Literature DB >> 28725104

Analysis of Dependently Truncated Data in Cox Framework.

Yang Liu1, Ji Li2, Xu Zhang3.   

Abstract

Truncation is a known feature of bone marrow transplant (BMT) registry data, for which the survival time of a leukemia patient is left truncated by the waiting time to transplant. It was recently noted that a longer waiting time was linked to poorer survival. A straightforward solution is a Cox model on the survival time with the waiting time as both truncation variable and covariate. The Cox model should also include other recognized risk factors as covariates. In this paper we focus on estimating the distribution function of waiting time and the probability of selection under the aforementioned Cox model.

Entities:  

Keywords:  Cox model; Dependent truncation; inverse probability weighting

Year:  2017        PMID: 28725104      PMCID: PMC5513481          DOI: 10.1080/03610918.2017.1322699

Source DB:  PubMed          Journal:  Commun Stat Simul Comput        ISSN: 0361-0918            Impact factor:   1.118


  4 in total

1.  Survival curve estimation with dependent left truncated data using Cox's model.

Authors:  Todd Mackenzie
Journal:  Int J Biostat       Date:  2012-10-19       Impact factor: 0.968

2.  A proportional hazards model for truncated AIDS data.

Authors:  D M Finkelstein; D F Moore; D A Schoenfeld
Journal:  Biometrics       Date:  1993-09       Impact factor: 2.571

3.  Bone marrow transplants from HLA-identical siblings as compared with chemotherapy for children with acute lymphoblastic leukemia in a second remission.

Authors:  A J Barrett; M M Horowitz; B H Pollock; M J Zhang; M M Bortin; G R Buchanan; B M Camitta; J Ochs; J Graham-Pole; P A Rowlings
Journal:  N Engl J Med       Date:  1994-11-10       Impact factor: 91.245

4.  Eligibility for allogeneic transplantation in very high risk childhood acute lymphoblastic leukemia: the impact of the waiting time.

Authors:  Adriana Balduzzi; Paola De Lorenzo; André Schrauder; Valentino Conter; Cornelio Uderzo; Christina Peters; Thomas Klingebiel; Jan Stary; Maria S Felice; Edina Magyarosy; Martin Schrappe; Giorgio Dini; Helmut Gadner; Maria Grazia Valsecchi
Journal:  Haematologica       Date:  2008-04-15       Impact factor: 9.941

  4 in total
  1 in total

1.  Conditional Independence Test of Failure and Truncation Times: Essential Tool for Method Selection.

Authors:  Jing Ning; Daewoo Pak; Hong Zhu; Jing Qin
Journal:  Comput Stat Data Anal       Date:  2021-11-19       Impact factor: 1.681

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.