添加 MRI 和 CSF 生物标志物是否可以提高基于认知表现问卷的认知状态分类？
Does adding MRI and CSF-based biomarkers improve cognitive status classification based on cognitive performance questionnaires?
机构信息
School of Gerontology, University of Southern California, Los Angeles, California, United States of America.
Human Development and Family Sciences, University of Texas at Austin, Austin, Texas, United States of America.
出版信息
PLoS One. 2023 May 8;18(5):e0285220. doi: 10.1371/journal.pone.0285220. eCollection 2023.
BACKGROUND
Cognitive status classification (e.g. dementia, cognitive impairment without dementia, and normal) based on cognitive performance questionnaires has been widely used in population-based studies, providing insight into the population dynamics of dementia. However, researchers have raised concerns about the accuracy of cognitive assessments. MRI and CSF biomarkers may provide improved classification, but the potential improvement in classification in population-based studies is relatively unknown.
METHODS
Data come from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We examined whether the addition of MRI and CSF biomarkers improved cognitive status classification based on cognitive status questionnaires (MMSE). We estimated several multinomial logistic regression models with different combinations of MMSE and CSF/MRI biomarkers. Based on these models, we also predicted prevalence of each cognitive status category using a model with MMSE only and a model with MMSE + MRI + CSF measures and compared them to diagnosed prevalence.
RESULTS
Our analysis showed a slight improvement in variance explained (pseudo-R2) between the model with MMSE only and the model including MMSE and MRI/CSF biomarkers; the pseudo-R2 increased from .401 to .445. Additionally, in evaluating differences in predicted prevalence for each cognitive status, we found a small improvement in the predicted prevalence of cognitively normal individuals between the MMSE only model and the model with MMSE and CSF/MRI biomarkers (3.1% improvement). We found no improvement in the correct prediction of dementia prevalence.
CONCLUSION
MRI and CSF biomarkers, while important for understanding dementia pathology in clinical research, were not found to substantially improve cognitive status classification based on cognitive status performance, which may limit adoption in population-based surveys due to costs, training, and invasiveness associated with their collection.
背景
基于认知表现问卷的认知状态分类（例如痴呆、无痴呆认知障碍和正常）已广泛应用于基于人群的研究，为痴呆的人群动态提供了深入了解。然而，研究人员对认知评估的准确性提出了担忧。MRI 和 CSF 生物标志物可能提供更好的分类，但基于人群的研究中分类的潜在改善相对未知。
方法
数据来自阿尔茨海默病神经影像学倡议（ADNI）。我们检查了 MRI 和 CSF 生物标志物的加入是否改善了基于认知状态问卷（MMSE）的认知状态分类。我们估计了几个包含 MMSE 和 CSF/MRI 生物标志物的不同组合的多项逻辑回归模型。基于这些模型，我们还使用仅包含 MMSE 的模型和包含 MMSE + MRI + CSF 测量值的模型预测了每个认知状态类别的患病率，并将它们与诊断患病率进行了比较。
结果
我们的分析表明，仅包含 MMSE 的模型和包含 MMSE 和 MRI/CSF 生物标志物的模型之间的方差解释（伪 R2）略有提高；伪 R2 从.401 增加到.445。此外，在评估每个认知状态的预测患病率差异时，我们发现仅包含 MMSE 的模型和包含 MMSE 和 CSF/MRI 生物标志物的模型之间认知正常个体的预测患病率有微小提高（提高了 3.1%）。我们发现痴呆患病率的正确预测没有改善。
结论
虽然 MRI 和 CSF 生物标志物对于理解临床研究中的痴呆病理学很重要，但它们并没有显著改善基于认知表现的认知状态分类，这可能会由于其采集相关的成本、培训和侵入性而限制在基于人群的调查中采用。
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