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Dutta, A.K., Hewett, D.R., Fink, J.L., Grady, J.P. and Zannettino, A.C. (2017) Cutting Edge Genomics Reveal New Insights into Tumour Development, Disease Progression and Therapeutic Impacts in Multiple Myeloma. British Journal of Haematology, 178, 196-208.
https://doi.org/10.1111/bjh.14649

has been cited by the following article:

• TITLE: Parametric and Non-Parametric Analysis of the Survival Times of Patients with Multiple Myeloma Cancer

  AUTHORS: Lohuwa Mamudu, Chris P. Tsokos

  KEYWORDS: Multiple Myeloma Cancer, Three-Parameter Lognormal, Kaplan-Meier, Maximum Likelihood Estimation, Health Science

  JOURNAL NAME: Open Journal of Applied Sciences, Vol.10 No.4, April 14, 2020

  ABSTRACT: Multiple myeloma (MM) is a type of cancer that remains incurable. In the last decade, most research into MM has focused on investigating the improvement in the therapeutic strategy. Our study assesses the survival probability of 48 patients diagnosed with MM based on parametric and non-parametric techniques. We performed parametric survival analysis and found a well-def- ined probability distribution of the survival time to follow three-parameter lognormal. We then estimated the survival probability and compared it with the commonly used non-parametric Kaplan-Meier survival analysis of the survival times. The comparison of the survival probability estimates of the two methods revealed a better survival probability estimate by the parametric method than the Kaplan-Meier. The parametric survival analysis is more robust and efficient because it is based on a well-defined parametric probabilistic distribution, hence preferred over the non-parametric Kaplan-Meier. This study offers therapeutic significance for further enhancement in the treatment strategy of multiple myeloma cancer.