Refining the Diagnostic Accuracy of Parkinsonian Disorders using Metaphenomic Annotation of the Clinicopathological Literature
Refining the Diagnostic Accuracy of Parkinsonian Disorders using Metaphenomic Annotation of the Clinicopathological Literature
复制标题
使用临床病理文献的元表型注释提高帕金森病的诊断准确性
DOI：
10.1101/2023.12.12.23299891
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Massey Q
中科院分区：
文献类型：
--
作者：
Massey Q
背景帕金森病的诊断精度不够准确。即使在专家诊所，也有多达五分之一的诊断是错误的。这导致了具有混合病理学的队列，影响了我们理解疾病异质性的能力，并对临床试验提出了重大挑战。金标准诊断是对潜在蛋白质病的死后确认，然而许多临床病理学研究侧重于单一疾病或一个时间方向的框架分析（即生前诊断与死后诊断，反之亦然）。鉴于帕金森病 (PD)、多系统萎缩 (MSA)、进行性核上性凝视麻痹 (PSP)、路易体痴呆 (DLB) 和皮质基底节变性 (CBD) 都可以相互模仿，这些可能会低估误诊和漏诊。方法目的是全面绘制帕金森病的误诊和漏诊情况，并利用表型特征来开发一种概率模型根据临床观察细化诊断可能性。自 1992 年以来，我们识别了 125 个已发表的临床病理学队列和病例报告，提取了约 9200 个死后病例的表型信息，并以标准化的机器可读格式整理数据。结果 MSA 诊断准确性最高 (92·8%)，DLB 最低 (82·1%)。 MSA 和 PSP 在生活中最常被误诊为 PD（7·2% 和 8·3% 的病例），而最常见的 PD 误诊是阿尔茨海默病（约 7% 的病例）。 PD 诊断时 DLB 年龄较大，CBD 较年轻，生存期较长。临床注释变化很大，这代表了临床病理学文献的局限性，但是我们为一系列特征创建了似然比，并展示了如何通过这些特征来完善诊断。解释这项工作提供了一个统一的开源数据集，代表了 30 多年已发表的结果，并为更灵活的预测模型奠定了关键基础，该模型利用不同的信息源来更好地区分疾病早期和前驱阶段的帕金森病。资助医学研究委员会背景研究在此之前的证据研究帕金森病的诊断精度不够准确——根据临床病理学研究得出的估计误诊率在 10% 至 20% 之间变化，具体取决于病情、背景和标准。然而，之前的许多研究要么关注一种单一条件，要么在一个时间方向上进行分析。当帕金森病出现运动症状时，这种情况已经存在 10-20 年了。之前的工作提出了一种概率方法来识别前驱帕金森病，但对于一系列经常相互模仿的常见帕金森病，尚不存在这种方法。 这项研究的附加价值这项研究构建并标准化了所有主要帕金森综合征的 30 年临床病理学数据，使其以开放、机器可读的格式提供，并且还更新了帕金森综合征的人类表型本体论。它利用这些来全面绘制所有疾病的漏诊和误诊模式，并构建灵活的多模式概率方法来帮助完善这些疾病的诊断。所有可用证据的影响这项工作为模块化框架提供了关键基础，该框架可以灵活地调整并与不同的工具、技术和方法相结合，以便在疾病的早期和前驱阶段更准确地诊断不同的帕金森病。
BackgroundThe diagnostic precision of Parkinsonian disorders is not accurate enough. Even in expert clinics up to one in five diagnoses are incorrect. This leads to cohorts with mixed pathologies, impacting our ability to understand disease heterogeneity and posing a major challenge for clinical trials. Gold standard diagnosis is post-mortem confirmation of the underlying proteinopathy, however many clinicopathological studies focus on either a single disease or frame analyses in one temporal direction (i.e., in-life diagnosis vs post-mortem or vice versa). Given Parkinson’s Disease (PD), Multiple System Atrophy (MSA), Progressive Supranuclear Gaze Palsy (PSP), Dementia with Lewy Bodies (DLB) and Corticobasal degeneration (CBD) can all mimic one-another, these may underestimate mis- and missed diagnoses.MethodsThe objective was to comprehensively map the mis- and missed diagnoses across the Parkinsonian disorders and use phenotypic features to develop a probabilistic model to refine diagnostic likelihoods based on clinical observations. We identified 125 published clinicopathological cohorts and case-reports since 1992, extracted phenotype information for ∼9200 post-mortem cases, and curated the data in a standardized machine-readable format.FindingsMSA diagnostic accuracy was highest (92·8%) and DLB lowest (82·1%). MSA and PSP were most frequently mis-labelled as PD in life (7·2% and 8·3% of cases), where-as the most common PD misdiagnosis was Alzheimer’s (∼7% cases). DLB age at diagnosis was older, CBD younger, and survival longer in PD. Clinical annotation was extremely variable, which represents a limitation with clinicopathological literature, however we created likelihood ratios for a range of features and demonstrate how these can refine diagnoses.InterpretationThis work delivers a harmonized, open-source dataset representing over 30 years of published results and represents a key foundation for more flexible predictive models that leverage different sources of information to better discriminate Parkinsonian disorders during the early and prodromal phases of the illness.FundingMedical Research CouncilResearch in contextEvidence before this studyThe diagnostic precision of Parkinsonian disorders is not accurate enough – estimated misdiagnosis rates, derived from clinicopathological studies, vary between 10 – 20% depending on the condition, context and criteria. However, many previous studies either focus on one single condition, or frame the analysis in one temporal direction. By the time Parkinsonian disorders manifest with motor symptoms, the conditions have been present for 10-20y. Previous work has proposed a probabilistic approach to identify prodromal Parkinson’s disease, but none exist for the range of common Parkinsonian disorders that often mimic one another.Added value of this studyThis study structures and standardises 30-years of clinicopathological data across all the main Parkinsonian syndromes, making it available in an open, machine-readable format, and also updates the Human Phenotyping Ontology for Parkinsonian syndromes. It uses these to comprehensively map the patterns of missed and mis-diagnosis across all of the conditions, and build a flexible multimodal probabilistic approach to help refine diagnoses of these disorders.Implications of all the available evidenceThis work provides a key foundation for a modular framework that can be flexibly adapted and combined with different tools, techniques and approaches to more accurately diagnose different Parkinsonian disorders during the early and prodromal phases of the illness.
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影响因子：
4
作者：
E. Natera;J. Martínez;J. L. López;A. Gómez;A. Sánchez;M. López;A. Rábano;A. Alonso
通讯作者：
A. Alonso
影响因子：
14.5
作者：
Ling, Helen;O'Sullivan, Sean S.;Lees, Andrew J.
通讯作者：
Lees, Andrew J.
八旬帕金森症 - 临床病理学观察。
影响因子：
4.1
作者：
A. Rajput;Emma F. Rajput
通讯作者：
Emma F. Rajput
影响因子：
11
作者：
Ozawa, T.;Tada, M.;Nishizawa, M.
通讯作者：
Nishizawa, M.
影响因子：
14.5
作者：
Molano, Jennifer;Boeve, Bradley;Petersen, Ronald
通讯作者：
Petersen, Ronald