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An estimation of the chronic rejection of kidney transplant using an eternal Weibull regression: A historical cohort study

An estimation of the chronic rejection of kidney transplant using an eternal Weibull regression: A historical cohort study

Golestan, B., Hosseini-Moghaddam, S.M., Nafar, M., Rennolls, K. and Mohammad, K. (2009) An estimation of the chronic rejection of kidney transplant using an eternal Weibull regression: A historical cohort study. Archives of Iranian Medicine, 12 (4). pp. 341-346. ISSN 1029-2977 (Print), 1735-3947 (Online)

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Abstract

Background: We estimated the chronic rejection of kidney transplant using an eternal Weibull regression. Methods: In this historical cohort study, we enrolled all patients with chronic renal failure who were admitted to Shahid Labbafinejad medical center (Tehran, Iran) from 1984 to 2003. Using Matlab 7.0, we considered the eternal proportion θ , as a logistic-type function of the covariates and modified the survival function. We estimated the survival function in unmodified and modified forms using Weibull distribution. Results: The chance of chronic rejection was 1.95 times higher among those who received a kidney transplant before 1996. Considering all cases who received renal transplantation after 1984, males had a chance of rejection 20% less than females. Next to the eternity, Weibull model was fitted to patients who received renal transplantation after 1996. Treatment protocol was changed after 1996 expecting fewer chronic rejections; thereafter, the eternal proportion was estimated to be 0.81. This seems quite considerable as a percentage of non-failure cases. Conclusion: Providing a non-zero eternal proportion, the modified model would be superior over the unmodified mode.

Item Type: Article
Uncontrolled Keywords: cohort studies, graft rejection, kidney transplantation, regression analysis
Subjects: R Medicine > R Medicine (General)
R Medicine > RB Pathology
R Medicine > RC Internal medicine
R Medicine > RZ Other systems of medicine
Faculty / Department / Research Group: Faculty of Architecture, Computing & Humanities
Related URLs:
Last Modified: 14 Oct 2016 09:19
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/7848

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