Supplementary Material for: Risk Factors and Outcomes of Stem Cell Mobilization Failure in Multiple Myeloma Patients

<b><i>Introduction:</i></b> Autologous hematopoietic stem cell transplantation (ASCT) is a well-established treatment for patients with multiple myeloma (MM), and adequate stem cell collection must be assured before ASCT. However, prediction of poor mobilizers (PMs) is still difficult despite several risk factors for mobilization failure having been identified. <b><i>Methods:</i></b> We retrospectively analyzed MM patients at Taipei Veterans General Hospital in Taiwan who underwent stem cell collection between October 2006 and August 2020. A CD34⁺ cell collection of &lt;1 × 10⁶ cells/kg was defined as a mobilization failure. The primary endpoint was mobilization failure. The secondary endpoint was overall survival (OS). Odds ratios (ORs) and 95% confidence intervals (CIs) for mobilization failure were calculated using a logistic regression model. The cumulative incidence of mortality was estimated using the Kaplan-Meier method. <b><i>Results:</i></b> In the multivariate analysis, absolute monocyte count &lt;500/µL (adjusted OR 10.75, 95% CI: 1.82–63.57, <i>p</i> = 0.009), platelet count &lt;150,000/µL (adjusted OR 12.49, 95% CI: 2.65–58.89, <i>p</i> = 0.001) before mobilization, and time interval from diagnosis to stem cell harvest ≥180 days (adjusted OR 7.69, 95% CI: 1.61–36.87, <i>p</i> = 0.011) were risk factors for PMs. PM patients had poorer OS compared to patients with successful stem cell collection in the univariate analysis (log-rank test <i>p</i> = 0.027). The predicted probability of PMs was estimated by the multiple logistic regression model with a sensitivity of 84.6% and a specificity of 84.0%. <b><i>Conclusion:</i></b> Absolute monocyte count &lt;500/µL, platelet count &lt;150,000/µL, and treatment duration more than 180 days before stem cell mobilization are risk factors for unsuccessful stem cell collection. Our prediction models have high sensitivity and specificity for mobilization failure prediction and allow for early interventions for possible PMs.