Evidence map›Paper›PMID 29714520›Full record

ReviewTherapeutic innovation & regulatory science2018

Sources of Safety Data and Statistical Strategies for Design and Analysis: Postmarket Surveillance.

Rima Izem, Matilde Sanchez-Kam, Haijun Ma, Richard Zink, Yueqin Zhao

Abstract readReview
In one paragraph

Review in Therapeutic innovation & regulatory science, 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
–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

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.

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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

5 authors.

Rima IzemFood and Drug Administration, Center for Drug Evaluation and Research, Office of Biostatistics, WO Building 21, Silver Spring, MD, 20903, USA. rima.izem@fda.hhs.gov.
Matilde Sanchez-KamSanchezKam, LLC, Alexandria, VA, USA.
Haijun MaAmgen, Inc, Thousand Oaks, CA, USA.
Richard ZinkSAS institute, Inc, JMP Life Sciences, Cary, NC, USA.
Yueqin ZhaoFood and Drug Administration, Center for Drug Evaluation and Research, Office of Biostatistics, WO Building 21, Silver Spring, MD, 20903, USA.

Funding

Intramural FDA HHS FD999999
6 · The paper itself

Abstract

backgroundSafety data are continuously evaluated throughout the life cycle of a medical product to accurately assess and characterize the risks associated with the product. The knowledge about a medical product's safety profile continually evolves as safety data accumulate.

methodsThis paper discusses data sources and analysis considerations for safety signal detection after a medical product is approved for marketing. This manuscript is the second in a series of papers from the American Statistical Association Biopharmaceutical Section Safety Working Group.

resultsWe share our recommendations for the statistical and graphical methodologies necessary to appropriately analyze, report, and interpret safety outcomes, and we discuss the advantages and disadvantages of safety data obtained from passive postmarketing surveillance systems compared to other sources.

conclusionsSignal detection has traditionally relied on spontaneous reporting databases that have been available worldwide for decades. However, current regulatory guidelines and ease of reporting have increased the size of these databases exponentially over the last few years. With such large databases, data-mining tools using disproportionality analysis and helpful graphics are often used to detect potential signals. Although the data sources have many limitations, analyses of these data have been successful at identifying safety signals postmarketing. Experience analyzing these dynamic data is useful in understanding the potential and limitations of analyses with new data sources such as social media, claims, or electronic medical records data.

Indexed as

Data CollectionData Interpretation, StatisticalDrug-Related Side Effects and Adverse ReactionsHumansPatient SafetyProduct Surveillance, PostmarketingResearch Designadverse eventsdata miningpassive surveillancepostmarket surveillancesignal detection

Identifiers

PMID29714520
PMCPMC5987777

What OpenQuestion holds

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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.