Linked Life Data

14716729

Source:http://linkedlifedata.com/resource/pubmed/id/14716729

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2004-1-12
pubmed:abstractText
Recent research in Alzheimer's disease (AD) is centred about the early detection and prevention of this disease. Several recent moderate size clinical trials targeted at high risk cohorts have been designed along this theme. There have been few attempts to design a large trial to prevent this disease in elderly individuals at low risk for the disease. The purpose of this paper is to suggest a framework for designing a simple, large AD prevention trial. This framework uses a discrete time hazard model for decreasing the incidence of AD when participants are randomly assigned to one or more active prevention agents or placebo. This design allows for differential incidence among participants due to age, family history, genetic disposition, and ethnicity. It takes into account the length of the follow-up period, participant mortality, drop-outs, drop-ins, and loss to follow-up. This framework is illustrated by PREADVISE, a recently initiated large add-on prevention trial investigating the use of anti-oxidants for preventing AD among men enrolled in a even larger prostate cancer prevention study, SELECT.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jan
pubmed:issn
0277-6715
pubmed:author
pubmed:copyrightInfo
Copyright 2004 John Wiley & Sons, Ltd.
pubmed:issnType
Print
pubmed:day
30
pubmed:volume
23
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
285-96
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
2004
pubmed:articleTitle
Designing a large prevention trial: statistical issues.
pubmed:affiliation
Department of Statistics, University of Kentucky, Lexington 40536-0230, USA. kryscio@uky.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S.