Quantitative Risk Factor Analysis of Prior Disease Condition and Socioeconomic Status with the Multiple Myeloma Development: Nationwide cohort study

Abstract

Abstract Early diagnosis and following management are important determinants of the prognosis of multiple myeloma (MM). However, screening for MM is not routinely performed because it is a rare disease. In this study, we evaluated the association of prior disease condition and socioeconomic status (SES) with MM diagnosis and developed a simple predictive model that can identify patients at high risk of developing MM who may need screening using a nationwide database from South Korea. According to multivariate logistic regression analysis, seven prior disease conditions (congestive heart failure, autoimmune disease, chronic pulmonary disease, hepatic disease, renal disease, any malignancy, and metastatic solid tumor) and poor SES before diagnosis were shown as possible risk factors of MM development. Based on the result, the scoring model was developed to predict the risk of MM development, and total scores were categorized into four groups: no-risk (≤0) intermediate-1 (0.5−6), intermediate-2 (6.5−14), and high-risk (>14). The odds ratios for developing MM in the intermediate-1, intermediate-2, and high-risk groups were 1.31, 2.68, and 4.96 respectively when compared to the no-risk group. This scoring system is also provided by a web-based application and could be a useful tool to support clinicians in identifying potential candidates for MM screening.