A prognostic model for patients with primary extramedullary multiple myeloma

Area of Science:

• Hematology
• Oncology
• Medical Statistics

Background:

• Extramedullary disease (EMD) is a serious manifestation of multiple myeloma (MM).
• Prognosis for patients with EMM remains poor despite advancements in MM therapies.
• There is a critical need for improved prognostic tools for primary EMM.

Purpose of the Study:

• To develop and validate a predictive nomogram model for overall survival (OS) in patients with primary extramedullary multiple myeloma (EMM).
• To identify key clinical and laboratory factors influencing survival outcomes in EMM patients.

Main Methods:

• Retrospective analysis of clinical and laboratory data from 217 primary EMM patients (July 2007-July 2021).
• Prognostic factor selection using univariate and least absolute shrinkage and selection operation (LASSO) Cox regression.
• Nomogram model construction and internal validation using concordance index (C-index), bootstrapping, area under the curve (AUCs), and calibration curves.

Main Results:

• The developed nomogram integrated six prognostic factors: performance status, number of EMM sites, β2-microglobulin, lactate dehydrogenase, monocyte-lymphocyte ratio, and prothrombin time.
• The nomogram demonstrated robust discrimination with a C-index of 0.775 (internal validation: 0.756) and excellent predictive performance for 1-, 3-, and 5-year OS (AUCs: 0.814, 0.744, 0.832).
• Patients stratified into high-risk and low-risk groups by the nomogram showed significantly different 5-year OS rates (23.3% vs. 73.0%, p < 0.001).

Conclusions:

• The nomogram model effectively predicts individual survival outcomes for patients with primary EMM.
• This tool can aid clinicians in better stratifying patients and guiding personalized treatment decisions.
• The model's robust performance suggests its utility in clinical practice for managing EMM.