Assessing the performance of the Iceland screens, treats, or prevents multiple myeloma (iStopMM) model in a multicultural Bronx cohort: implications for monoclonal gammopathy of undetermined significance risk stratification

Abstract

The Iceland Screens, Treats, or Prevents Multiple Myeloma (iStopMM) risk stratification model, developed to predict ≥10% abnormal plasma cells in the bone marrow in monoclonal gammopathy of undetermined significance (MGUS) patients, was developed in a predominantly White and genetically homogeneous Icelandic population, lacking external validation. Our study aimed to externally validate this model in a racially and ethnically diverse Bronx population. The medical records of patients at Montefiore Medical Center (2002–2023) were searched to identify patients with MGUS who had undergone a bone marrow biopsy. For each patient, the iStopMM variables were entered into the iStopMM prediction model, and predicted, and actual plasma cell percentages were recorded. The area under the receiver operating characteristic (AUROC) curve assessed the iStopMM model’s performance in predicting ≥10% plasma cells, and sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Of the initial 663 patients, 190 were included in the final cohort, of whom 52.6% were African-Americans, and 23.2% identified themselves as Hispanic/Latino, remarkably different from the homogenous population of the iStopMM study. The iStopMM predictive model was able to predict greater than or equal to 10% plasma cells on bone marrow biopsy with an AUROC of 0.78 (CI 0.71, 0.85). When set at a 10% threshold for predicting SMM or worse, the iStopMM model had a 93.3% sensitivity, 33.7% specificity, 55.3% PPV, and 85.0% NPV. This AUROC value of 0.778 suggests a reasonable discriminatory performance of the model in our racially and ethnically diverse Bronx population.