Evidence map›Paper›PMID 27416001›Full record

ArticleClinical pharmacology and therapeutics2016

Successful Comparison of US Food and Drug Administration Sentinel Analysis Tools to Traditional Approaches in Quantifying a Known Drug-Adverse Event Association.

J J Gagne, X Han, S Hennessy, C E Leonard, E A Chrischilles, R M Carnahan, S V Wang, C Fuller, A Iyer, H Katcoff and 5 more

Open access · greenAbstract readComparative Study
In one paragraph

Article in Clinical pharmacology and therapeutics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
5.5field-weighted citation impact, top 4% 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

16 citing papers in PubMed, 35 citations in OpenAlex.

  1. Article
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  5. Leveraging the Capabilities of the FDA's Sentinel System To Improve Kidney Care.Journal of the American Society of Nephrology : JASN · 2020
    Review
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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

15 authors at 6 institutions in 1 country.

J J GagneDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA. jgagne1@partners.org.
X HanCenter for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, and Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
S HennessyCenter for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, and Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
C E LeonardCenter for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, and Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
E A ChrischillesDepartment of Epidemiology, University of Iowa College of Public Health, Iowa City, Iowa, USA.
R M CarnahanDepartment of Epidemiology, University of Iowa College of Public Health, Iowa City, Iowa, USA.
S V WangDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
C FullerDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA.
A IyerDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA.
H KatcoffDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA.
T S WoodworthDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA.
P ArchdeaconOffice of Medical Policy, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, USA.
T E MeyerDivision of Epidemiology, Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, USA.
S SchneeweissDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
S TohDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA.
Harvard University · USHarvard Pilgrim Health Care · USUniversity of Pennsylvania · USCenter for Drug Evaluation and Research · USUniversity of Iowa · USBrigham and Women's Hospital · US

Funding

Methods for studying treatment heterogeneity using large observational databasesR00HS022193 · AHRQ · BRIGHAM AND WOMEN'S HOSPITAL · PI WANG, SHIRLEY · 2015 to 2017
$747k
AHRQ HHS R00 HS022193FDA HHS HHSF223200910006I
6 · The paper itself

Abstract

The US Food and Drug Administration's Sentinel system has developed the capability to conduct active safety surveillance of marketed medical products in a large network of electronic healthcare databases. We assessed the extent to which the newly developed, semiautomated Sentinel Propensity Score Matching (PSM) tool could produce the same results as a customized protocol-driven assessment, which found an adjusted hazard ratio (HR) of 3.04 (95% confidence interval [CI], 2.81-3.27) comparing angioedema in patients initiating angiotensin-converting enzyme (ACE) inhibitors vs. beta-blockers. Using data from 13 Data Partners between 1 January 2008, and 30 September 2013, the PSM tool identified 2,211,215 eligible ACE inhibitor and 1,673,682 eligible beta-blocker initiators. The tool produced an HR of 3.14 (95% CI, 2.86-3.44). This comparison provides initial evidence that Sentinel analytic tools can produce findings similar to those produced by a highly customized protocol-driven assessment.

Indexed as

Drug-Related Side Effects and Adverse ReactionsAdrenergic beta-AntagonistsAngioedemaAngiotensin-Converting Enzyme InhibitorsDatabases, FactualHumansModels, StatisticalProduct Surveillance, PostmarketingUnited StatesUnited States Food and Drug AdministrationAdrenergic beta-AntagonistsAngiotensin-Converting Enzyme Inhibitors

Identifiers

PMID27416001
PMCPMC6736515
OpenAlexW2461501036

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.