Optimal cut-off values and diagnostic significance of clinical laboratory indicators in newly diagnosed multiple myeloma

Abstract

Abstract Objective This study aims to identify clinical laboratory parameters for the diagnosis of newly diagnosed multiple myeloma (NDMM), establish optimal cutoffs for early screening, and develop a diagnostic model for precise diagnosis. Methods The study conducted a retrospective analysis of 279 NDMM patients and 553 healthy subjects at Zhejiang Province People’s Hospital between January 2008 and June 2023. Multifactor LR was employed to explore clinical laboratory indicators with diagnostic value for NDMM, determine optimal cutoff values and contract a diagnostic model. The diagnostic efficacy and clinical utility were evaluated using receiver operating characteristic curves (ROC), sensitivity, specificity, and other indicators. Results Multifactor analysis revealed that hemoglobin (Hb), albumin (Alb), and platelet distribution width (PDW) were significant diagnostic factors for NDMM. Optimal cutoff values for Hb, Alb, and PDW in MM diagnosis were determined, and the results showed a significant increase in the probability of NDMM diagnosis when Alb was below 39.3 g/L, Hb was below 11.6 g/dL, and PDW was below 14.1 fL. The diagnostic model constructed from the development cohort demonstrated a high area under the ROC curve of 0.960 (95% CI 0.942–0.978) and exhibited good sensitivity (0.860), specificity (0.957). The area under the curve (AUC) value of the diagnostic model in the external validation cohort was 0.979, confirming its good diagnostic efficacy and generalization. Conclusions The optimal cutoff values for Hb, Alb, and PDW and the diagnostic model designed in the study provided good accuracy and sensitivity for the initial screening and diagnosis of NDMM.

Keywords

• Newly diagnosed multiple myeloma
• Early diagnosis
• Logistic regression
• Hemoglobin
• Optimal cut-off value
• Diagnostic model