| A graphical assessment of the potential impact of losses to follow-up on the validity of study results. The Terry Beirn Community Programs for Clinical Research on AIDS. | |
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MedLine Citation:
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PMID: 9304765 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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Losses to follow-up in clinical trials-patients for whom we do not know if the outcome of interest has occurred-can bias study results. If we investigate extreme case scenarios and find the study results do not change much, impact is negligible. If not, we may need to interpret the study's results with caution. At issue is how much caution do we need? We describe a graphical approach to assess the potential impact of losses to follow-up on the validity of study results. One can create the graphs using design estimates and interim or final data. We give two examples using design parameters and another example modelled after observed data from clinical trials conducted by the Terry Beirn Community Programs for Clinical Research on AIDS. The examples illustrate that tolerable levels of losses to follow-up change depending on the overall outcome and direction of differential losses. |
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Authors:
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J P Matts; C A Launer; E T Nelson; C Miller; B Dain |
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Publication Detail:
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Type: Journal Article; Research Support, U.S. Gov't, P.H.S. |
Journal Detail:
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Title: Statistics in medicine Volume: 16 ISSN: 0277-6715 ISO Abbreviation: Stat Med Publication Date: 1997 Sep |
Date Detail:
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Created Date: 1997-11-20 Completed Date: 1997-11-20 Revised Date: 2007-11-15 |
Medline Journal Info:
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Nlm Unique ID: 8215016 Medline TA: Stat Med Country: ENGLAND |
Other Details:
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Languages: eng Pagination: 1943-54 Citation Subset: IM |
Affiliation:
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Division of Biostatistics, University of Minnesota, Minneapolis 55414, USA. |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Bias (Epidemiology) Clinical Trials as Topic / standards, statistics & numerical data* Humans Models, Statistical Patient Dropouts / statistics & numerical data* Research Design Sample Size Treatment Outcome |
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