Prognostic Value of Serum Paraprotein Response Kinetics in Patients With Newly Diagnosed Multiple Myeloma

Clinical Lymphoma Myeloma and Leukemia(2022)

Cited 1|Views36
No score
Abstract
Introduction Response kinetics is a well-established prognostic marker in acute lymphoblastic leukemia. The situation is not clear in multiple myeloma (MM) despite having a biomarker for response monitoring (monoclonal component [MC]). Materials and Methods We developed a mathematical model to assess the prognostic value of serum MC response kinetics during 6 induction cycles, in 373 NDMM transplanted patients treated in the GEM2012Menos65 clinical trial. The model calculated a “resistance” parameter that reflects the stagnation in the response after an initial descent. Results Two patient subgroups were defined based on low and high resistance, that respectively captured sensitive and refractory kinetics, with progression-free survival (PFS) at 5 years of 72% and 59% (HR 0.64, 95% CI 0.44-0.93; P = .02). Resistance significantly correlated with depth of response measured after consolidation (80.9% CR and 68.4% minimal residual disease negativity in patients with sensitive vs. 31% and 20% in those with refractory kinetics). Furthermore, it modulated the impact of reaching CR after consolidation; thus, within CR patients those with refractory kinetics had significantly shorter PFS than those with sensitive kinetics (median 54 months vs. NR; P = .02). Minimal residual disease negativity abrogated this effect. Our study also questions the benefit of rapid responders compared to late responders (5-year PFS 59.7% vs. 76.5%, respectively [P < .002]). Of note, 85% of patients considered as late responders were classified as having sensitive kinetics. Conclusion This semi-mechanistic modeling of M-component kinetics could be of great value to identify patients at risk of early treatment failure, who may benefit from early rescue intervention strategies.
More
Translated text
Key words
Early treatment failure,Newly diagnosed myeloma,Time to best response,Prognostic marker,Depht of response
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined