Abstract
Multiple Myeloma (MM) has been and continues to be the subject of many research studies. The main goal is to improve the therapeutic/treatment process of survival of MM patients. Based on the 2012-2016 MM cases and deaths, the number of new cases was 6.9 per 100,000 men and women per year, and the number of deaths was 3.3 per 100,000 men and women per year. It is therefore imperative to research into MM. In the present study, we proposed a data-driven statistical model for the survival time of 48 patients diagnosed with multiple myeloma as a function of 16 attributable risk factors. We identified 9 attributable risk factors out of 16 and one interaction term to be significantly contributing to the survival time. They are Bence Jone protein in urine, blood urea nitrogen (BUN)/serum creatinine, infections, % myeloid cells in peripheral blood, fractures, serum calcium, gender, platelets and age, and white blood cells & total serum protein an interaction term. The proposed model satisfied all the model assumptions, passes the residual analysis test and has very high prediction accuracy. Thus, it passes the goodnessof- fit test and the qualities of a good model. The identified significant attributable risk factors and the interaction has been ranked based on the percent contribution to the survival time. The proposed model was evaluated and compared with other existing models of survival of multiple myeloma. Our model is very accurate and also identifies some new significant risk factors. The study offers an improved strategy for the therapeutic/treatment process of multiple Myeloma Cancer.
Highlights
Multiple Myeloma (MM), known as Kahler disease, myelomatosis, and plasma cell myeloma is a type of cancer that starts from a malignant plasma cell [1]
We have developed and propose a data-driven statistical model that identifies nine significant risk factors and one interaction term, namely Bence Jone protein in urine, blood urea nitrogen (BUN)/serum creatinine, infections, % myeloid cells in peripheral blood, fractures, serum calcium, gender, platelets and age, and white blood cells & total serum protein that contribute to the survival time of patients diagnosed with multiple myeloma
R ) 2 adjusted statistic, the Akaike information criterion (AIC) of model selection, the prediction error sum of squares (PRESS), the root mean square error (RMSE), the variance inflation factor (VIF), the residual analysis, and the prediction accuracy to be of
Summary
Multiple Myeloma (MM), known as Kahler disease, myelomatosis, and plasma cell myeloma is a type of cancer that starts from a malignant plasma cell ( the white blood cell) [1]. The plasma cell produces antibodies as part of the human immune system that helps fight against germs and harmful substances. Myeloma is caused by the plasma cell becoming abnormal called the myeloma cell. The myeloma cell accumulates in the bone marrow, where they crowd out healthy blood cells and may cause damage to the solid part of the bone. Multiple myeloma is caused by the accumulation of the myeloma cells in the bones [2,3,4,5,6,7,8].
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