Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Pharmacoepidemiology...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Pharmacoepidemiology and Drug Safety
Article . 2009 . Peer-reviewed
License: Wiley Online Library User Agreement
Data sources: Crossref
versions View all 4 versions
addClaim

Reasons for non‐response in observational pharmacogenetic research

Authors: van Wieren-de Wijer, Diane B M A; Maitland-van der Zee, Anke-Hilse; de Boer, Anthonius; Kroon, Abraham A; de Leeuw, Peter W; Schiffers, Paul; Janssen, Rob G J H; +4 Authors

Reasons for non‐response in observational pharmacogenetic research

Abstract

AbstractPurposeIn epidemiological studies, non‐response may introduce bias and limit generalizability. In genetic pharmacoepidemiological research, collection of DNA might be a major reason for non‐response. We determined reasons for non‐response and compared characteristics of non‐responders and responders in a pharmacogenetic case‐control study.MethodsMyocardial infarction (MI) cases and controls, who were antihypertensive drug users, were recruited through community pharmacies that participate in the Pharmaco‐Morbidity‐Record‐Linkage‐System (PHARMO). The PHARMO database comprises drug dispensing histories of about 2 000 000 subjects from a representative sample of Dutch community pharmacies linked to the national registry of hospital discharges. Independent samples t‐test and ANOVA‐statistics were used to analyse the differences in continuous variables between responders and non‐responders. χ 2 statistics and logistic regression were used to compare categorical variables.ResultsWe approached 1871 cases and 14 102 controls of whom 794 MI cases (42.4%) and 4997 controls (35.4%) responded. We could not approach 2194 patients of whom 63.1% had died and 31.2% moved to another pharmacy. Main reasons for non‐response were health problems or hospital stays (16.2%, OR 1.47; 95%CI: 1.00–2.16). Other reasons were old age or dementia (16.9%, OR 1.82; 95%CI: 1.24–2.65). Only a small percentage (1.1%, OR 1.43; 95%CI: 0.41–5.03) mentioned DNA sampling as a reason. About 30% of the non‐responders did not give a reason. Women were statistically significantly (p < 0.0005) less willing to participate than men (38.8% versus 31.3%). An association with age was also found (mean age 64.6 versus 66.5 yrs) (p < 0.0005).ConclusionIn a pharmacogenetic case‐control study fear for genetic screening was not a major reported reason for non‐response. Females were less willing to participate than males. Copyright © 2009 John Wiley & Sons, Ltd.

Country
Netherlands
Keywords

Questionnaires, EMC NIHES-01-64-03, Adult, Male, Health Knowledge, Attitudes, Practice, Research Subjects, EMC NIHES-03-77-02, Myocardial Infarction, Risk Assessment, Risk Factors, Odds Ratio, Humans, Registries, Genetic Testing, Genetic Privacy, Antihypertensive Agents, Aged, Netherlands, Practice, Chi-Square Distribution, Health Knowledge, Patient Selection, Fear, Middle Aged, Correspondence as Topic, Telephone, Logistic Models, Pharmacogenetics, Attitudes, Case-Control Studies, Feasibility Studies, Female

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    9
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Average
Top 10%
Top 10%
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!