Literature DB >> 6638001

Lead time estimation in a controlled screening program.

J S Chen, P C Prorok.   

Abstract

A method is presented for estimating a discrete form of the lead time distribution of cases detected in a single-shot screening program. The procedure is based upon a three-state progressive disease model of disease natural history and screening which focuses on the age at entry into the preclinical disease state, the duration of the preclinical state, and the age at screening or observation. Estimation is accomplished by comparing observed incidence rates of the disease between a screened group and a randomized control group in successive follow-up intervals after the screen. No assumptions concerning the false negative rate of the screening test or the distribution of the duration of time spent in the preclinical disease state are required. An example is presented by means of breast cancer screening data.

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Mesh:

Year:  1983        PMID: 6638001     DOI: 10.1093/oxfordjournals.aje.a113685

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  4 in total

1.  A reality check for overdiagnosis estimates associated with breast cancer screening.

Authors:  Ruth Etzioni; Jing Xia; Rebecca Hubbard; Noel S Weiss; Roman Gulati
Journal:  J Natl Cancer Inst       Date:  2014-10-31       Impact factor: 13.506

2.  A Bayesian model for estimating multi-state disease progression.

Authors:  Shiwen Shen; Simon X Han; Panayiotis Petousis; Robert E Weiss; Frank Meng; Alex A T Bui; William Hsu
Journal:  Comput Biol Med       Date:  2016-12-22       Impact factor: 4.589

3.  Quantifying the duration of the preclinical detectable phase in cancer screening: a systematic review.

Authors:  Sandra M E Geurts; Anne M W M Aarts; André L M Verbeek; Tony H H Chen; Mireille J M Broeders; Stephen W Duffy
Journal:  Epidemiol Health       Date:  2022-01-03

4.  A mathematical model of case-ascertainment bias: Applied to case-control studies nested within a randomized screening trial.

Authors:  Rick J Jansen; Bruce H Alexander; Richard B Hayes; Anthony B Miller; Sholom Wacholder; Timothy R Church
Journal:  PLoS One       Date:  2018-03-19       Impact factor: 3.240

  4 in total

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