A Mixture Cure Model for Interval Censorship with a Change Point based on Age Threshold on Hodgkin Lymphoma Patients after Stem Cell Transplantation A Cure Model with Change Point for Hodgkin Lymphoma Patients
Archives of Advances in Biosciences,
Vol. 12 No. 4 (2021),
12 October 2021
,
Page 35-42
https://doi.org/10.22037/aab.v12i4.36350
Abstract
Abstract
Introduction: Hodgkin lymphoma (HL) is one of the best curable cancers. Many researches have validated the benefit of hematopoietic stem cell transplant (HSCT) for patients with relapsed or primary resistant HL. This analysis aimed to identify an effective change point in patients' age, the cure fraction before and after the change point, and significant prognostic factors on the cure fraction before and after the change point for these patients after HSCT in Iran.
Materials and Methods: In this retrospective cohort study, there were 156 patients with HL who underwent HSCT from 2007 to 2014 with 18 months of follow up in Tehran, Iran. The survival time was set as the time interval between transplantation and the recurrence of HL. Also, the change point and the cure fraction before and after the change point were estimated using the Bayesian estimation method and log-normal distribution.
Results: The estimated cure fraction was 79.2% for all patients. In susceptible cases, the mean survival time was 999 days (2.7 years). Also, the three and five-year survival rates were 82.1% and 80.0%, respectively. The effective change point in the age at transplantation of patients was 35 years, and the cure fraction before the change point was 84.5 % and after the change point was 60.6%.
Conclusion: The study concluded that the age of 35 years is a significant change point in the age at transplantation. If individuals underwent HSCT with HL before the age of 35, they have a higher survival rate (recurrent of HL) than those underwent HSCT after 35.
Keywords: Hodgkin Lymphoma, Mixture Cure Model, Change Point, Interval Censorship,
Bayesian Method
- Hodgkin Lymphoma, Mixture Cure Model, Change Point, Interval Censorship, Bayesian Method
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