BACKGROUND: Leukemia is a kind of malignancy blood system which leads to death of human beings in a very short period of time.In this paper, the Recliner effective factors on survival time of the acute lymphoblastic leukemia (ALL) patients have been considered to achieve a linear regression model show the relation between the life-time after diagnosis and some explanatory factors.METHODS: In this study, the data of 52 patients died from ALL was used.The designed model contained three variables, hemoglobin, large undifferentiated cell (LUC) and age.
According to the data suggesting, a kind of mixture distribution, we considered a mixture model for survival time.Applying the EM-algorithm, we have found the maximum likelihood estimate of mean survival time and the Bayesian estimate of the mean survival time by Monte Carlo Markov Chain method.FINDINGS: Based on the obtained estimating survival function, we can predict the survival time of the patients and decide about their treatment protocol.CONCLUSION: Cod Liver Oil It is suggested that by conducting larger studies and statistical analysis used in this paper, a correlative can be found between clinical & paraclinical findings and the survival time.
This model can be used in often kinds of diseases for determining the prognosis.KEY WORDS: Maximum likelihood estimation, bayesian estimation, bimodal, leukemia, mixture models, survival mean.