A Novel Prognostic System Based on Circulating Tumor Cells for Newly Diagnosed Multiple Myeloma
Authors: Ntanasis-Stathopoulos Ioannis , Kostopoulos Ioannis V , Malandrakis Panagiotis , Rousakis Pantelis , Panteli Chrysanthi , Eleutherakis-Papaiakovou Evangelos , Spiliopoulou Vasiliki , Dimitrakopoulou Georgia , Fotiou Despina , Migkou Magdalini , Theodorakakou Foteini , Kanellias Nikolaos , Gavriatopoulou Maria , Kastritis Efstathios , Dimopoulos Meletios A. , Tsitsilonis Ourania , Terpos Evangelos 
Published: December 2024

Background

The assessment of circulating tumor cells (CTCs) has been proposed as a new biomarker with independent prognostic significance for newly diagnosed Multiple Myeloma (NDMM) patients. We recently identified a CTC threshold of 0.02% as an optimal prognostic cutoff for NDMM patients, independent of other established prognostic factors. In this study, our goal was to develop a novel CTC-based prognostic algorithm to enhance existing stratification systems.

Methods

The study included 535 NDMM patients, with a median follow-up period of 45 months (range 12-71 months). Comprehensive clinical data were available for all patients, including demographics, cytogenetics, heavy/light chain restriction, bone marrow (BM) infiltration, white blood cell count, platelet count, and levels of serum albumin, creatinine, calcium, LDH, and β2-microglobulin. Additionally, the Revised International Staging System (R-ISS) stage and phenotypic classification system (PCS) were determined for each patient. The PCS was estimated using the relevant frequencies of normal, clonal, and total BM plasma cells assessed by flow cytometry, based on the available online MGUS-like calculator.

Results

The study utilized the CTC cutoff in subgroup analyses of progression-free survival (PFS) and overall survival (OS) across various parameters, revealing a significantly lower risk of progression and/or death for patients (pts) with CTCs &lt; 0.02% in all cases. This impact was observed in the PFS of both transplant-eligible (TE) and transplant-ineligible (TI) patients (HR: 0.38, 95% CI: 0.22-0.59 for TE, p&lt;0.001; HR: 0.43, 95% CI: 0.31-0.64, p&lt;0.0001 for TI). However, the effect on OS was mainly evident in TI patients (HR: 0.4, 95% CI: 0.22-0.71, p=0.004), likely due to the low number of deaths during the monitoring period. The lack of interaction between CTCs, R-ISS, and PCS allowed for the integration of all three systems to refine patient stratification.

Patients were assigned one point per increased risk status in each system (1-3 points for R-ISS; 1-3 points for PCS; 1-2 points for CTCs), resulting in a final score ranging from 3 to 8 points. The distribution of scores was as follows: 3.5% of patients had a score of 3, 17.4% scored 4, 22.3% scored 5, 22.1% scored 6, 20.3% scored 7, and 14.4% scored 8. PFS and OS deteriorated progressively with each increasing score. The optimal model efficacy was achieved by categorizing patients into three groups: group A (score 3-5), group B (score 6-7), and group C (score 8). The median PFS was not reached for group A, was 42 months for group B, and 25 months for group C (p&lt;0.0001). OS was not reached in any group (p&lt;0.001), demonstrating superior stratification efficacy (c-index 0.65) compared to R-ISS, PCS, and CTC discrimination individually or in any dual combination.

Conclusion

Elevated CTC numbers worsen the prognostic status in newly diagnosed Multiple Myeloma (NDMM) patients, regardless of other clinical features. Incorporating the 0.02% CTC cutoff with the R-ISS and PCS creates a new stratification system with enhanced predictive and prognostic value, allowing for better definition of patient subgroups that may benefit from different therapeutic strategies.