Medical Research Council (MRC) Biostatistics, University of Cambridge, Cambridge, United Kingdom.
PLoS Med. 2009 Nov;6(11):e1000180. doi: 10.1371/journal.pmed.1000180. Epub 2009 Nov 10.
Dementia drug development aims to modulate pathological processes that cause clinical syndromes. Population data (epidemiological neuropathology) will help to model and predict the potential impact of such therapies on dementia burden in older people. Presently this can only be explored through post mortem findings. We report the attributable risks (ARs) for dementia at death for common age-related degenerative and vascular pathologies, and other factors, in the MRC Cognitive Function and Ageing Study (MRC CFAS).
A multicentre, prospective, longitudinal study of older people in the UK was linked to a brain donation programme. Neuropathology of 456 consecutive brain donations assessed degenerative and vascular pathologies. Logistic regression modelling, with bootstrapping and sensitivity analyses, was used to estimate AR at death for dementia for specific pathologies and other factors. The main contributors to AR at death for dementia in MRC CFAS were age (18%), small brain (12%), neocortical neuritic plaques (8%) and neurofibrillary tangles (11%), small vessel disease (12%), multiple vascular pathologies (9%), and hippocampal atrophy (10%). Other significant factors include cerebral amyloid angiopathy (7%) and Lewy bodies (3%).
Such AR estimates cannot be derived from the living population; rather they estimate the relative contribution of specific pathologies to dementia at death. We found that multiple pathologies determine the overall burden of dementia. The impact of therapy targeted to a specific pathology may be profound when the dementia is relatively "pure," but may be less impressive for the majority with mixed disease, and in terms of the population. These data justify a range of strategies, and combination therapies, to combat the degenerative and vascular determinants of cognitive decline and dementia. Please see later in the article for the Editors' Summary.
痴呆症药物研发旨在调节导致临床综合征的病理过程。人群数据（流行病学神经病理学）将有助于对这些疗法对老年人痴呆症负担的潜在影响进行建模和预测。目前，这只能通过死后发现来探索。我们报告了在 MRC 认知功能与衰老研究（MRC CFAS）中，常见的与年龄相关的退行性和血管病理学以及其他因素导致痴呆症死亡的归因风险（AR）。
一项针对英国老年人的多中心、前瞻性、纵向研究与大脑捐赠计划相关联。对 456 例连续大脑捐赠的神经病理学进行了评估，以评估退行性和血管病理学。使用逻辑回归模型（带有自举和敏感性分析）来估计特定病理学和其他因素导致痴呆症死亡的 AR。MRC CFAS 中导致痴呆症死亡的 AR 的主要贡献者是年龄（18%）、脑小（12%）、皮质神经突斑块（8%）和神经纤维缠结（11%）、小血管疾病（12%）、多种血管病理学（9%）和海马萎缩（10%）。其他重要因素包括脑血管淀粉样变性（7%）和路易体（3%）。
这些 AR 估计不能从存活人群中得出；相反，它们估计了特定病理学对死亡时痴呆症的相对贡献。我们发现，多种病理学决定了痴呆症的总体负担。当痴呆症相对“单纯”时，针对特定病理学的治疗可能会产生深远的影响，但对于大多数患有混合性疾病的患者以及人群而言，影响可能不那么明显。这些数据证明了一系列策略和联合治疗的合理性，以对抗认知能力下降和痴呆症的退行性和血管决定因素。请在文章稍后查看编辑摘要。
