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Keywords: Health Science, Multiple Myeloma Cancer, Cancer Therapeutic, Cox Model, Statistical Model, Survival Analysis, Probability Estimation
To further improve the therapeutic/treatment strategy for the incurable cancer disease multiple myeloma (MM), this study focus on comparing the survival analysis of a statistical nonlinear regression model with the commonly used Cox proportional hazard model for a given set of significantly identified attributable risk factors or covariates of the survival times of 48 patients diagnosed with MM. First, we obtained very high quality and accurate predictive statistical nonlinear regression model and Cox-PH model for the survival times of the MM patients satisfying all the required model assumptions. We compared the survival function of the two high profile models’ ability to effectively and efficiently estimate the proportion of survival times. We found the nonlinear regression model gives a better estimation of the survival time than the Cox-PH model. Hence, our procedure of using statistical models for survival analysis is more robust and preferable, given that the underlying probability distribution is parametric.