Linked Life Data

17725809

Source:http://linkedlifedata.com/resource/pubmed/id/17725809

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2008-5-16
pubmed:abstractText
Consider a group of subjects who are offered an opportunity to receive a sequence of periodic special examinations for the purpose of diagnosing a chronic disease earlier relative to usual care. The mortality for the early detection group is to be compared with a group receiving usual care. Benefit is reflected in a potential reduction in mortality. This article develops a general probability model that can be used to predict cumulative mortality for each of these groups. The elements of the model assume (i) a four-state progressive disease model in which a subject may be in a disease-free state (or a disease state that cannot be detected), preclinical disease state (capable of being diagnosed by a special exam), clinical state (diagnosis by usual care), and a death state; (ii) age-dependent transitions into the states; (iii) age-dependent examination sensitivity; (iv) age-dependent sojourn time in each state; and (v) the distribution of disease stages on diagnosis conditional on modality of detection. The model may be used to (i) compare mortality rates for different screening schedules; (ii) explore potential benefit of subpopulations; and (iii) compare relative reductions in disease-specific mortality due to advances and dissemination of both treatment and early detection screening programs.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jun
pubmed:issn
1541-0420
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
64
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
386-95
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
Mortality modeling of early detection programs.
pubmed:affiliation
Harvard School of Public Health and the Dana-Farber Cancer Institute, Boston, Massachusetts 02115, USA. lee.sandra@jimmy.harvard.edu
pubmed:publicationType
Journal Article, Research Support, N.I.H., Extramural