Clinical Feature and Predictive Model for Transplanted Patients With Functional High-Risk Multiple Myeloma

Abstract

Objective

A subset of patients with multiple myeloma (MM) experience early relapse despite the absence of any high-risk features at diagnosis, defined as functional high-risk (FHR) MM with inferior prognosis. This study compared FHR and standard risk (SR) MM cohorts to investigate clinical risk factors and establish a validated prognostic model for early prediction of FHR in patients with MM that were transplanted.

Methods

A retrospective cohort study was conducted to analyze the clinical data of patients with MM. Univariate and multivariate analyses were performed to identify independent risk factors for FHR-MM. A prognostic nomogram was developed through logistic regression analysis and internally validated.

Results

The study cohort comprised 357 MM patients. Univariate and multivariate analyses identified the following as independent predictors of FHR-MM: lactate dehydrogenase (LDH) ≥190 U/L, PET-CT SUVmax ≥7.5 at baseline, post-induction ≥80% reduction in PET-CT SUVmax, platelet count <80×10⁹/L, ferritin ≥650 µg/L, Pattern B of M-protein decline, and achieved complete remission (CR) after autologous stem cell transplantation (ASCT). The derived predictive model demonstrated area under the curve (AUC) scores of 0.753 (95% CI 0.666–0.840) for the training set and 0.857 (95% CI 0.759–0.954) for the validation set.

Conclusion

This study established a predictive nomogram for transplanted patients with FHR-MM that demonstrates robust discriminative capacity through internal validation.