Evidence map›Paper›PMID 37542312›Full record

ArticleBMC medical informatics and decision making2023

An ontology-based approach for harmonization and cross-cohort query of Alzheimer's disease data resources.

Xubing Hao, Xiaojin Li, Guo-Qiang Zhang, Cui Tao, Paul E Schulz, Alzheimer’s Disease Neuroimaging Initiative, Licong Cui

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PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medical informatics and decision making, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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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

7 authors.

Xubing Hao *McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Xiaojin Li *Department of Neurology, McGovern School of Medicine, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Guo-Qiang ZhangMcWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Cui TaoMcWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Paul E SchulzDepartment of Neurology, McGovern School of Medicine, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Alzheimer’s Disease Neuroimaging Initiative
Licong CuiMcWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA. licong.cui@uth.tmc.edu.ORCID http://orcid.org/0000-0001-5549-8780

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
NATIONAL ALZHEIMERS COORDINATING CENTER (NACC)U01AG016976 · NIA · UNIVERSITY OF WASHINGTON · PI KUKULL, WALTER ANTHONY · 1999 to 2020
$72.8M
THERAPEUTIC EFFECTS OF INTRA-NASAL INSULIN DETEMIRP50AG005136 · NIA · UNIVERSITY OF WASHINGTON · PI GRABOWSKI, THOMAS J. · 1985 to 2019
$57.2M
VIRUS-INDUCED BRAIN PATHOLOGYP50AG005131 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BREWER, JAMES B · 1985 to 2018
$55.4M
WASHINGTON UNIVERSITY ALZHEIMERS DISEASE RESEARCH CENTERP50AG005681 · NIA · WASHINGTON UNIVERSITY · PI FAGAN, ANNE · 1985 to 2019
$52.1M
SUPPLEMENT TO RUSH ALZHEIMERS DISEASE CENTER COREP30AG010161 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI LEURGANS, SUE E. · 1991 to 2020
$49.1M
Satellite Diagnostic and Treatment Clinic CoreP50AG008702 · NIA · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI DE JAGER, PHILIP L · 1989 to 2019
$46.3M
TREATMENT OF DEPRESSION IN ALZHEIMER'S DISEASEP50AG005133 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI KAMBOH, M. ILYAS · 1985 to 2019
$43.0M
THE ROLE OF ADVANCED CAA IN ALZHEIMER'S DEMENTIAP50AG005134 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI HYMAN, BRADLEY T. · 1985 to 2018
$42.1M
VASCULAR RISK AND COGNITIVE STATUS IN A LATINO POPULATIONP50AG005142 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI BRASKIE, MEREDITH NICOLE · 1985 to 2019
$41.0M
VESICULAR LOCALIZATION AND FUNCTION OF PRESENILIN 1 FRAGMENTP50AG005138 · NIA · MOUNT SINAI SCHOOL OF MEDICINE OF NYU · PI GROSSMAN, HILLEL · 1985 to 2019
$37.9M
'T V ASSESSMENT - MEMORY DISORDERED PATIENTS'P50AG005146 · NIA · JOHNS HOPKINS UNIVERSITY · PI ALBERT, MARILYN S. · 1985 to 2019
$37.6M
NIA NIH HHS P30 AG008017NIA NIH HHS P30 AG008051NIA NIH HHS P30 AG010124NIA NIH HHS P30 AG010129NIA NIH HHS P30 AG010133NIA NIH HHS P30 AG010161NIA NIH HHS P30 AG012300NIA NIH HHS P30 AG013846NIA NIH HHS P30 AG013854NIA NIH HHS P30 AG019610NIA NIH HHS P30 AG028383NIA NIH HHS P30 AG035982NIA NIH HHS P30 AG049638NIA NIH HHS P30 AG053760NIA NIH HHS P50 AG005131NIA NIH HHS P50 AG005133NIA NIH HHS P50 AG005134NIA NIH HHS P50 AG005136NIA NIH HHS P50 AG005138NIA NIH HHS P50 AG005142NIA NIH HHS P50 AG005146NIA NIH HHS P50 AG005681NIA NIH HHS P50 AG008702NIA NIH HHS P50 AG016573NIA NIH HHS P50 AG016574NIA NIH HHS P50 AG023501NIA NIH HHS P50 AG025688NIA NIH HHS P50 AG033514NIA NIH HHS P50 AG047266NIA NIH HHS P50 AG047270NIA NIH HHS P50 AG047366NIA NIH HHS R01 AG072799NIA NIH HHS R21 AG068994NIA NIH HHS RF1 AG072799NIA NIH HHS U01 AG016976NIA NIH HHS U01 AG024904NIH HHS RF1AG072799NINDS NIH HHS R01 NS116287NINDS NIH HHS R01 NS126690NLM NIH HHS R01 LM013335
6 · The paper itself

Abstract

backgroundIn the United States, the National Alzheimer's Coordinating Center (NACC) and the Alzheimer's Disease Neuroimaging Initiative (ADNI) are two major data sharing resources for Alzheimer's Disease (AD) research. NACC and ADNI strive to make their data more FAIR (findable, interoperable, accessible and reusable) for the broader research community. However, there is limited work harmonizing and supporting cross-cohort interoperability of the two resources.

methodIn this paper, we leverage an ontology-based approach to harmonize data elements in the two resources and develop a web-based query system to search patient cohorts across the two resources. We first mapped data elements across NACC and ADNI, and performed value harmonization for the mapped data elements with inconsistent permissible values. Then we built an Alzheimer's Disease Data Element Ontology (ADEO) to model the mapped data elements in NACC and ADNI. We further developed a prototype cross-cohort query system to search patient cohorts across NACC and ADNI.

resultsAfter manual review, we found 172 mappings between NACC and ADNI. These 172 mappings were further used to construct common concepts in ADEO. Our data element mapping and harmonization resulted in five files storing common concepts, variables in NACC and ADNI, mappings between variables and common concepts, permissible values of categorical type data elements, and coding inconsistency harmonization, respectively. Our cross-cohort query system consists of three core architectural elements: a web-based interface, an advanced query engine, and a backend MongoDB database.

conclusionsIn this work, ADEO has been specifically designed to facilitate data harmonization and cross-cohort query of NACC and ADNI data resources. Although our prototype cross-cohort query system was developed for exploring NACC and ADNI, its backend and frontend framework has been designed and implemented to be generally applicable to other domains for querying patient cohorts from multiple heterogeneous data sources.

Indexed as

Alzheimer DiseaseHumansNeuroimagingUnited StatesAlzheimer’s diseaseCross-cohort queryData element mappingData harmonizationOntology

Identifiers

PMID37542312
PMCPMC10401730

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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.