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Updated: Jul 2, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Quantitative risk factor analysis of prior disease condition and socioeconomic status with the multiple myeloma
Suein Choi1,2, Eunjin Kim1,2, Jinhee Jung1,2
1Department of Pharmacology, College of Medicine, The Catholic University of Korea, 222 Banpodaero, Seochogu, Seoul, Republic of Korea.
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 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 nationwide database from South Korea. According to multivariate logistic regression analysis, eight prior disease conditions and SES before diagnosis were shown to be predictors of MM development and selected for score development. Total prediction scores were categorized into four groups: patients without any risk (≤ 0) intermediate-1 (0.5-9), intermediate-2 (9-14), and high risk (> 14). The odds ratios for developing MM in the intermediate-1, intermediate-2, and high-risk groups were 1.29, 3.07, and 4.62, respectively. The association of prior disease conditions and SES with MM diagnosis were demonstrated and the simple scoring system to predict the MM risk was developed. This scoring system is also provided by web-based application and could be a useful tool to support clinicians in identifying potential candidates for MM screening.
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