Literature DB >> 29308097

Methods for Contrasting Gap Time Hazard Functions: Application to Repeat Liver Transplantation.

Xu Shu1, Douglas E Schaubel2.   

Abstract

In studies featuring a sequence of ordered events, gap times between successive events are often of interest. Despite the rich literature in this area, very few methods for comparing gap times have been developed. We propose methods for estimating a hazard ratio connecting the first and second gap times. Specifically, a two-stage procedure is developed based on estimating equations. At the first stage, a proportional hazards model is fitted for the first gap time. Weighted estimating equations are then solved at the second stage to estimate the hazard ratio between the first and second gap times. The proposed estimator has a closed form and, being analogous to a standardized mortality ratio, is easy to interpret. Large sample properties of the proposed estimators are derived, with simulation studies used to evaluate finite sample characteristics. Extension of the approach to accommodate a piecewise constant hazard ratio is considered. The proposed methods are applied to contrast repeat (second) versus primary (first) liver transplants with respect to graft failure, based on national registry data.

Entities:  

Keywords:  Counting processes; Inverse weighting; Organ transplantation; Proportional hazards model; Semiparametric methods; Survival analysis

Year:  2016        PMID: 29308097      PMCID: PMC5754042          DOI: 10.1007/s12561-016-9168-6

Source DB:  PubMed          Journal:  Stat Biosci        ISSN: 1867-1764


  14 in total

1.  Non-parametric estimation of gap time survival functions for ordered multivariate failure time data.

Authors:  Douglas E Schaubel; Jianwen Cai
Journal:  Stat Med       Date:  2004-06-30       Impact factor: 2.373

2.  Semiparametric regression analysis on longitudinal pattern of recurrent gap times.

Authors:  Ying Qing Chen; Mei-Cheng Wang; Yijian Huang
Journal:  Biostatistics       Date:  2004-04       Impact factor: 5.899

3.  A joint frailty model for survival and gap times between recurrent events.

Authors:  Xuelin Huang; Lei Liu
Journal:  Biometrics       Date:  2007-06       Impact factor: 2.571

4.  Conditional GEE for recurrent event gap times.

Authors:  David Y Clement; Robert L Strawderman
Journal:  Biostatistics       Date:  2009-03-18       Impact factor: 5.899

5.  Late orthotopic liver retransplantation: indications and survival.

Authors:  F G Durán; R A Cercadillo; L Santos; A de Diego; J Ferreiroa; E Valdecantos; G Clemente
Journal:  Transplant Proc       Date:  1998-08       Impact factor: 1.066

6.  Smoothing spline ANOVA frailty model for recurrent event data.

Authors:  Pang Du; Yihua Jiang; Yuedong Wang
Journal:  Biometrics       Date:  2011-04-02       Impact factor: 2.571

7.  Long-term survival after retransplantation of the liver.

Authors:  J F Markmann; J S Markowitz; H Yersiz; M Morrisey; D G Farmer; D A Farmer; J Goss; R Ghobrial; S V McDiarmid; R Stribling; P Martin; L I Goldstein; P Seu; C Shackleton; R W Busuttil
Journal:  Ann Surg       Date:  1997-10       Impact factor: 12.969

8.  Hepatitis C infection in patients undergoing liver retransplantation.

Authors:  H R Rosen; P Martin
Journal:  Transplantation       Date:  1998-12-27       Impact factor: 4.939

9.  OPTN/SRTR 2012 Annual Data Report: liver.

Authors:  W R Kim; J M Smith; M A Skeans; D P Schladt; M A Schnitzler; E B Edwards; A M Harper; J L Wainright; J J Snyder; A K Israni; B L Kasiske
Journal:  Am J Transplant       Date:  2014-01       Impact factor: 8.086

10.  Poor survival after liver retransplantation: is hepatitis C to blame?

Authors:  Kymberly D S Watt; Elizabeth R Lyden; Timothy M McCashland
Journal:  Liver Transpl       Date:  2003-10       Impact factor: 5.799

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  1 in total

1.  Statistical Methods in Organ Failure and Transplantation.

Authors:  Douglas E Schaubel
Journal:  Stat Biosci       Date:  2017-11-27
  1 in total

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