Literature DB >> 2434150

A Markov model for analysing cancer markers and disease states in survival studies.

R Kay.   

Abstract

In studies of serial cancer markers or disease states and their relation to survival, data on the marker or state are usually obtained at infrequent time points during follow-up. A Markov model is developed to assess the dependence of risk of death on marker level or disease state and inferences within this model are based directly on data collected in this haphazard way. An application relating changing levels of serum alpha-fetoprotein to death in hepatocellular carcinoma is discussed in detail.

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Year:  1986        PMID: 2434150

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  54 in total

Review 1.  Multi-state models: a review.

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

2.  Design of panel studies for disease progression with multiple stages.

Authors:  Wei-Ting Hwang; Ron Brookmeyer
Journal:  Lifetime Data Anal       Date:  2003-09       Impact factor: 1.588

Review 3.  Inference for outcome probabilities in multi-state models.

Authors:  Per Kragh Andersen; Maja Pohar Perme
Journal:  Lifetime Data Anal       Date:  2008-09-13       Impact factor: 1.588

4.  Modeling Disease Progression with Longitudinal Markers.

Authors:  Lurdes Y T Inoue; Ruth Etzioni; Christopher Morrell; Peter Müller
Journal:  J Am Stat Assoc       Date:  2008       Impact factor: 5.033

5.  Approaches to the analysis of quality of life data: experiences gained from a medical research council lung cancer working party palliative chemotherapy trial.

Authors:  P Hopwood; R J Stephens; D Machin
Journal:  Qual Life Res       Date:  1994-10       Impact factor: 4.147

6.  Modeling transition rates using panel current-status data: how serious is the bias?

Authors:  Douglas A Wolf; Thomas M Gill
Journal:  Demography       Date:  2009-05

7.  Markov chains and semi-Markov models in time-to-event analysis.

Authors:  Erin L Abner; Richard J Charnigo; Richard J Kryscio
Journal:  J Biom Biostat       Date:  2013-10-25

8.  Multi-state models for the analysis of time-to-event data.

Authors:  Luís Meira-Machado; Jacobo de Uña-Alvarez; Carmen Cadarso-Suárez; Per K Andersen
Journal:  Stat Methods Med Res       Date:  2008-06-18       Impact factor: 3.021

9.  Landmark risk prediction of residual life for breast cancer survival.

Authors:  Layla Parast; Tianxi Cai
Journal:  Stat Med       Date:  2013-03-14       Impact factor: 2.373

10.  A nonstationary Markov transition model for computing the relative risk of dementia before death.

Authors:  Lei Yu; William S Griffith; Suzanne L Tyas; David A Snowdon; Richard J Kryscio
Journal:  Stat Med       Date:  2010-03-15       Impact factor: 2.373

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