Pattern recognition in menstrual bleeding diaries by statistical cluster analysis.
Background: The aim of this paper is to empirically identify a treatment-independent statistical method to describe clinically relevant bleeding patterns by using bleeding diaries of clinical studies on various sex hormone containing drugs.Methods: We used the four cluster analysis methods single, a...
| Published in: | BMC Women's Health Vol. 9; pp. 21 - 22 |
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| Main Authors: | , , , , , , , |
| Format: | research Journal Article |
| Published: |
BioMed Central
2009
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105394868&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105394868 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 14726874 1CIP jtl: BMC Women's Health issn: 14726874 maglogo: N pubinfo: dt: 2009 vid: 9 pid: 24147 pub: BioMed Central artinfo: ui: 105394868 NLM19607665 2010357557 10.1186/1472-6874-9-21 NLM19607665 105394868 ppf: 21 ppct: 1 formats: fmt: @attributes: type: P tig: atl: Pattern recognition in menstrual bleeding diaries by statistical cluster analysis. aug: au: Gerlinger C Wessel J Kallischnigg G Endrikat J Gerlinger, Christoph Wessel, Jens Kallischnigg, Gerd Endrikat, Jan affil: Global Clinical Statistics, Bayer Schering Pharma AG, Müllerstrasse 178, 13342 Berlin, Germany sug: subj: Menstruation Drug Effects Menstruation Physiology Sex Hormones Administration and Dosage Adolescence Adult Cluster Analysis Female Medical Records Metrorrhagia Chemically Induced Perception Sex Hormones Adverse Effects Time Factors Human Adolescent: 13-18 years Adult: 19-44 years Female ab: Background: The aim of this paper is to empirically identify a treatment-independent statistical method to describe clinically relevant bleeding patterns by using bleeding diaries of clinical studies on various sex hormone containing drugs.Methods: We used the four cluster analysis methods single, average and complete linkage as well as the method of Ward for the pattern recognition in menstrual bleeding diaries. The optimal number of clusters was determined using the semi-partial R2, the cubic cluster criterion, the pseudo-F- and the pseudo-t2-statistic. Finally, the interpretability of the results from a gynecological point of view was assessed.Results: The method of Ward yielded distinct clusters of the bleeding diaries. The other methods successively chained the observations into one cluster. The optimal number of distinctive bleeding patterns was six. We found two desirable and four undesirable bleeding patterns. Cyclic and non cyclic bleeding patterns were well separated.Conclusion: Using this cluster analysis with the method of Ward medications and devices having an impact on bleeding can be easily compared and categorized. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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