Abstract

Background: There are few available methods for qualitatively evaluating patients with primary progressive aphasia (PPA). Commonly adopted approaches are time-consuming, of limited accuracy, or designed to assess different patient populations. This paper introduces a new clinical test - the Mini Linguistic State Examination (MLSE) - which was designed uniquely to enable a clinician to assess and subclassify both classical and mixed presentations of PPA. The adoption of a novel assessment method (error classification) greatly amplifies the clinical information that can be derived from a set of standard linguistic tasks and allows a five-dimensional profile to be defined. Methods: Fifty-four patients and 30 matched controls were recruited. Five domains of language competence (motor speech, phonology, semantics, syntax, and working memory) were assessed using a sequence of 11 distinct linguistic assays. A random forest classification was used to assess the diagnostic accuracy for predicting PPA subtypes and create a decision tree as a guide to clinical classification. Findings: The random forest prediction model was 96% accurate overall (92% for logopenic variant, 93% for semantic variant, and 98% for non-fluent variant PPA). The derived decision tree produced a correct classification of 91% of participants whose data were not included in the training set. Interpretation: The MLSE is a new cognitive test incorporating a novel and powerful, yet straightforward, approach to scoring. Rigorous assessment of its diagnostic accuracy confirmed excellent matching of PPA syndromes to clinical gold standard diagnoses. Adoption of the MLSE by clinicians will have a decisive impact on the consistency and uniformity with which patients can be described clinically. It will also facilitate screening for cohort-based research, including future therapeutic trials, and is suitable for describing, quantifying and monitoring language deficits in other brain disorders. Funding Information: The research was funded by a Medical Research Council Research Grant award (Ref MR/N025881/1) to PG, MLR JR, KP and SC. Additional support was provided through grants from the MRC (UAG051 and G101400), Wellcome Trust (103838) and ERC (GAP: 670428), and through funding awarded to the National Institute for Health Research Cambridge Biomedical Research Centre and to the MRC CBU (MC_UU_00005/18). Declaration of Interests: JBR reports consultancy unrelated to the work with Biogen, UCB, Asceneuron and Althira; and receipt of research grants, unrelated to this work, from Janssen, AZ-Medimmune, and Lilly. The other authors declare no conflicts of interest. Ethics Approval Statement: Written informed consent was provided by all participants. The study protocol was reviewed and approved by the London (Chelsea) Research Ethics Committee [Ref. 16/LO/1735].

Highlights

  • By way of a preliminary study of the construct validity of the Mini Linguistic State Examinatiodn (MLSE), the present paper describes the test and reports the profiles obtained in a cohort of patients with predominantly mild progressive aphasia’ (PPA), recruited through specialist cognitive neurology services at three centres in the United Kingdom

  • This paper reports the motivation, assumptions, structure, and diagnostic properties of a clinical instrument that can be used for detection, diagnosis and classification of patients with the reproducible measure of language competence that is differentially sensitive to the classic PPA

  • Competence in the domains of motor speech, phonology, semantics, syntax and auditory verbal working memory, which are differentially impaired across the PPA variants,17–23 is quantified in the MLSE in terms of the numbers of errors deriving from each domain that a patient makes during a sequence of eleven simple linguistic assays

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Summary

Introduction

Correspondence to: Professor Peter Garrard, Molecular and Clinical Sciences Research Institute, St George’s, University of London, Cranmer Terrace, London SW17 ORE. There are few available methods for qualitatively evaluating patients with primary progressive aphasia. Adopted approaches are time-consuming, of limited accuracy, or designed to assess different patient populations. Linguistic State Examination - which was designed uniquely to enable a clinician to assess and subclassify both classical and mixed presentations of primary progressive aphasia. The adoption of a novel assessment method (error classification) greatly amplifies the clinical information that can be derived from a set of standard linguistic tasks and allows a five-dimensional profile to be defined. Five domains of language competence (motor speech, phonology, semantics, syntax, and working memory) were assessed using a sequence of 11 distinct linguistic assays. A random forest classification was used to assess the diagnostic accuracy for predicting primary progressive aphasia subtypes and create a decision tree as a guide to clinical classification

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