Ríos, R. (Rafael)

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    Circulating tumor cells for the staging of patients with newly diagnosed transplant-eligible multiple myeloma
    (American Society of Clinical Oncology, 2022) Garcés-Latre, J.J. (Juan José); Cedena, M.T. (María Teresa); Puig, N. (Noemí); Burgos, L. (Leire); Pérez, J.J. (José J.); Cordón, L. (Lourdes); Flores-Montero, J. (Juan); Sanoja-Flores, L. (Luzalba); Calasanz-Abinzano, M.J. (Maria Jose); Ortiol, A. (Albert); Blanchard, M.J. (María Jesús); Ríos, R. (Rafael); Martin, J. (Jesus); Martínez-Martínez, R. (Rafael); Bargay, J. (Joan); Sureda-Balari, A. (Anna); Rubia, J. (Javier) de la; Hernandez, M.T. (Miguel Teodoro); Rodriguez-Otero, P. (Paula); de-la-Cruz, J. (Javier); Orfao, A. (Alberto); Mateos, M.V. (María Victoria); Martínez-López, J. (Joaquín); Lahuerta, J.J. (Juan José); Rosiñol, L. (Laura); Bladé, J. (Joan); San-Miguel, J.F. (Jesús F.); Paiva, B. (Bruno)
    PURPOSE Patients with multiple myeloma (MM) may show patchy bone marrow (BM) infiltration and extramedullary disease. Notwithstanding, quantification of plasma cells (PCs) continues to be performed in BM since the clinical translation of circulating tumor cells (CTCs) remains undefined. PATIENTS AND METHODS CTCs were measured in peripheral blood (PB) of 374 patients with newly diagnosed MM enrolled in the GEM2012MENOS65 and GEM2014MAIN trials. Treatment included bortezomib, lenalidomide, and dexamethasone induction followed by autologous transplant, consolidation, and maintenance. Next-generation flow cytometry was used to evaluate CTCs in PB at diagnosis and measurable residual disease (MRD) in BM throughout treatment. RESULTS CTCs were detected in 92% (344 of 374) of patients with newly diagnosed MM. The correlation between the percentages of CTCs and BM PCs was modest. Increasing logarithmic percentages of CTCs were associated with inferior progression-free survival (PFS). A cutoff of 0.01% CTCs showed an independent prognostic value (hazard ratio: 2.02; 95% CI, 1.3 to 3.1; P 5 .001) in multivariable PFS analysis including the International Staging System, lactate dehydrogenase levels, and cytogenetics. The combination of the four prognostic factors significantly improved risk stratification. Outcomes according to the percentage of CTCs and depth of response to treatment showed that patients with undetectable CTCs had exceptional PFS regardless of complete remission and MRD status. In all other cases with detectable CTCs, only achieving MRD negativity (and not complete remission) demonstrated a statistically significant increase in PFS. CONCLUSION Evaluation of CTCs in PB outperformed quantification of BM PCs. The detection of $ 0.01% CTCs could be a new risk factor in novel staging systems for patients with transplant-eligible MM
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    A Machine Learning Model Based on Tumor and Immune Biomarkers to Predict Undetectable MRD and Survival Outcomes in Multiple Myeloma
    (American Association for Cancer Research, 2022) Guerrero, C. (Camila); Puig, N. (Noemí); Cedena, M.T. (María Teresa); Goicoechea, I. (Ibai); Perez, C. (Cristina); Garcés-Latre, J.J. (Juan José); Botta, C. (Cirino); Calasanz-Abinzano, M.J. (Maria Jose); Gutierrez, N.C. (Norma C.); Martin-Ramos, M.L. (Maria Luisa); Oriol, A. (Albert); Ríos, R. (Rafael); Hernandez, M.T. (Miguel Teodoro); Martínez-Martínez, R. (Rafael); Bargay, J. (Joan); Arriba, F. (Felipe) de; Palomera, L. (Luis); González-Rodriguez, A.P. (Ana Pilar); Mosquera-Orgueira, A. (Adrián); Pérez-González, M. (Marta); Martínez-López, J. (Joaquín); Lahuerta, J.J. (Juan José); Rosiñol, L. (Laura); Bladé, J. (Joan); Mateos, M.V. (María Victoria); San-Miguel, J.F. (Jesús F.); Paiva, B. (Bruno)
    Purpose: Undetectable measurable residual disease (MRD) is a surrogate of prolonged survival in multiple myeloma. Thus, treatment individualization based on the probability of a patient achieving undetectable MRD with a singular regimen could represent a new concept toward personalized treatment, with fast assessment of its success. This has never been investigated; therefore, we sought to define a machine learning model to predict undetectable MRD at the onset of multiple myeloma. Experimental Design: This study included 487 newly diagnosed patients with multiple myeloma. The training (n ¼ 152) and internal validation cohorts (n ¼ 149) consisted of 301 transplant-eligible patients with active multiple myeloma enrolled in the GEM2012MENOS65 trial. Two external validation cohorts were defined by 76 high-risk transplant-eligible patients with smoldering multiple myeloma enrolled in the Grupo Espanol de Mieloma ~ (GEM)-CESAR trial, and 110 transplant-ineligible elderly patients enrolled in the GEM-CLARIDEX trial. Results: The most effective model to predict MRD status resulted from integrating cytogenetic [t(4;14) and/or del(17p13)], tumor burden (bone marrow plasma cell clonality and circulating tumor cells), and immune-related biomarkers. Accurate predictions of MRD outcomes were achieved in 71% of cases in the GEM2012MENOS65 trial (n ¼ 214/301) and 72% in the external validation cohorts (n ¼ 134/186). The model also predicted sustained MRD negativity from consolidation onto 2 years maintenance (GEM2014MAIN). High-confidence prediction of undetectable MRD at diagnosis identified a subgroup of patients with active multiple myeloma with 80% and 93% progression-free and overall survival rates at 5 years. Conclusions: It is possible to accurately predict MRD outcomes using an integrative, weighted model defined by machine learning algorithms. This is a new concept toward individualized treatment in multiple myeloma