Literature DB >> 17077868

Simulation Procedure in Periodic Cancer Screening Trials.

Dongfeng Wu1, Xiaoqin Wu, Ioana Banicescu, Ricolindo L Cariño.   

Abstract

A general simulation procedure is described to validate model fitting algorithms for complex likelihood functions that are utilized in periodic cancer screening trials. Although screening programs have existed for a few decades, there are still many unsolved problems, such as how age or hormone affects the screening sensitivity, the sojourn time in the preclinical state, and the transition probability from disease-free state to the preclinical state. Simulations are needed to check reliability or validity of the likelihood function combined with the associated effect functions. One bottleneck in the simulation procedure is the very time consuming calculations of the maximum likelihood estimates (MLE) from generated data. A practical procedure is presented, along with results for when both sensitivity and transition probability into the preclinical state are age-dependent. The procedure is also suitable for other applications.

Entities:  

Year:  2005        PMID: 17077868      PMCID: PMC1513186     

Source DB:  PubMed          Journal:  J Mod Appl Stat Methods        ISSN: 1538-9472


  9 in total

1.  Testing the independence of two diagnostic tests.

Authors:  Y Shen; D Wu; M Zelen
Journal:  Biometrics       Date:  2001-12       Impact factor: 2.571

2.  MLE and Bayesian inference of age-dependent sensitivity and transition probability in periodic screening.

Authors:  Dongfeng Wu; Gary L Rosner; Lyle Broemeling
Journal:  Biometrics       Date:  2005-12       Impact factor: 2.571

3.  Estimating lead time and sensitivity in a screening program without estimating the incidence in the screened group.

Authors:  H Straatman; P G Peer; A L Verbeek
Journal:  Biometrics       Date:  1997-03       Impact factor: 2.571

4.  Estimation of the duration of a pre-clinical disease state using screening data.

Authors:  S D Walter; N E Day
Journal:  Am J Epidemiol       Date:  1983-12       Impact factor: 4.897

5.  Simplified models of screening for chronic disease: estimation procedures from mass screening programmes.

Authors:  N E Day; S D Walter
Journal:  Biometrics       Date:  1984-03       Impact factor: 2.571

6.  Estimation of sojourn time in chronic disease screening without data on interval cases.

Authors:  T H Chen; H S Kuo; M F Yen; M S Lai; L Tabar; S W Duffy
Journal:  Biometrics       Date:  2000-03       Impact factor: 2.571

7.  Effect of age, breast density, and family history on the sensitivity of first screening mammography.

Authors:  K Kerlikowske; D Grady; J Barclay; E A Sickles; V Ernster
Journal:  JAMA       Date:  1996-07-03       Impact factor: 56.272

8.  Canadian National Breast Screening Study: 1. Breast cancer detection and death rates among women aged 40 to 49 years.

Authors:  A B Miller; C J Baines; T To; C Wall
Journal:  CMAJ       Date:  1992-11-15       Impact factor: 8.262

9.  Canadian National Breast Screening Study: 2. Breast cancer detection and death rates among women aged 50 to 59 years.

Authors:  A B Miller; C J Baines; T To; C Wall
Journal:  CMAJ       Date:  1992-11-15       Impact factor: 8.262

  9 in total

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