Abstract
Background: Patients with multiple myeloma (MM) who have a suboptimal response to induction therapy or early relapse are classified as functional high-risk (FHR) patients and have been shown to have a dismal prognosis. The aim of this study was to establish a predictive nomogram for patients with non-transplanted FHR MM. Materials and Methods: The group comprised 215 patients in our center between 1 January 2006 and 1 March 2024. To identify independent risk factors, univariate and multivariate logistic regression analyses were performed, and a nomogram was constructed to predict non-transplant FHR MM. To evaluate the nomogram's predictive accuracy, we utilized bias-corrected AUC, calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC). Results: Multivariate logistic regression demonstrated that younger age at onset, a higher proportion of LDH (more than 220 U/L), pattern A + C of M protein decline patterns, a lower proportion of patients with induction treatment efficacy than VGPR, and those undergoing maintenance therapies were independent risk factors for patients with non-transplanted FHR MM. The AUC scores for the training and internal validation groups were 0.940 (95% CI 0.893-0.986) and 0.978 (95% CI 0.930-1.000). DCA and CIC curves were utilized to further verify the clinical efficacy of the nomogram. Conclusions: We developed a nomogram that enables early prediction of non-transplant FHR MM patients. Younger age at onset, LDH ≥ 220 U/L, an A + C pattern of M-protein decline, and induction therapy efficacy not reaching VGPR are more likely to be FHR MM patients. Patients who do not undergo maintenance therapy are prone to early progression or relapse.