Kaplan-Meier and Cox Proportional Hazards Survival Regression Analysis Illustrated with Immune Deficiency Cohort of Patients after Allogeneic Bone Marrow Transplantation
Year: 2013
Type: preprint
Abstract: The number of allogeneic and autologous bone marrow transplants continues to grow worldwide. Nevertheless, Bone marrow transplantation (BMT) has become standard therapy for many patients with leukemia, breast cancer, severe immune deficiency, and other diseases; there are risk factors after transplantations. We have obtained dataset of 65,535 patients have been treated with BMT to study such risk factors. The dataset recorded from 1994 to 2005 in the Statistical Center for International Blood and Marrow Transplant Research (CIBMTR). Since the dataset is large, the primary objective of this paper is to introduce the dataset, which will be analyzed in a series of papers using the finest techniques in survival models. The secondary objective of the series will be review the common methods in survival data analysis applied in such useful dataset and then develop some techniques to be suited in such data. In this paper, we discuss the analysis of significant risk factors of severe immune disease after allogeneic BMTs. First, the survival curves were calculated by the Kaplan-Meier method and then the well known Cox model is discussing, that is because it is found that, that model is suited to be applied in immune deficiency in such subset data. When fitting a Cox model, it is vital to assess the assumption of proportionality.
Source: SSRN Electronic Journal
Authors: Ayman A. Mostafa, Imam Mohammad, Ibn Saud
Institution: Imam Mohammad ibn Saud Islamic University
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W320482183