Evidence map›Paper›PMID 35357769›Full record

ArticleBasic & clinical pharmacology & toxicology2022

Incidence in pharmacoepidemiology-Basic definitions and types of misclassification.

Mikael Hoffmann, Henrik Støvring

Abstract read
In one paragraph

Article in Basic & clinical pharmacology & toxicology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
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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

2 authors.

Mikael HoffmannHealth Care Analysis, Division of Society and Health, Linköping University, Sweden & The NEPI Foundation, Stockholm, Sweden.ORCID https://orcid.org/0000-0001-9420-3316
Henrik StøvringClinical Pharmacology, Pharmacy and Environmental Medicine, University of Southern Denmark, Odense, Denmark.ORCID https://orcid.org/0000-0002-5821-2351

Funding

NEPI foundation SE802400-2589
6 · The paper itself

Abstract

The definition of a new case is a vital step in incidence studies in both epidemiology and pharmacoepidemiology, although with significant differences in methodology between the fields. We define and apply a framework for two different types of new cases of drug use, first-ever and recurrent, and show how the associated misclassifications related to length of run-in period can be expressed by the positive predictive value (PPV). In the study, we consider individual-level dispensations of statins 2006-2019 for 1,017,058 individuals with at least one dispensation in 2019 in Sweden. The incidence proportion for statins for both sexes of all ages in Sweden 2019 varied from 17.4/1000 with a run-in of 8 months, 9.45/1000 with 5 years and 8.4/1000 with 10 years. The PPV was 49% with 8 months and 89% for 5 years using 10 years as gold standard. We conclude that the interpretation of incidence and thus the selection of an appropriate run-in period, in pharmacoepidemiology, depends on whether first-ever use, recurrent treatment or both together (new cases) is the focus of the research question studied. At least five different misclassifications can be introduced depending on how incidence is defined.

Indexed as

Hydroxymethylglutaryl-CoA Reductase InhibitorsPharmacoepidemiologyCohort StudiesFemaleHumansIncidenceInfantMalePredictive Value of TestsHydroxymethylglutaryl-CoA Reductase Inhibitorsincidencemisclassificationpharmacoepidemiologyrun-instatins

Identifiers

PMID35357769
PMCPMC9320840

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.