The semi-parametric Cox proportional hazards (PH) regression model was developed by Sir David Cox (Cox 1972) and is by far the most popular model for survival analysis. The model defines a hazard function, which is the rate of an event occurring at any given time, given the observation is still at risk, as a function of the observed covariates. When data consist of independent and identically d...

background: breast cancer is the most common cancer after lung cancer and the second cause of death. in this study we compared weibull and lognormal cure models with cox regression on the survival of breast cancer. study design: a cohort study. methods: the current study retrospective cohort study was conducted on 140 patients referred to ali ibn abitaleb hospital, rafsanjan southeastern iran f...

background and purpose: leukemia is the most prevalent type of cancer in children and its prognostic factors vary in different geographic locations. the aim of this study was to estimate the 5 years survival rate of children suffering from leukemia in kerman, iran and to investigate the factors which might influence it. materials and methods: this was a cohort study conducted on patients with a...

background: the incidence of restenosis in patients suffering from coronary artery disease after undergoing angioplasty is of paramount importance. accordingly, this study aimed to investigate factors affecting the time of the first incidence of restenosis in patients undergone angioplasty in the city of zanjan, iran.   methods: this retrospective cohort study was conducted on 421 patients who ...

Cox proportional hazards (PH) regression is a well-known model for analyzing survival data and its strengths are widely recognized. Threshold regression (TR) is a relatively new methodology but one that is receiving greater attention and being used successfully by researchers in different fields, including biopharmaceutical statistics. In threshold regression, event times are modeled by a stoch...

cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. in recent decades, artificial neural network model has been increasingly applied to predict survival data. this research was conducted to compare cox regression and artificial neural network models in prediction of kidney transplant survival. the prese...

In prognostic studies for breast cancer patients treated with neoadjuvant chemotherapy (NAC), the ordinary Cox proportional-hazards (PH) model has been often used to identify prognostic factors for disease-free survival (DFS). This model assumes that all patients eventually experience relapse or death. However, a subset of NAC-treated breast cancer patients never experience these events during ...