Development and Validation of a Risk Assessment Model for Early Infection during the First 3 Months in Patients with Newly Diagnosed Multiple Myeloma

PurposeEarly infection was an important cause of mortality in patients with multiple myeloma (MM). The study aimed to assess factors affecting early infection and identify patients with high risk developing infection.

MethodsDuring January 2010 to June 2019, patients with MM were analyzed, retrospectively. The data was divided into training and independent validation cohort. The least absolute shrinkage and selection operator (LASSO) regression model was used for data dimension reduction, feature selection, and model building.

ResultsOf 745 confirmed MM patients, 540 eligible cases were included in final analyses. In total, 165 patients (30.6%) suffered infections, while 110 patients (20.4%) occurred early infections during the first 3 months after diagnosis. Bacteria and the respiratory tract were the most common pathogen and localization of infection, respectively. In training cohort, PS≥2, HGB<100g/L, β2MG≥6.0mg/L and GLB≥80g/L were identified associated with early infections by LASSO regression. Based on the four factors, an early infection risk model of MM (IRMM) was established to define high- and low-risk groups, which showed significantly different rates of infection (35.3% vs. 9.4%,P<0.001, HR=4.381 [95% CI, 2.802-7.221]). IRMM displayed good discrimination (AUC=0.756) and calibration (P=0.94).

ConclusionWe determined risk factors for early infection and established a predictive model to help clinicians identify patients with high-risk infection. It can help clinicians to determine whether to adjust monitoring and treatment strategies, or apply prophylactic interventions to high-risk patients.