsy (PSP, n = 77). Clinical diagnoses in these cases comprised AD (n = 136), CBD (n = 17), Creutzfeldt‐Jakob disease (CJD, n = 6), dementia with Lewy bodies (DLB, n = 11), frontotemporal dementia (FTD, n = 44), HD (n = 23), MND (n = 20), MSA (n = 36), Parkinson's disease (PD, n = 92), PSP (n = 60) and vascular dementia (VD, n = 10). Figure 1 illustrates the relationship between clinical (left) and neuropathological diagnoses (right). Figure 2 shows sensitivity, specificity, ROC curves, AUCs including standard errors (SE) and 95% confidence intervals (CI) and p‐values for testing the null hypothesis AUC = 0.5 for clinical diagnoses. Conclusion: Clinical diagnoses of neurodegenerative diseases exhibited a wide span of sensitivity depending on the particular disease (0‐100%) while specificity was high for all clinical diagnoses (89.5‐100%). Accuracy of clinical diagnoses as determined with AUC analysis was very good (AUC>0.9) for HD, MND and MSA, good (AUC = 0.8‐0.9) for AD, DLB/PD and PSP, moderate (AUC = 0.7‐0.8) for FTD, poor (AUC = 0.51‐0.7) for CBD and bad/no discrimination capacity (AUC = 0.5) for AGD. Based on these findings, an increase of sensitivity of clinical diagnoses may be key to improve correct identification of neurodegenerative diseases. This may be possible through development and clinical implementation of molecular biomarkers that are able to indicate the causal proteinopathies of neurodegenerative diseases. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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