Evidence map›Paper›PMID 41403033›Full record

ReviewExpert review of neurotherapeutics2026

Speech and language outcome measures in clinical trials of Alzheimer's and Parkinson's diseases.

Marcelo L Berthier, Alejandro Sosa-Welford, Juan Rafael Orozco-Arroyave, Diana López-Barroso, María José Torres-Prioris, Guadalupe Dávila, Adolfo M García

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Expert review of neurotherapeutics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. The include network: Advancing cross-linguistic equity in brain health research.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Marcelo L BerthierCognitive Neuroscience and Aphasia Unit, Faculty of Psychology and Speech Therapy, University of Málaga, Málaga, Spain.
Alejandro Sosa-WelfordCognitive Neuroscience Center, Universidad de San Andrés, Victoria, Argentina.
Juan Rafael Orozco-ArroyaveGITA Lab, Faculty of Engineering, University of Antioquia, Medellín, Colombia.
Diana López-BarrosoCognitive Neuroscience and Aphasia Unit, Faculty of Psychology and Speech Therapy, University of Málaga, Málaga, Spain.
María José Torres-PriorisCognitive Neuroscience and Aphasia Unit, Faculty of Psychology and Speech Therapy, University of Málaga, Málaga, Spain.
Guadalupe DávilaCognitive Neuroscience and Aphasia Unit, Faculty of Psychology and Speech Therapy, University of Málaga, Málaga, Spain.
Adolfo M GarcíaCognitive Neuroscience Center, Universidad de San Andrés, Victoria, Argentina.

Funding

An automated machine learning approach to language changes in Alzheimer’s disease and frontotemporal dementia across Latino and English-speaking populationsR01AG075775 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MARIA LUISA GORNO TEMPINI, Adolfo Martin Garcia · 2023 to 2026
$7.2M
NIA NIH HHS R01 AG075775
6 · The paper itself

Abstract

introductionAlongside core diagnostic symptoms, Alzheimer's disease (AD) and Parkinson's disease (PD) involve early and pervasive speech-language impairments (SLI), often appearing in preclinical stages and capturing disease severity. However, speech language outcome measures are under-represented in clinical trials, missing out on critical clinical outcome assessments (COAs). AREAS COVERED: The purpose of this review is to survey the findings from classical (analogical) and novel (digital) speech-language measures as pathways toward more precise diagnosis and response to treatment indices in interventional clinical trials. This narrative review covers two main areas; first, it examines the strengths and limitations of SL measures in traditional cognitive testing scales to identify adequate COAs for AD and PD. Second, it overviews findings on classical and digital COAs that hold great promise despite their widespread absence in clinical trials. EXPERT OPINION: Incorporating strategic SL COAs in clinical trials may identify early, severity-sensitive deficits and enhance the clinical insights thus obtained. The modification of clinical trial designs will nevertheless be required to increase sensitivity to identify meaningful clinical outcomes.

Indexed as

Alzheimer DiseaseLanguage DisordersOutcome Assessment, Health CareParkinson DiseaseClinical Trials as TopicHumansAlzheimer’s diseaseclassical testing methodsclinical outcome assessmentscognitive testingdigital testing methodsParkinson’s diseasespeech-language testing

Identifiers

PMID41403033
PMCPMC13072438

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.