Evidence map›Paper›PMID 32920624›Full record

ArticleThe journal of prevention of Alzheimer's disease2020

TRC-PAD: Accelerating Recruitment of AD Clinical Trials through Innovative Information Technology.

G A Jimenez-Maggiora, S Bruschi, R Raman, O Langford, M Donohue, M S Rafii, R A Sperling, J L Cummings, P S Aisen

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The journal of prevention of Alzheimer's disease, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 2 pooled it
2.0field-weighted citation impact, top 13% 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.

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

14 citing papers in PubMed, 2 syntheses or guidelines pooled it, 19 citations in OpenAlex.

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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

9 authors at 3 institutions in 1 country.

G A Jimenez-MaggioraGA Jimenez-Maggiora, Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, USA, gustavoj@usc.edu.
S Bruschi
R Raman
O Langford
M Donohue
M S Rafii
R A Sperling
J L Cummings
P S Aisen
University of Southern California · USBrigham and Women's Hospital · USCleveland Clinic · US

Funding

Trial-Ready Cohort for Preclinical/Prodromal Alzheimer's DiseaseR01AG053798 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI AISEN, PAUL S., CUMMINGS, JEFFREY L. · 2017 to 2022
$39.4M
Renewal of Centers of Biomedical Research Excellence (COBRE) (Phase 2) CNTN - ResubmissionP20GM109025 · NIGMS · CLEVELAND CLINIC FOUNDATION · PI JESSICA KIRKLAND CALDWELL · 2015 to 2026
$22.8M
Chronic Traumatic Encephalopathy: Detection, Diagnosis, Course, and Risk FactorsU01NS093334 · NINDS · BOSTON UNIVERSITY MEDICAL CAMPUS · PI CUMMINGS, JEFFREY L., REIMAN, ERIC MICHAEL · 2016 to 2022
$17.0M
NVEDARC Clinical CoreP20AG068053 · NIA · CLEVELAND CLINIC FOUNDATION · PI FOX, ROBERT J. · 2020 to 2022
$3.3M
Mentoring Imaging Research in Early ADK24AG035007 · NIA · BRIGHAM AND WOMEN'S HOSPITAL · PI SPERLING, REISA A. · 2010 to 2020
$1.4M
NIA NIH HHS K24 AG035007NIA NIH HHS P20 AG068053NIA NIH HHS R01 AG053798NIGMS NIH HHS P20 GM109025NINDS NIH HHS U01 NS093334
6 · The paper itself

Abstract

backgroundThe Trial-Ready Cohort for Preclinical/Prodromal Alzheimer's Disease (TRC-PAD) Informatics Platform (TRC-PAD IP) was developed to facilitate the efficient selection, recruitment, and assessment of study participants in support of the TRC-PAD program.

objectivesDescribe the innovative architecture, workflows, and components of the TRC-PAD IP.

designThe TRC-PAD IP was conceived as a secure, scalable, multi-tiered information management platform designed to facilitate high-throughput, cost-effective selection, recruitment, and assessment of TRC-PAD study participants and to develop a learning algorithm to select amyloid-bearing participants to participate in trials of early-stage Alzheimer's disease.

settingTRC-PAD participants were evaluated using both web-based and in-person assessments to predict their risk of amyloid biomarker abnormalities and eligibility for preclinical and prodromal clinical trials. Participant data were integrated across multiple stages to inform the prediction of amyloid biomarker elevation.

participantsTRC-PAD participants were age 50 and above, with an interest in participating in Alzheimer's research. MEASUREMENTS: TRC-PAD participants' cognitive performance and subjective memory concerns were remotely assessed on a longitudinal basis to predict participant risk of biomarker abnormalities. Those participants determined to be at the highest risk were invited to an in-clinic screening visit for a full battery of clinical and cognitive assessments and amyloid biomarker confirmation using positron emission tomography (PET) or lumbar puncture (LP).

resultsThe TRC-PAD IP supported growth in recruitment, screening, and enrollment of TRC-PAD participants by leveraging a secure, scalable, cost-effective cloud-based information technology architecture.

conclusionsThe TRC-PAD program and its underlying information management infrastructure, TRC-PAD IP, have demonstrated feasibility concerning the program aims. The flexible and modular design of the TRC-PAD IP will accommodate the introduction of emerging diagnostic technologies.

Indexed as

Information TechnologyPatient SelectionAgedAlzheimer DiseaseClinical Trials as TopicFemaleHumansLongitudinal StudiesMaleMiddle AgedProdromal SymptomsRegistriesRisk AssessmentAlzheimer’sclinical trialsinformaticsrecruitment

Identifiers

PMID32920624
PMCPMC7769128
OpenAlexW3084792595

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.