Avoiding bias and incorrect confidence interval coverage in prescription drug labeling.
Background: The primary purpose of prescription drug labeling is to give healthcare professionals the information needed to prescribe drugs appropriately. Therefore, labeling typically reports the effects that the treatment might be expected to have on several efficacy measures, including not only t...
| Publicado en: | Clinical Trials Vol. 13; no. 2; pp. 199 - 205 |
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| Autor principal: | |
| Formato: | equations & formulas tables/charts Journal Article |
| Publicado: |
Sage Publications, Ltd.
Apr2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=113623254&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 113623254 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 17407745 AB6 jtl: Clinical Trials issn: 17407745 maglogo: N pubinfo: dt: Apr2016 vid: 13 iid: 2 pid: 33180 pub: Sage Publications, Ltd. place: <Blank> artinfo: ui: 113623254 113623254 113623254 10.1177/1740774515615097 113623254 ppf: 199 ppct: 6 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Avoiding bias and incorrect confidence interval coverage in prescription drug labeling. aug: au: Levin, Gregory affil: Food and Drug Administration, Silver Spring, MD, USA sug: subj: Drug Labeling Clinical Trials Bias (Research) Confidence Intervals United States Food and Drug Administration Government Regulations United States United States ab: Background: The primary purpose of prescription drug labeling is to give healthcare professionals the information needed to prescribe drugs appropriately. Therefore, labeling typically reports the effects that the treatment might be expected to have on several efficacy measures, including not only the primary endpoint used to establish effectiveness but also a number of key secondary endpoints that are important to practitioners and patients. Methods: One possible regulatory approach to drug labeling is to include results on important secondary efficacy endpoints in labeling only if there is statistical evidence of a treatment effect and a clinically meaningful estimated effect. We evaluate the statistical consequences of this approach by deriving and discussing the potential bias in point estimates and deviation from nominal coverage in confidence intervals that are reported in labeling. Results: Such an approach can lead to substantial conditional bias in point estimates (toward spuriously greater effects than the truth) and undercoverage in confidence intervals. Conclusion: These statistical properties may have important and undesirable regulatory and public health implications. We discuss an alternative approach to include results in labeling for a selected set of reliably ascertained, clinically important endpoints whether or not there is evidence of a treatment effect. pubtype: Academic Journal doctype: equations & formulas tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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