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Updated: Sep 8, 2025
Establishment of a Human Multiple Myeloma Xenograft Model in the Chicken to Study Tumor Growth, Invasion and Angiogenesis
Published on: May 1, 2015
Clinical Feature and Predictive Model for Transplanted Patients with Functional High-Risk Multiple Myeloma
Tongyong Yu1, Meilan Chen1, Beihui Huang1
1Department of Hematology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China.
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.
