Evidence map›Paper›PMID 23786578›Full record

ArticleJournal of biopharmaceutical statistics2013

Medical records-based postmarketing safety evaluation of rare events with uncertain status.

Hongyuan Cao, Lisa M LaVange, Joseph F Heyse, T Christopher Mast, Michael R Kosorok

Abstract read
In one paragraph

Article in Journal of biopharmaceutical statistics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 90% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

5 authors at 4 institutions in 1 country.

Hongyuan CaoDepartment of Health Studies, University of Chicago, Chicago, IL 60637, USA. hycao@uchicago.edu
Lisa M LaVange
Joseph F Heyse
T Christopher Mast
Michael R Kosorok
University of North Carolina at Chapel Hill · USDecision Sciences (United States) · USMerck & Co., Inc., Rahway, NJ, USA (United States) · USUniversity of Chicago · US

Funding

Statistical Methods for Cancer Clinical TrialsP01CA142538 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI TSIATIS, ANASTASIOS A · 2010 to 2019
$21.3M
NCI NIH HHS CA142538NCI NIH HHS P01 CA142538
6 · The paper itself

Abstract

We develop a simple statistic for comparing rates of rare adverse events between treatment groups in postmarketing safety studies where the events have uncertain status. In this setting, the statistic is asymptotically equivalent to the logrank statistic, but the limiting distribution has Poisson and binomial components instead of being Gaussian. We develop two new procedures for computing critical values: a Gaussian approximation and a parametric bootstrap. Both numerical and asymptotic properties of the procedures are studied. The test procedures are demonstrated on a postmarketing safety study of the RotaTeq vaccine. This vaccine was developed to reduce the incidence of severe diarrhea in infants.

Indexed as

Consumer Product SafetyModels, StatisticalUncertaintyHumansMedical RecordsProduct Surveillance, PostmarketingRotavirus VaccinesVaccines, AttenuatedRotaTeqRotavirus VaccinesVaccines, Attenuated

Identifiers

PMID23786578
PMCPMC4491986
OpenAlexW2083865080

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.