Literature DB >> 11318159

The graft versus leukemia effect after bone marrow transplantation: a case study using structural nested failure time models.

N Keiding1, M Filiberti, S Esbjerg, J M Robins, N Jacobsen.   

Abstract

Over the last decade, J. M. Robins has developed a set of tools for assessing, from observational data, the causal effects of a time-dependent treatment or exposure in the presence of time-dependent covariates that may be simultaneously confounders and intermediate variables. This report concerns a case study of the application of one these techniques, G-estimation using structural nested failure time models, to the problem of assessing the effect of graft versus host disease on leukemia relapse after bone marrow transplantation.

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Year:  1999        PMID: 11318159     DOI: 10.1111/j.0006-341x.1999.00023.x

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


  11 in total

1.  Healthy worker survivor bias in the Colorado Plateau uranium miners cohort.

Authors:  Alexander P Keil; David B Richardson; Melissa A Troester
Journal:  Am J Epidemiol       Date:  2015-04-01       Impact factor: 4.897

2.  MIMICKING COUNTERFACTUAL OUTCOMES TO ESTIMATE CAUSAL EFFECTS.

Authors:  Judith J Lok
Journal:  Ann Stat       Date:  2017-05-16       Impact factor: 4.028

3.  The parametric g-formula for time-to-event data: intuition and a worked example.

Authors:  Alexander P Keil; Jessie K Edwards; David B Richardson; Ashley I Naimi; Stephen R Cole
Journal:  Epidemiology       Date:  2014-11       Impact factor: 4.822

4.  Estimating the effect of cumulative occupational asbestos exposure on time to lung cancer mortality: using structural nested failure-time models to account for healthy-worker survivor bias.

Authors:  Ashley I Naimi; Stephen R Cole; Michael G Hudgens; David B Richardson
Journal:  Epidemiology       Date:  2014-03       Impact factor: 4.822

5.  Impact of time to start treatment following infection with application to initiating HAART in HIV-positive patients.

Authors:  Judith J Lok; Victor DeGruttola
Journal:  Biometrics       Date:  2012-02-21       Impact factor: 2.571

6.  Estimating the average treatment effect on survival based on observational data and using partly conditional modeling.

Authors:  Qi Gong; Douglas E Schaubel
Journal:  Biometrics       Date:  2016-05-18       Impact factor: 2.571

7.  Adjusting for time-varying confounding in the subdistribution analysis of a competing risk.

Authors:  Maarten Bekaert; Stijn Vansteelandt; Karl Mertens
Journal:  Lifetime Data Anal       Date:  2009-10-10       Impact factor: 1.588

8.  Accounting for Time-Varying Confounding in the Relationship Between Obesity and Coronary Heart Disease: Analysis With G-Estimation: The ARIC Study.

Authors:  Maryam Shakiba; Mohammad Ali Mansournia; Arsalan Salari; Hamid Soori; Nasrin Mansournia; Jay S Kaufman
Journal:  Am J Epidemiol       Date:  2018-06-01       Impact factor: 4.897

9.  Survival Benefit of Lung Transplantation in the Modern Era of Lung Allocation.

Authors:  David M Vock; Michael T Durheim; Wayne M Tsuang; C Ashley Finlen Copeland; Anastasios A Tsiatis; Marie Davidian; Megan L Neely; David J Lederer; Scott M Palmer
Journal:  Ann Am Thorac Soc       Date:  2017-02

10.  Years of Life Lost due to exposure: Causal concepts and empirical shortcomings.

Authors:  P Morfeld
Journal:  Epidemiol Perspect Innov       Date:  2004-12-16
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