Evidence map›Paper›PMID 31386280›Full record

ArticleClinical and translational science2020

Development of an Integrated Platform Using Multidisciplinary Real-World Data to Facilitate Biomarker Discovery for Medical Products.

Stefan Dabic, Yasameen Azarbaijani, Tigran Karapetyan, Nilsa Loyo-Berrios, Vahan Simonyan, Terrie Kitchner, Murray Brilliant, Yelizaveta Torosyan

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

Article in Clinical and translational science, 2020. 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
0.4field-weighted citation impact, top 33% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Review
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

8 authors at 2 institutions in 1 country.

Stefan DabicCenter for Devices and Radiological Health, US Food and Drug Administration (CDRH/FDA), Silver Spring, Maryland, USA.
Yasameen AzarbaijaniCenter for Devices and Radiological Health, US Food and Drug Administration (CDRH/FDA), Silver Spring, Maryland, USA.
Tigran KarapetyanCenter for Devices and Radiological Health, US Food and Drug Administration (CDRH/FDA), Silver Spring, Maryland, USA.ORCID 0000-0001-9911-5315
Nilsa Loyo-BerriosCenter for Devices and Radiological Health, US Food and Drug Administration (CDRH/FDA), Silver Spring, Maryland, USA.
Vahan SimonyanHigh-Performance Integrated Virtual Environment (HIVE), US Food and Drug Administration (FDA), Silver Spring, Maryland, USA.
Terrie KitchnerCenter for Human Genetics, Marshfield Clinic Research Institute (MCRI), Marshfield, Wisconsin, USA.
Murray BrilliantCenter for Human Genetics, Marshfield Clinic Research Institute (MCRI), Marshfield, Wisconsin, USA.
Yelizaveta TorosyanCenter for Devices and Radiological Health, US Food and Drug Administration (CDRH/FDA), Silver Spring, Maryland, USA.ORCID 0000-0002-2565-3118
United States Food and Drug Administration · USMarshfield Clinic · US

Funding

University of Wisconsin Institute for Clinical and Translational ResearchUL1TR002373 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI ELIZABETH S BURNSIDE, Allan R. Brasier · 2017 to 2026
$75.9M
Institutional Clinical and Translational Science AwardUL1TR000427 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI DREZNER, MARC KENNETH · 2012 to 2016
$32.2M
The Electronic Medical Records and Genomics (eMERGE) Network Phase III Coordinating Center (U01)U01HG008701 · NHGRI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI PETERSON, JOSEPH F. · 2015 to 2019
$7.1M
NCATS NIH HHS UL1 TR000427NCATS NIH HHS UL1 TR002373NHGRI NIH HHS U01 HG008701
6 · The paper itself

Abstract

Translational multidisciplinary research is important for the Center for Devices and Radiological Health's efforts for utilizing real-world data (RWD) to enhance predictive evaluation of medical device performance in patient subpopulations. As part of our efforts for developing new RWD-based evidentiary approaches, including in silico discovery of device-related risk predictors and biomarkers, this study aims to characterize the sex/race-related trends in hip replacement outcomes and identify corresponding candidate single nucleotide polymorphisms (SNPs). Adverse outcomes were assessed by deriving RWD from a retrospective analysis of hip replacement hospital discharge data from the National Inpatient Sample (NIS). Candidate SNPs were explored using pre-existing data from the Personalized Medicine Research Project (PMRP). High-Performance Integrated Virtual Environment was used for analyzing and visualizing putative associations between SNPs and adverse outcomes. Ingenuity Pathway Analysis (IPA) was used for exploring plausibility of the sex-related candidate SNPs and characterizing gene networks associated with the variants of interest. The NIS-based epidemiologic evidence showed that periprosthetic osteolysis (PO) was most prevalent among white men. The PMRP-based genetic evidence associated the PO-related male predominance with rs7121 (odds ratio = 4.89; 95% confidence interval = 1.41-17.05) and other candidate SNPs. SNP-based IPA analysis of the expected gene expression alterations and corresponding signaling pathways suggested possible role of sex-related metabolic factors in development of PO, which was substantiated by ad hoc epidemiologic analysis identifying the sex-related differences in metabolic comorbidities in men vs. women with hip replacement-related PO. Thus, our in silico study illustrates RWD-based evidentiary approaches that may facilitate cost/time-efficient discovery of biomarkers for informing use of medical products.

Indexed as

Prosthesis FailureArthroplasty, Replacement, HipBiomarkersComorbidityComputer SimulationCost-Benefit AnalysisFeasibility StudiesFemaleGenetic Predisposition to DiseaseHip ProsthesisHumansMaleOsteolysisPolymorphism, Single NucleotidePrevalenceRisk AssessmentBiomarkers

Identifiers

PMID31386280
PMCPMC6951466
OpenAlexW2966592944

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.