Literature DB >> 17303192

Identifiability of the joint distribution of age and tumor size at detection in the presence of screening.

Leonid Hanin1, Andrei Yakovlev.   

Abstract

In recent years, a stochastic model of cancer development and detection allowing for arbitrary screening schedules has been developed and applied to analysis of screening trials and population-based cancer incidence and mortality data. The model is entirely mechanistic, builds on a minimal set of biologically plausible assumptions, and yields the joint distribution of tumor size and age of a patient at the time of diagnosis. Whether or not parameters of the model can be estimated from data generated by cohort studies depends on model identifiability. The present paper provides a proof of this important property of the model.

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Year:  2007        PMID: 17303192      PMCID: PMC2041843          DOI: 10.1016/j.mbs.2006.12.004

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  25 in total

1.  On the parameters of the clonal expansion model.

Authors:  W F Heidenreich
Journal:  Radiat Environ Biophys       Date:  1996-05       Impact factor: 1.925

2.  A distribution of tumor size at detection: an application to breast cancer data.

Authors:  A D Tsodikov; B Asselain; A Y Yakovlev
Journal:  Biometrics       Date:  1997-12       Impact factor: 2.571

3.  Some properties of the hazard function of the two-mutation clonal expansion model.

Authors:  W F Heidenreich; E G Luebeck; S H Moolgavkar
Journal:  Risk Anal       Date:  1997-06       Impact factor: 4.000

4.  A nonidentifiability aspect of the two-stage model of carcinogenesis.

Authors:  L G Hanin
Journal:  Risk Anal       Date:  1996-10       Impact factor: 4.000

5.  Effect of screening and adjuvant therapy on mortality from breast cancer.

Authors:  Donald A Berry; Kathleen A Cronin; Sylvia K Plevritis; Dennis G Fryback; Lauren Clarke; Marvin Zelen; Jeanne S Mandelblatt; Andrei Y Yakovlev; J Dik F Habbema; Eric J Feuer
Journal:  N Engl J Med       Date:  2005-10-27       Impact factor: 91.245

6.  The University of Rochester model of breast cancer detection and survival.

Authors:  Leonid G Hanin; Anthony Miller; A V Zorin; Andrei Y Yakovlev
Journal:  J Natl Cancer Inst Monogr       Date:  2006

Review 7.  Multivariate distributions of clinical covariates at the time of cancer detection.

Authors:  L G Hanin; A Y Yakovlev
Journal:  Stat Methods Med Res       Date:  2004-12       Impact factor: 3.021

8.  Age-dependent growth rate of primary breast cancer.

Authors:  P G Peer; J A van Dijck; J H Hendriks; R Holland; A L Verbeek
Journal:  Cancer       Date:  1993-06-01       Impact factor: 6.860

9.  Discrete strategies of cancer post-treatment surveillance. Estimation and optimization problems.

Authors:  A D Tsodikov; B Asselain; A Fourque; T Hoang
Journal:  Biometrics       Date:  1995-06       Impact factor: 2.571

10.  Estimation of mean sojourn time in breast cancer screening using a Markov chain model of both entry to and exit from the preclinical detectable phase.

Authors:  S W Duffy; H H Chen; L Tabar; N E Day
Journal:  Stat Med       Date:  1995-07-30       Impact factor: 2.373

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