Sum of boxes of the clinical dementia rating scale highly predicts conversion or reversion in predementia stages

Ray-Chang Tzeng; Yu-Wan Yang; Kai-Cheng Hsu; Hsin-Te Chang; Pai-Yi Chiu

doi:10.3389/fnagi.2022.1021792

Sum of boxes of the clinical dementia rating scale highly predicts conversion or reversion in predementia stages

Front Aging Neurosci. 2022 Sep 23:14:1021792. doi: 10.3389/fnagi.2022.1021792. eCollection 2022.

Authors

Ray-Chang Tzeng¹, Yu-Wan Yang², Kai-Cheng Hsu^{2

3

4}, Hsin-Te Chang⁵, Pai-Yi Chiu^{6

7}

Affiliations

¹ Department of Neurology, Tainan Municipal Hospital, Tainan, Taiwan.
² Department of Neurology, China Medical University Hospital, Taichung, Taiwan.
³ Department of Medicine, China Medical University, Taichung, Taiwan.
⁴ Artificial Intelligence Center for Medical Diagnosis, China Medical University Hospital, Taichung, Taiwan.
⁵ Department of Psychology, College of Science, Chung Yuan Christian University, Taoyuan City, Taiwan.
⁶ Department of Neurology, Show Chwan Memorial Hospital, Changhua, Taiwan.
⁷ Department of Applied Mathematics, Tunghai University, Taichung, Taiwan.

Abstract

Background: The clinical dementia rating (CDR) scale is commonly used to diagnose dementia due to Alzheimer's disease (AD). The sum of boxes of the CDR (CDR-SB) has recently been emphasized and applied to interventional trials for tracing the progression of cognitive impairment (CI) in the early stages of AD. We aimed to study the influence of baseline CDR-SB on disease progression to dementia or reversion to normal cognition (NC).

Materials and methods: The baseline CDR < 1 cohort registered from September 2015 to August 2020 with longitudinal follow-up in the History-based Artificial Intelligence Clinical Dementia Diagnostic System (HAICDDS) database was retrospectively analyzed for the rates of conversion to CDR ≥ 1. A Cox regression model was applied to study the influence of CDR-SB levels on progression, adjusting for age, education, sex, neuropsychological tests, neuropsychiatric symptoms, parkinsonism, and multiple vascular risk factors.

Results: A total of 1,827 participants were analyzed, including 1,258 (68.9%) non-converters, and 569 (31.1%) converters with mean follow-up of 2.1 (range 0.4-5.5) and 1.8 (range 0.3-5.0) years, respectively. Conversion rates increased with increasing CDR-SB scores. Compared to a CDR-SB score of 0, the hazard ratios (HR) for conversion to dementia were 1.51, 1.91, 2.58, 2.13, 3.46, 3.85, 3.19, 5.12, and 5.22 for CDR-SB scores of 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, and ≥4.5, respectively (all p < 0.05 except for CDR-SB score = 0.5). In addition, older age, lower education, lower cognitive performance, and a history of diabetes also increased conversion rates. Furthermore, reversions to NC were 12.5, 5.6, 0.9, and 0% for CDR-SB scores of 0.5, 1.0-2.0, 2.5-3.5 and ≥4.0, respectively (p < 0.001).

Conclusion: CDR-SB in predementia or very mild dementia (VMD) stages highly predicts progression to dementia or reversion to NC. Therefore, CDR-SB could be a good candidate for tracing the effectiveness of pharmacological and non-pharmacological interventions in populations without dementia.

Keywords: Alzheimer’s disease; history-based artificial intelligence clinical dementia diagnostic system; predementia; sum of boxes of the clinical dementia rating; the clinical dementia rating.