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A Multivariable Prediction Model for Early Mortality in Multiple Myeloma Patients With Renal Impairment
Menghan Liu1, Yuan Jian1, Huixing Zhou1
1Department of Hematology, Myeloma Research Center of Beijing, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Abstract:
Despite therapeutic advances, early mortality remains a significant challenge in multiple myeloma (MM) patients with renal impairment (RI), with no validated prognostic models currently available for this high-risk subgroup. This multicenter, retrospective study aimed to develop and validate a practical nomogram for predicting early death (< 12 months) using readily accessible clinical parameters. We analyzed data from 285 newly diagnosed MM patients with RI treated between 2007 and 2020, divided into training (n = 222) and validation (n = 63) cohorts. Multivariate analysis identified five independent predictors of early mortality: age > 55 years (OR 3.48, 95% CI 1.10-11.01), serum calcium ≥ 2.5 mmol/L (OR 3.29, 95% CI 1.30-8.29), bone marrow plasma cell percentage ≥ 40% (OR 2.90, 95% CI 1.24-6.77), renal response less than partial response (OR 0.27, 95% CI 0.11-0.65), and hematologic response less than complete response (OR 20.93, 95% CI 4.61-95.10). The developed nomogram demonstrated excellent discrimination (AUC 0.858) and calibration in the training cohort, with consistent performance in validation (AUC 0.747). Risk stratification categorized patients into three distinct prognostic groups with significantly different early mortality rates: Low Risk (1.6%), Mid Risk (13.9%), and High Risk (43.9%). This validated model provides the first practical tool for early mortality risk stratification in MM patients with RI, enabling clinicians to identify high-risk patients who may benefit from more intensive interventions. Further prospective validation is warranted to confirm generalizability.