Evidence map›Paper›PMID 29196989›Full record

ArticleDrug safety2018

Mixed Approach Retrospective Analyses of Suicide and Suicidal Ideation for Brand Compared with Generic Central Nervous System Drugs.

Ning Cheng, Md Motiur Rahman, Yasser Alatawi, Jingjing Qian, Peggy L Peissig, Richard L Berg, C David Page, Richard A Hansen

Abstract read
In one paragraph

Article in Drug safety, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

9 citing papers in PubMed, 13 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 1 country.

Ning ChengDepartment of Health Outcomes Research and Policy, Harrison School of Pharmacy, Auburn University, Auburn, AL, USA.
Md Motiur RahmanDepartment of Health Outcomes Research and Policy, Harrison School of Pharmacy, Auburn University, Auburn, AL, USA.
Yasser AlatawiDepartment of Health Outcomes Research and Policy, Harrison School of Pharmacy, Auburn University, Auburn, AL, USA.
Jingjing QianDepartment of Health Outcomes Research and Policy, Harrison School of Pharmacy, Auburn University, Auburn, AL, USA.
Peggy L PeissigBiomedical Informatics Research Center, Marshfield Clinic Research Institute, Marshfield, WI, USA.
Richard L BergBiomedical Informatics Research Center, Marshfield Clinic Research Institute, Marshfield, WI, USA.
C David PageDepartment of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA.
Richard A HansenDepartment of Health Outcomes Research and Policy, Harrison School of Pharmacy, Auburn University, Auburn, AL, USA. rah0019@auburn.edu.
Auburn University · USMarshfield Clinic · USMarshfield Clinic · USUniversity of Wisconsin–Madison · US

Funding

Machine Learning for Identifying Adverse Drug EventsR01GM097618 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI CALDWELL, MICHAEL DEFOIX, HANSEN, RICHARD A. · 2011 to 2018
$3.8M
Post-market Authorized Generic Evaluation (PAGE)U01FD005272 · FDA · AUBURN UNIVERSITY AT AUBURN · PI HANSEN, RICHARD A. · 2014 to 2015
$400k
FDA HHS U01 FD005272NIGMS NIH HHS R01 GM097618NIH HHS 2R01GM097618-04U.S. Food and Drug Administration HHSF2232015101102CU.S. Food and Drug Administration U01FD005272
6 · The paper itself

Abstract

introductionSeveral different types of drugs acting on the central nervous system (CNS) have previously been associated with an increased risk of suicide and suicidal ideation (broadly referred to as suicide). However, a differential association between brand and generic CNS drugs and suicide has not been reported.

objectivesThis study compares suicide adverse event rates for brand versus generic CNS drugs using multiple sources of data.

methodsSelected examples of CNS drugs (sertraline, gabapentin, zolpidem, and methylphenidate) were evaluated via the US FDA Adverse Event Reporting System (FAERS) for a hypothesis-generating study, and then via administrative claims and electronic health record (EHR) data for a more rigorous retrospective cohort study. Disproportionality analyses with reporting odds ratios and 95% confidence intervals (CIs) were used in the FAERS analyses to quantify the association between each drug and reported suicide. For the cohort studies, Cox proportional hazards models were used, controlling for demographic and clinical characteristics as well as the background risk of suicide in the insured population.

resultsThe FAERS analyses found significantly lower suicide reporting rates for brands compared with generics for all four studied products (Breslow-Day P < 0.05). In the claims- and EHR-based cohort study, the adjusted hazard ratio (HR) was statistically significant only for sertraline (HR 0.58; 95% CI 0.38-0.88).

conclusionSuicide reporting rates were disproportionately larger for generic than for brand CNS drugs in FAERS and adjusted retrospective cohort analyses remained significant only for sertraline. However, even for sertraline, temporal confounding related to the close proximity of black box warnings and generic availability is possible. Additional analyses in larger data sources with additional drugs are needed.

Indexed as

AdolescentAdultAdverse Drug Reaction Reporting SystemsAgedCentral Nervous System AgentsDrug-Related Side Effects and Adverse ReactionsDrugs, GenericElectronic Health RecordsFemaleHumansMaleMiddle AgedOdds RatioProportional Hazards ModelsRetrospective StudiesSuicidal IdeationCentral Nervous System AgentsDrugs, Generic

Identifiers

PMID29196989
PMCPMC5878739
OpenAlexW2771121839

What OpenQuestion holds

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Registered trials

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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.