Evidence map›Paper›PMID 29605890›Full record

ArticleEuropean journal of epidemiology2018

Hypothesis-free screening of large administrative databases for unsuspected drug-outcome associations.

Jesper Hallas, Shirley V Wang, Joshua J Gagne, Sebastian Schneeweiss, Nicole Pratt, Anton Pottegård

Abstract read
PubMed Publisher
In one paragraph

Article in European journal of epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 3 pooled it
–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

22 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  16. Use of State Sequence Analysis in Pharmacoepidemiology: A Tutorial.International journal of environmental research and public health · 2021
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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

6 authors.

Jesper HallasDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. jhallas@health.sdu.dk.ORCID http://orcid.org/0000-0002-8097-8708
Shirley V WangDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Joshua J GagneDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Sebastian SchneeweissDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Nicole PrattQuality Use of Medicines and Pharmacy Research Centre, Sansom Institute, University of South Australia, Adelaide, Australia.
Anton PottegårdClinical Pharmacology and Pharmacy, Department of Public Health, University of Southern Denmark, JB Winsløwsvej 19, 2, 5000, Odense C, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Active surveillance for unknown or unsuspected adverse drug effects may be carried out by applying epidemiological techniques to large administrative databases. Self-controlled designs, like the symmetry design, have the advantage over conventional design of adjusting for confounders that are stable over time. The aim of this paper was to describe the output of a comprehensive open-ended symmetry analysis of a large dataset. All drug dispensings and all secondary care contacts in Denmark during the period 1995-2012 for persons born before 1950 were analyzed by a symmetry design. We analyzed all drug-drug sequences and all drug-disease sequences occurring during the study period. The identified associations were ranked according to the number of outcomes that potentially could be attributed to the exposure. In the main analysis, 29,891,212 incident drug therapies, and 21,300,000 incident diagnoses were included. Out of 186,758 associations tested in the main analysis, 43,575 (23.3%) showed meaningful effect size. For the top 200 drug-drug associations, 47% represented unknown associations, 24% represented known adverse drug reactions, 30% were explained by mutual indication or reverse causation. For the top 200 drug-disease associations the proportions were 31, 15, and 55%, respectively. Screening by symmetry analysis can be a useful starting point for systematic pharmacovigilance activities if coupled with a systematic post-hoc review of signals.

Indexed as

Databases, FactualPharmacovigilanceDenmarkDrug-Related Side Effects and Adverse ReactionsRisk FactorsDatabasesPharmacovigillancePharmcoepidemiologyScreeningSelf-controlled design

Identifiers

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.