title: Hypertabastic survival model.
abstract: A new two-parameter probability distribution called hypertabastic is introduced to model the survival or time-to-event data. A simulation study was carried out to evaluate the performance of the hypertabastic distribution in comparison with popular distributions. We then demonstrate the application of the hypertabastic survival model by applying it to data from two motivating studies. The first one demonstrates the proportional hazards version of the model by applying it to a data set from multiple myeloma study. The second one demonstrates an accelerated failure time version of the model by applying it to data from a randomized study of glioma patients who underwent radiotherapy treatment with and without radiosensitizer misonidazole. Based on the results from the simulation study and two applications, the proposed model shows to be a flexible and promising alternative to practitioners in this field.
authors.affiliation: Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, AR, USA. mtabatabai@cameron.edu
authors.forename: Mohammad A
authors.initials: MA
authors.lastname: Tabatabai
authors.forename: Zoran
authors.initials: Z
authors.lastname: Bursac
authors.forename: David K
authors.initials: DK
authors.lastname: Williams
authors.forename: Karan P
authors.initials: KP
authors.lastname: Singh
mesh_terms: D001932:Brain Neoplasms / Q000401:mortality*; D003198:Computer Simulation; D005910:Glioma / Q000401:mortality*; D006801:Humans; D009101:Multiple Myeloma / Q000401:mortality*; D016016:Proportional Hazards Models; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data; D012307:Risk Factors