Hypercoagulability Biomarkers in a New Score Linked to Treatment Resistance for Multiple Myeloma Patients. the Roadmap-MM Study

Background:

Research has focused on the implications of platelet, endothelial cell and blood coagulation activation in the risk of venous thromboembolism (VTE) in patients with multiple myeloma (MM). The reciprocal interaction between cancer cells and blood coagulation renders biomarkers of hypercoagulability as potential candidates for the evaluation of resistance to treatment in patients with newly diagnosed multiple myeloma (NDMM).

Aims:

The aim of the current analysis of the ROADMAP-MM study was to identify among a large number of hypercoagulability biomarkers in NDMM patients the most clinically relevant for the inclusion in treatment-resistance assessment tools.

Methods: The ROADMAP-MM-CAT study (NCT03405571) was an investigator initiated, prospective, non-interventional trial. Newly diagnosed, treatment naïve symptomatic patients with multiple myeloma (based on 2014 IMWG Criteria) (n=144) were enrolled prior to treatment initiation and response to treatment was assessed at 3 months. Selected biomarkers , such as STA-Procoag-PPL®, factor VIIa factor V, antithrombin, fibrin monomers, thrombomodulin, free TFPI, D-Dimers, P-selectin, heparanase and thrombin generation (Calibrated Automated Thrombogram® and PPP-Reagent®) were measured.

Results:

At inclusion no patient had received any anti-myeloma treatment or thromboprophylaxis. Median age was 66.0±11.6 (36-86) years and 53% of the population was male. Regarding ISS disease stage: 32% were ISS-I, 23% ISS-II and 45% ISS-III. High risk cytogenetics [defined as presence of any of t(4;14), t(14;16) or del17p by FISH] were detected in 27% of the patients. In 32% of patients the treatment was immunomodulatory drug (IMiD) (90% lenalidomide and 10% thalidomide) and in 64% proteasome inhibitor (PI) based whereas 4% of patients received other regimens. Before any treatment administration - patients showed significantly increased levels of TFa, FVIIa, D-Dimers and FM and significantly shorter Procoag-PPL® as compared to the group of healthy individuals. Levels of P-selectin and TM were significantly lower in patients as compared to healthy individuals. Overall, thrombin generation was attenuated in patients compared to healthy individuals. Lag-time and ttPeak were significantly increased and Peak, MRI and ETP were significantly lower as compared to the group of healthy individuals

At 3 months from treatment initiation, 23% (n=33) of the patients showed poor response or resistance to the anti-myeloma treatment. Among them, 7.6% (n=11) had progressive disease, 9.7% (n=14) had stable disease and 5.7% (n=8) had minor response. Among responders (n=111) 42.3 % (n=61) achieved PR and 34.7% (n=50) had VGPR.

Multivariate logistic regression analysis for demonstrated that Procoag-PPL^®≥41.7 versus <41.7 sec (OR=4.06, 95% CI: 1.59-10.38, p=0.003), D-Dimers ≥1.44 versus <1.44 μg/ml (OR=2.52, 95% CI: 1.06-6.01, p=0.037) and thrombin peak ≥181.66 versus <181.66 nM (OR=3.29, 95% CI: 1.17-9.26, p=0.024), were independently associated with poor response or resistance to anti-myeloma treatment

Poor response/treatment resistance was associated with longer Procoag-PPL, higher D-dimer levels and higher thrombin's Peak. The new score had 84% sensitivity and 59% specificity to identify patients who showed treatment resistance at 3 months from treatment initiation. The AUC of the ROC analysis for the model was 0.75.

Conclusions:

Based on the evaluation of Procoag-PPL®, D-Dimers and Peak of thrombin generation, the prospective ROADMAP-MM-CAT study led to the derivation of an original risk assessment model for the identification of NDMM patients with poor response or resistance to the anti-myeloma treatment.. The identified biomarkers of hypercoagulability need to be correlated in future studies with established clinical prognostic parameters in multiple myeloma patients and then validated clinically within the context of prospective clinical trials in order to assess their role in clinical practice and in anti-myeloma treatment optimization.