A Novel Strategy for Assessing Bone Marrow Plasma Cell Percentage: Development and Internal Validation of a Surrogate...

Area of Science:

• Hematology
• Oncology
• Biochemistry

Background:

• Accurate quantification of clonal plasma cells (PCs) in bone marrow (BM) is crucial for diagnosing and monitoring plasma cell neoplasms (PCNs) like multiple myeloma (MM).
• Current monitoring relies on International Myeloma Working Group (IMWG) criteria, which require invasive bone marrow biopsies (BMBs), associated with patient discomfort and sampling variability.
• There is a need for less invasive methods to assess BM PC percentage.

Purpose of the Study:

• To investigate the potential of routine biochemical biomarkers to predict bone marrow trephine (BMT) plasma cell percentage (PC%) in patients with PCNs.
• To establish a less invasive alternative for quantifying PCs in the bone marrow.

Main Methods:

• A cross-sectional study involving 112 newly diagnosed MM patients at Tygerberg Hospital, South Africa.
• Partial Least Squares Regression (PLS-R) model trained using routine biomarkers including SFLC ratio, paraprotein, hemoglobin (Hb), calcium, creatinine, and albumin.
• Statistical analyses included correlation and regression modeling for model validation.

Main Results:

• PLS-R analysis identified SFLC ratio, paraprotein, Hb, and serum albumin as significant predictors of BMT PC%.
• The predictive model demonstrated moderate power (Q² = 0.410, R²Y = 0.432).
• Bone marrow aspirate (BMA) PC% was a stronger predictor of BMT PC% (R² = 0.489) than flow cytometry PC% (R² = 0.184).

Conclusions:

• This study presents proof of concept for using biochemical markers to predict BMT PC%, offering a less invasive approach for PC quantification in PCNs.
• Standardization of biomarker sampling and measurement is essential for improving predictive model accuracy.
• Future multicenter prospective studies are recommended to enhance clinical applicability.