Survival analysis of thalassemia major patients using Cox, Gompertz proportional hazard and Weibull accelerated failure time models

Authors

  • Akbar Biglarian Department of Biostatistics, Social Determinants of Health Research Center, Universi-ty of Social Welfare and Rehabilitation Sciences, Tehran, Iran.
  • Azita Azarkeivan Pediatric Hematology Oncology, Iranian Blood Transfusion Organization (IBTO) – High Institute for Research and Education in Transfusion Medicine, Thalassemia Clinic, Tehran, Iran.
  • Enayatollah Bakhshi Department of Biostatistics, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran.
  • Reza Ali Akbari Khoei Department of Biostatistics, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran.
Abstract:

Background: Thalassemia major (TM) is a severe disease and the most common anemia worldwide. The survival time of the disease and its risk factors are of importance for physicians. The present study was conducted to apply the semi-parametric Cox PH model and use parametric proportional hazards (PH) and accelerated failure time (AFT) models to identify the risk factors related to survival of TM patients.    Methods: The data of this historical cohort study (296 patients with TM) were collected during 1994 and 2013 in Zafar Clinic in Tehran. Gompertz PH and Weibull AFT models were used for survival analysis (SA) of these patients. Data analysis was performed using R3.2.2 software.    Results: 153 (51.7%) of patients were female; the mean (±SD) age of the patients was 29.11 (±0.47) years. One-year survival rate for males and females was 0.963±0.007 and 0.973±0.013, respectively; and 3-year survival rate for males and females was 0.711±0.057 and 0.733±0.114, respectively. In the Gompertz model, birthplace and age at onset of the disease were significant factors (p= 0.035, and p= 0.005) in survival time. Also, in the Weibull model, birth place and age at onset of the disease were significant factors (p= 0.013, and p= 0.008) in survival time.  The Akaike Information Criterion (AIC) for Weibull model was 158.51, which was lower than other parametric models.    Conclusion: According to the results, the Weibull AFT model was found to be a better model for identifying the risk factors related to survival of patients with TM disease. Informing parents, especially mothers and paying attention to blood screening for early diagnosis may increase the survival rate of patients.    

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

A Comparison between Accelerated Failure-time and Cox Proportional Hazard Models in Analyzing the Survival of Gastric Cancer Patients.

BACKGROUND Gastric cancer is the one of the most prevalent reason of cancer-related death in the world. Survival of patients after surgery involves identifying risk factors. There are various models to detect the effect of risk factors on patients' survival. The present study aims at evaluating these models. METHODS Data from 330 gastric cancer patients diagnosed at the Iran cancer institute ...

full text

a comparison between accelerated failure-time and cox pro-portional hazard models in analyzing the survival of gastric cancer patients

background : gastric cancer is the one of the most prevalent reason of cancer-related death in the world. survival of patients after surgery involves identifying risk factors. there are various models to detect the effect of risk factors on patients’ survival. the present study aims at evaluating these models. methods : data from 330 gastric cancer patients diagnosed at the iran cancer institut...

full text

Prognostic factors of survival time after hematopoietic stem cell transplant in acute lymphoblastic leukemia patients: Cox proportional hazard versus accelerated failure time models

BACKGROUND The aim of this study is to evaluate the prognostic factors of overall survival (OS) after haematopoietic stem cell transplant (HSCT) in acute lymphoblastic leukaemia (ALL) patients using accelerated failure time (AFT), Cox proportional hazard (PH), and Cox time-varying coefficient models. METHODS 206 patients were enrolled after HSCH in Shariati Hospital between 1993 and 2007. The...

full text

The evaluation of Cox and Weibull proportional hazards models and their applications to identify factors influencing survival time in acute leukem

Introduction: The most important models used in analysis of survival data is proportional hazards models. Applying this model requires establishment of the relevance proportional hazards assumption, otherwise it world lead to incorrect inference. This study aims to evaluate Cox and Weibull models which are used in identification of effective factors on survival time in acute leukemia. Me...

full text

Bayesian Analysis for Step-Stress Accelerated Life Testing using Weibull Proportional Hazard Model

In this paper, we present a Bayesian analysis for the Weibull proportional hazard (PH) model used in step-stress accelerated life testings. The key mathematical and graphical difference between the Weibull cumulative exposure (CE) model and the PH model is illustrated. Compared with the CE model, the PH model provides more flexibility in fitting step-stress testing data and has the attractive m...

full text

estimation of the genetic parameters for survival rate in lori-bakhtiari lambs using linear and weibull proportional hazard models

the data set employed in this study was comprised of a number of 6,800 records of lamb’s longevity and their survival rate, collected from 1989 through 2009, from the lori-bakhtiari experimental flock at the shooli station in shahrekord, iran. the data were analyzed using linear models and proportional hazard models with weibull function. these models included fixed factors and direct additive ...

full text

My Resources

Save resource for easier access later

Save to my library Already added to my library

{@ msg_add @}


Journal title

volume 31  issue 1

pages  568- 571

publication date 2017-01

By following a journal you will be notified via email when a new issue of this journal is published.

Keywords

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023