Literature DB >> 11782054

Hidden Markov models for the onset and progression of bronchiolitis obliterans syndrome in lung transplant recipients.

Christopher H Jackson1, Linda D Sharples.   

Abstract

Chronic rejection in lung transplant recipients is monitored by repeated measurement of forced expiratory volume in one second (FEV1). This marker is measured at irregular intervals and is also affected by covariates and short-term fluctuation. This paper describes the use of hidden Markov models for the underlying staged functional decline. Maximum likelihood methods are used to simultaneously estimate disease progression rates and the effects of mismeasurement and covariates. Copyright 2002 John Wiley & Sons, Ltd.

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Year:  2002        PMID: 11782054     DOI: 10.1002/sim.886

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  20 in total

1.  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

2.  Computation of the asymptotic null distribution of goodness-of-fit tests for multi-state models.

Authors:  Andrew C Titman
Journal:  Lifetime Data Anal       Date:  2009-11-01       Impact factor: 1.588

3.  Effect of common neuropathologies on progression of late life cognitive impairment.

Authors:  Lei Yu; Patricia A Boyle; Sue Leurgans; Julie A Schneider; Richard J Kryscio; Robert S Wilson; David A Bennett
Journal:  Neurobiol Aging       Date:  2015-04-22       Impact factor: 4.673

4.  Qualitative longitudinal analysis of symptoms in patients with primary and metastatic brain tumours.

Authors:  Frank Rijmen; Edward H Ip; Stephen Rapp; Edward G Shaw
Journal:  J R Stat Soc Ser A Stat Soc       Date:  2008       Impact factor: 2.483

5.  Non-Markov multistate modeling using time-varying covariates, with application to progression of liver fibrosis due to hepatitis C following liver transplant.

Authors:  Peter Bacchetti; Ross D Boylan; Norah A Terrault; Alexander Monto; Marina Berenguer
Journal:  Int J Biostat       Date:  2010-02-20       Impact factor: 0.968

6.  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

7.  Nonparametric inference and uniqueness for periodically observed progressive disease models.

Authors:  Beth Ann Griffin; Stephen W Lagakos
Journal:  Lifetime Data Anal       Date:  2009-07-23       Impact factor: 1.588

8.  Fibrosis progression in African Americans and Caucasian Americans with chronic hepatitis C.

Authors:  Norah A Terrault; Kelly Im; Ross Boylan; Peter Bacchetti; David E Kleiner; Robert J Fontana; Jay H Hoofnagle; Steven H Belle
Journal:  Clin Gastroenterol Hepatol       Date:  2008-08-19       Impact factor: 11.382

9.  Study design for non-recurring, time-to-event outcomes in the presence of error-prone diagnostic tests or self-reports.

Authors:  Xiangdong Gu; Raji Balasubramanian
Journal:  Stat Med       Date:  2016-05-18       Impact factor: 2.373

10.  SEMIPARAMETRIC TIME TO EVENT MODELS IN THE PRESENCE OF ERROR-PRONE, SELF-REPORTED OUTCOMES-WITH APPLICATION TO THE WOMEN'S HEALTH INITIATIVE.

Authors:  Xiangdong Gu; Yunsheng Ma; Raji Balasubramanian
Journal:  Ann Appl Stat       Date:  2015-06       Impact factor: 2.083

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