Batuhan SUBASI, Nahide EKICI GUNAY, Derya KOCER, Esra YILDIZHAN
International Journal of Medical Biochemistry - 2026;9(2):93-102
Objectives: Multiple myeloma (MM) is characterized by clonal plasma cell proliferation and significant systemic impacts. This study aimed to evaluate the relationship between routine hemogram and biochemical parameters and disease severity markers (M-protein and beta-2 microglobulin [beta-2M]) to identify accessible clinical indicators of tumor load at the time of diagnosis. Methods: In this retrospective cross-sectional study, newly diagnosed, treatment-naive MM patients and healthy controls were analyzed. Statistical significance was set at a threshold (p<0.00125) using Bonferroni correction to prevent Type I errors. Multivariable logistic regression was performed to identify independent predictors of high M-protein load (>=3g/dL), and ROC analysis was used to determine the diagnostic performance of significant parameters. Results: MM patients exhibited significantly lower WBC, RBC, HCT, and PLT counts, and higher BUN and CRP levels compared to controls (p<0.001). beta-2M showed significant correlations with several routine parameters; however, partial correlation and multivariable regression revealed that these associations were entirely dependent on renal function. Conversely, multivariable logistic regression identified RBC count (OR=0.383, p=0.026), eGFR, and age as significant independent predictors of high M-protein load. Notably, each 1x10?/muL decline in RBC count was associated with a 161% increase in the risk of high disease severity. ROC analysis established an optimal RBC cut-off value of 3.73x10?/muL (AUC: 0.695, sensitivity: 64.1%, specificity: 69.6%) for predicting high tumor load. Conclusion: Routine laboratory data, particularly RBC count, serve as powerful indicators of MM severity at the time of initial diagnosis. Unlike beta-2M, which is heavily influenced by renal status, RBC count is an independent predictor of monoclonal protein load. A baseline RBC level below 3.73x10?/muL should alert clinicians to a potentially high tumor load, facilitating rapid triage and treatment prioritization.
