Literature DB >> 9385108

A parametric multistate model for the analysis of carcinogenicity experiments.

R Z Omar1, N Stallard, J Whitehead.   

Abstract

A fully parametric multistate model is explored for the analysis of animal carcinogenicity experiments in which the time of tumour onset is not known. This model does not require assumptions about tumour lethality or cause of death judgements and can be fitted in the absence of sacrifice data. The model is constructed as a three-state model with simple parametric forms for the transition rates. Maximum likelihood methods are used to estimate the transition rates and different treatment groups are compared using likelihood ratio tests. Selection of an appropriate model and methods to assess the fit of the model are illustrated with data from animal experiments. Comparisons with standard methods are made.

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Year:  1995        PMID: 9385108     DOI: 10.1007/bf00985448

Source DB:  PubMed          Journal:  Lifetime Data Anal        ISSN: 1380-7870            Impact factor:   1.588


  17 in total

1.  A simple stochastic model of recovery, relapse, death and loss of patients.

Authors:  E FIX; J NEYMAN
Journal:  Hum Biol       Date:  1951-09       Impact factor: 0.553

2.  Nonparametric methods for survival/sacrifice experiments.

Authors:  A Dewanji; J D Kalbfleisch
Journal:  Biometrics       Date:  1986-06       Impact factor: 2.571

3.  Semiparametric analysis of tumor incidence rates in survival/sacrifice experiments.

Authors:  C J Portier; G E Dinse
Journal:  Biometrics       Date:  1987-03       Impact factor: 2.571

4.  Efficiencies of experimental designs for an illness-death model.

Authors:  O Borgan; K Liestøl; P Ebbesen
Journal:  Biometrics       Date:  1984-09       Impact factor: 2.571

5.  Guidelines for simple, sensitive significance tests for carcinogenic effects in long-term animal experiments.

Authors:  R Peto; M C Pike; N E Day; R G Gray; P N Lee; S Parish; J Peto; S Richards; J Wahrendorf
Journal:  IARC Monogr Eval Carcinog Risk Chem Hum Suppl       Date:  1980

6.  A time-dependent statistical model which relates current clinical status to prognosis: application to advanced prostatic cancer.

Authors:  L E Myers; D F Paulson; W R Berry; E B Cox; J Laszlos; W Stanley
Journal:  J Chronic Dis       Date:  1980

7.  A Weibull model for the estimation of tumorigenic potency.

Authors:  A Dewanji; D Krewski; M J Goddard
Journal:  Biometrics       Date:  1993-06       Impact factor: 2.571

8.  Evaluating constraints that allow survival-adjusted incidence analyses in single-sacrifice studies.

Authors:  G E Dinse
Journal:  Biometrics       Date:  1993-06       Impact factor: 2.571

9.  Constant risk differences in the analysis of animal tumorigenicity data.

Authors:  G E Dinse
Journal:  Biometrics       Date:  1991-06       Impact factor: 2.571

10.  The age distribution of cancer and a multi-stage theory of carcinogenesis.

Authors:  P ARMITAGE; R DOLL
Journal:  Br J Cancer       Date:  1954-03       Impact factor: 7.640

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  2 in total

Review 1.  Multi-state models: a review.

Authors:  P Hougaard
Journal:  Lifetime Data Anal       Date:  1999-09       Impact factor: 1.588

2.  Assessing Prognostic Factors in Hodgkin's Lymphoma: Multistate Illness-Death Model.

Authors:  Fatemeh Javanmardi; Amal Saki-Malehi; Ahmad Ahmadzadeh; Fakher Rahim
Journal:  Int J Hematol Oncol Stem Cell Res       Date:  2018-01-01
  2 in total

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