Abstract:
:The sojourn time, time spent in the preclinical detectable phase (PCDP) for chronic diseases, for example, breast cancer, plays an important role in the design and assessment of screening programmes. Traditional methods to estimate it usually assume a uniform incidence rate of preclinical disease from a randomized control group or historical data. In this paper, a two-parameter Markov chain model is proposed and developed to explicitly estimate the preclinical incidence rate (lambda 1) and the rate of transition from preclinical to clinical state (lambda 2, equivalent to the inverse of mean sojourn time) without using control data. A new estimate of sensitivity is proposed, based on the estimated parameters of the Markov process. When this method is applied to the data from the Swedish two-county study of breast cancer screening in the age group 70-74, the estimate of MST is 2.3 with 95 per cent CI ranging from 2.1 to 2.5, which is close to the result based on the traditional method but the 95 per cent CI is narrower using the Markov model. The reason for the greater precision of the latter is the fuller use of all temporal data, since the continuous exact times to events are used in our method instead of grouping them as in the traditional method. Ongoing and future researches should extend this model to include, for example, the tumour size, nodal status and malignancy grade, along with methods of simultaneously estimating sensitivity and the transition rates in the Markov process.
journal_name
Stat Medjournal_title
Statistics in medicineauthors
Duffy SW,Chen HH,Tabar L,Day NEdoi
10.1002/sim.4780141404subject
Has Abstractpub_date
1995-07-30 00:00:00pages
1531-43issue
14eissn
0277-6715issn
1097-0258journal_volume
14pub_type
临床试验,杂志文章,随机对照试验abstract::In this commentary, we revisit Sir Austin Bradford Hill's seminal Alfred Watson Memorial Lecture in 1962 through the eyes of two practicing biostatisticians of the current era. We summarize some eternal takeaway messages from Hill's lecture regarding observations and experiments translated through the modern lexicon o...
journal_title:Statistics in medicine
pub_type: 杂志文章
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journal_title:Statistics in medicine
pub_type: 杂志文章
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journal_title:Statistics in medicine
pub_type: 杂志文章
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journal_title:Statistics in medicine
pub_type: 临床试验,杂志文章,多中心研究,随机对照试验
doi:10.1002/sim.711
更新日期:2001-03-15 00:00:00
abstract::The analysis of patient-reported outcomes or other psychological traits can be realized using the Rasch measurement model. When the objective of a study is to compare groups of individuals, it is important, before the study, to define a sample size such that the group comparison test will attain a given power. The Ras...
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pub_type: 杂志文章
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更新日期:1998-12-30 00:00:00
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journal_title:Statistics in medicine
pub_type: 杂志文章
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更新日期:2007-01-15 00:00:00
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journal_title:Statistics in medicine
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更新日期:2014-11-10 00:00:00
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journal_title:Statistics in medicine
pub_type: 杂志文章
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pub_type: 杂志文章
doi:10.1002/sim.1506
更新日期:2003-05-15 00:00:00
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journal_title:Statistics in medicine
pub_type: 杂志文章
doi:10.1002/sim.1724
更新日期:2004-04-30 00:00:00
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pub_type: 杂志文章
doi:10.1002/sim.6306
更新日期:2014-12-20 00:00:00
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pub_type: 杂志文章
doi:10.1002/(sici)1097-0258(20000530)19:10<1319::aid-s
更新日期:2000-05-30 00:00:00
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pub_type: 杂志文章
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journal_title:Statistics in medicine
pub_type: 杂志文章
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