Literature DB >> 23807694

A competing risks approach for nonparametric estimation of transition probabilities in a non-Markov illness-death model.

Arthur Allignol1, Jan Beyersmann, Thomas Gerds, Aurélien Latouche.   

Abstract

Competing risks model time to first event and type of first event. An example from hospital epidemiology is the incidence of hospital-acquired infection, which has to account for hospital discharge of non-infected patients as a competing risk. An illness-death model would allow to further study hospital outcomes of infected patients. Such a model typically relies on a Markov assumption. However, it is conceivable that the future course of an infected patient does not only depend on the time since hospital admission and current infection status but also on the time since infection. We demonstrate how a modified competing risks model can be used for nonparametric estimation of transition probabilities when the Markov assumption is violated.

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Year:  2013        PMID: 23807694     DOI: 10.1007/s10985-013-9269-1

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


  14 in total

1.  Robust inference for event probabilities with non-Markov event data.

Authors:  David V Glidden
Journal:  Biometrics       Date:  2002-06       Impact factor: 2.571

2.  A note on variance estimation of the Aalen-Johansen estimator of the cumulative incidence function in competing risks, with a view towards left-truncated data.

Authors:  Arthur Allignol; Martin Schumacher; Jan Beyersmann
Journal:  Biom J       Date:  2010-02       Impact factor: 2.207

3.  The importance of good data, analysis, and interpretation for showing the economics of reducing healthcare-associated infection.

Authors:  Nicholas Graves; Adrian G Barnett; Kate Halton; Christopher Crnich; Ben Cooper; Jan Beyersmann; Martin Wolkewitz; Matthew Samore; Stephan Harbarth
Journal:  Infect Control Hosp Epidemiol       Date:  2011-09       Impact factor: 3.254

Review 4.  Estimating the proportion of healthcare-associated infections that are reasonably preventable and the related mortality and costs.

Authors:  Craig A Umscheid; Matthew D Mitchell; Jalpa A Doshi; Rajender Agarwal; Kendal Williams; Patrick J Brennan
Journal:  Infect Control Hosp Epidemiol       Date:  2011-02       Impact factor: 3.254

Review 5.  Application of multistate models in hospital epidemiology: advances and challenges.

Authors:  Jan Beyersmann; Martin Wolkewitz; Arthur Allignol; Nadine Grambauer; Martin Schumacher
Journal:  Biom J       Date:  2011-01-14       Impact factor: 2.207

6.  Multistate modelling to estimate the excess length of stay associated with meticillin-resistant Staphylococcus aureus colonisation and infection in surgical patients.

Authors:  G De Angelis; A Allignol; A Murthy; M Wolkewitz; J Beyersmann; E Safran; J Schrenzel; D Pittet; S Harbarth
Journal:  J Hosp Infect       Date:  2011-04-09       Impact factor: 3.926

7.  Incidence densities in a competing events analysis.

Authors:  Nadine Grambauer; Martin Schumacher; Markus Dettenkofer; Jan Beyersmann
Journal:  Am J Epidemiol       Date:  2010-09-03       Impact factor: 4.897

8.  Use of multistate models to assess prolongation of intensive care unit stay due to nosocomial infection.

Authors:  J Beyersmann; P Gastmeier; H Grundmann; S Bärwolff; C Geffers; M Behnke; H Rüden; M Schumacher
Journal:  Infect Control Hosp Epidemiol       Date:  2006-04-20       Impact factor: 3.254

9.  A qualifier Q for the survival function to describe the prevalence of a transient condition.

Authors:  M S Pepe; G Longton; M Thornquist
Journal:  Stat Med       Date:  1991-03       Impact factor: 2.373

10.  Estimating stage occupation probabilities in non-Markov models.

Authors:  Nina Gunnes; Ornulf Borgan; Odd O Aalen
Journal:  Lifetime Data Anal       Date:  2007-03-02       Impact factor: 1.429

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  5 in total

1.  Landmark estimation of transition probabilities in non-Markov multi-state models with covariates.

Authors:  Rune Hoff; Hein Putter; Ingrid Sivesind Mehlum; Jon Michael Gran
Journal:  Lifetime Data Anal       Date:  2019-04-17       Impact factor: 1.588

2.  Bootstrapping complex time-to-event data without individual patient data, with a view toward time-dependent exposures.

Authors:  Tobias Bluhmki; Hein Putter; Arthur Allignol; Jan Beyersmann
Journal:  Stat Med       Date:  2019-06-04       Impact factor: 2.373

3.  A hybrid landmark Aalen-Johansen estimator for transition probabilities in partially non-Markov multi-state models.

Authors:  Niklas Maltzahn; Rune Hoff; Odd O Aalen; Ingrid S Mehlum; Hein Putter; Jon Michael Gran
Journal:  Lifetime Data Anal       Date:  2021-09-30       Impact factor: 1.588

4.  Causal inference in multi-state models-sickness absence and work for 1145 participants after work rehabilitation.

Authors:  Jon Michael Gran; Stein Atle Lie; Irene Øyeflaten; Ørnulf Borgan; Odd O Aalen
Journal:  BMC Public Health       Date:  2015-10-23       Impact factor: 3.295

Review 5.  Current recommendations on the estimation of transition probabilities in Markov cohort models for use in health care decision-making: a targeted literature review.

Authors:  Elena Olariu; Kevin K Cadwell; Elizabeth Hancock; David Trueman; Helene Chevrou-Severac
Journal:  Clinicoecon Outcomes Res       Date:  2017-09-01
  5 in total

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