Evidence map›Paper›PMID 35947423›Full record

ArticleJMIR research protocols2022

Description of the Method for Evaluating Digital Endpoints in Alzheimer Disease Study: Protocol for an Exploratory, Cross-sectional Study.

Jelena Curcic, Vanessa Vallejo, Jennifer Sorinas, Oleksandr Sverdlov, Jens Praestgaard, Mateusz Piksa, Mark Deurinck, Gul Erdemli, Maximilian Bügler, Ioannis Tarnanas and 18 more

2 registry-linked trialsOpen access · goldAbstract read
In one paragraph

Article in JMIR research protocols, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 20% of its field
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.

NCT05524415 withdrawnnot on this mapstarted 2023, after this paper: background citation

Evaluation of Neurosteer System (Quantitative EEG Features) in Stroke Patients Suffering From Disorders of Consciousness

TypeobservationalSponsorNeurosteer Ltd.Ran2023 to 2023Enrolled0ConditionsAcute StrokeArmsNeurosteer EEG recorder
NCT05528445 completednot on this map

Evaluation of Cognitive State in Seniors Using Neurosteer Single-channel EEG With an Auditory Assessment Tool

TypeobservationalSponsorNeurosteer Ltd.Ran2022 to 2023Enrolled77ConditionsCognitive DeclineArmsNeurosteer EEG recorder
3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. 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

28 authors at 12 institutions in 6 countries.

Jelena CurcicNovartis Institutes for Biomedical Research, Basel, Switzerland.ORCID https://orcid.org/0000-0001-9647-5972
Vanessa VallejoNovartis Institutes for Biomedical Research, Basel, Switzerland.ORCID https://orcid.org/0000-0001-9117-8186
Jennifer SorinasNovartis Institutes for Biomedical Research, Basel, Switzerland.ORCID https://orcid.org/0000-0002-8726-4847
Oleksandr SverdlovNovartis Pharmaceuticals Corporation, East Hanover, NJ, United States.ORCID https://orcid.org/0000-0002-1626-2588
Jens PraestgaardNovartis Institutes for Biomedical Research, Cambridge, MA, United States.ORCID https://orcid.org/0000-0001-5122-7190
Mateusz PiksaNovartis Institutes for Biomedical Research, Basel, Switzerland.ORCID https://orcid.org/0000-0002-7221-6770
Mark DeurinckNovartis Institutes for Biomedical Research, Basel, Switzerland.ORCID https://orcid.org/0000-0002-8842-0944
Gul ErdemliNovartis Institutes for Biomedical Research, Cambridge, MA, United States.ORCID https://orcid.org/0000-0003-4677-2914
Maximilian BüglerAltoida Inc, Washington, DC, United States.ORCID https://orcid.org/0000-0002-2591-017X
Ioannis TarnanasAltoida Inc, Washington, DC, United States.ORCID https://orcid.org/0000-0003-4069-6551
Nick TaptiklisCambridge Cognition Ltd, Cambridge, United Kingdom.ORCID https://orcid.org/0000-0003-0194-9413
Francesca CormackCambridge Cognition Ltd, Cambridge, United Kingdom.ORCID https://orcid.org/0000-0002-4413-177X
Rebekka AnkerMindMaze SA, Lausanne, Switzerland.ORCID https://orcid.org/0000-0001-9768-4784
Fabien MasséMindMaze SA, Lausanne, Switzerland.ORCID https://orcid.org/0000-0002-7447-5119
William Souillard-MandarLinus Health, Boston, MA, United States.ORCID https://orcid.org/0000-0002-7441-8229
Nathan IntratorNeurosteer Inc, New York, NY, United States.ORCID https://orcid.org/0000-0002-5635-9835
Lior MolchoNeurosteer Inc, New York, NY, United States.ORCID https://orcid.org/0000-0001-9707-9066
Erica MaderoNeurotrack Technologies Inc, Redwood City, CA, United States.ORCID https://orcid.org/0000-0002-5112-2441
Nicholas BottDepartment of Medicine, School of Medicine, Stanford University, Stanford, CA, United States.ORCID https://orcid.org/0000-0001-5709-4261
Mieko ChambersNeurovision Imaging Inc, Sacramento, CA, United States.ORCID https://orcid.org/0000-0002-7315-5244
Josef TamoryNeurovision Imaging Inc, Sacramento, CA, United States.ORCID https://orcid.org/0000-0003-3792-8892
Matias ShulzViewMind Inc, New York, NY, United States.ORCID https://orcid.org/0000-0003-2355-5802
Gerardo FernandezViewMind Inc, New York, NY, United States.ORCID https://orcid.org/0000-0002-6081-6437
William SimpsonWinterlight Labs, Toronto, ON, Canada.ORCID https://orcid.org/0000-0003-1671-5660
Jessica RobinWinterlight Labs, Toronto, ON, Canada.ORCID https://orcid.org/0000-0003-4153-2655
Jón G SnædalMemory Clinic, Landspitali, Reykjavik, Iceland.ORCID https://orcid.org/0000-0002-1351-1104
Jang-Ho ChaNovartis Institutes for Biomedical Research, Cambridge, MA, United States.ORCID https://orcid.org/0000-0002-0458-3931
Kristin HannesdottirNovartis Institutes for Biomedical Research, Cambridge, MA, United States.ORCID https://orcid.org/0000-0003-4496-0110
Novartis (Switzerland) · CHNovartis (United States) · USCambridge Cognition (United Kingdom) · GBFaculty of 1000 (United States) · USGemini Computers (United States) · USStereoVision Imaging (United States) · USMassachusetts Institute of Technology · USNational University Hospital of Iceland · ISNeurotrack Technologies (United States) · USStanford University · USTrinity College Dublin · IEUniversidade para o Desenvolvimento do Alto Vale do Itajaí · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMore sensitive and less burdensome efficacy end points are urgently needed to improve the effectiveness of clinical drug development for Alzheimer disease (AD). Although conventional end points lack sensitivity, digital technologies hold promise for amplifying the detection of treatment signals and capturing cognitive anomalies at earlier disease stages. Using digital technologies and combining several test modalities allow for the collection of richer information about cognitive and functional status, which is not ascertainable via conventional paper-and-pencil tests.

objectiveThis study aimed to assess the psychometric properties, operational feasibility, and patient acceptance of 10 promising technologies that are to be used as efficacy end points to measure cognition in future clinical drug trials.

methodsThe Method for Evaluating Digital Endpoints in Alzheimer Disease study is an exploratory, cross-sectional, noninterventional study that will evaluate 10 digital technologies' ability to accurately classify participants into 4 cohorts according to the severity of cognitive impairment and dementia. Moreover, this study will assess the psychometric properties of each of the tested digital technologies, including the acceptable range to assess ceiling and floor effects, concurrent validity to correlate digital outcome measures to traditional paper-and-pencil tests in AD, reliability to compare test and retest, and responsiveness to evaluate the sensitivity to change in a mild cognitive challenge model. This study included 50 eligible male and female participants (aged between 60 and 80 years), of whom 13 (26%) were amyloid-negative, cognitively healthy participants (controls); 12 (24%) were amyloid-positive, cognitively healthy participants (presymptomatic); 13 (26%) had mild cognitive impairment (predementia); and 12 (24%) had mild AD (mild dementia). This study involved 4 in-clinic visits. During the initial visit, all participants completed all conventional paper-and-pencil assessments. During the following 3 visits, the participants underwent a series of novel digital assessments.

resultsParticipant recruitment and data collection began in June 2020 and continued until June 2021. Hence, the data collection occurred during the COVID-19 pandemic (SARS-CoV-2 virus pandemic). Data were successfully collected from all digital technologies to evaluate statistical and operational performance and patient acceptance. This paper reports the baseline demographics and characteristics of the population studied as well as the study's progress during the pandemic.

conclusionsThis study was designed to generate feasibility insights and validation data to help advance novel digital technologies in clinical drug development. The learnings from this study will help guide future methods for assessing novel digital technologies and inform clinical drug trials in early AD, aiming to enhance clinical end point strategies with digital technologies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/35442.

Indexed as

Alzheimer diseasebrain amyloidclinical trial designcognitiondigital endpointsmethodology studymobile phone

Identifiers

PMID35947423
PMCPMC9403829
OpenAlexW4285324269

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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 Socratic graph.