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A Machine Learning Model Based on Tumor and Immune Biomarkers to Predict Undetectable MRD and Survival Outcomes in Multiple Myeloma.
Guerrero C, Puig N, Cedena MT, Goicoechea I, Perez C, Garcés JJ, Botta C, Calasanz MJ, Gutierrez NC, Martin-Ramos ML, Oriol A, Rios R, Hernandez MT, Martinez-Martinez R, Bargay J, de Arriba F, Palomera L, Gonzalez-Rodriguez AP, Mosquera-Orgueira A, Gonzalez-Perez MS, Martinez-Lopez J, Lahuerta JJ, Rosiñol L, Blade J, Mateos MV, San-Miguel JF, Paiva B. Guerrero C, et al. Among authors: gutierrez nc. Clin Cancer Res. 2022 Jun 13;28(12):2598-2609. doi: 10.1158/1078-0432.CCR-21-3430. Clin Cancer Res. 2022. PMID: 35063966
[Comparative genomic hybridization. Methodologic features].
García JL, Gutiérrez NC, Hernández JM, Sánchez MA, González MB, Arroyo JL, San Miguel JF. García JL, et al. Among authors: gutierrez nc. Sangre (Barc). 1999 Aug;44(4):291-6. Sangre (Barc). 1999. PMID: 10589281 Review. Spanish. No abstract available.
Early immunophenotypical evaluation of minimal residual disease in acute myeloid leukemia identifies different patient risk groups and may contribute to postinduction treatment stratification.
San Miguel JF, Vidriales MB, López-Berges C, Díaz-Mediavilla J, Gutiérrez N, Cañizo C, Ramos F, Calmuntia MJ, Pérez JJ, González M, Orfao A. San Miguel JF, et al. Blood. 2001 Sep 15;98(6):1746-51. doi: 10.1182/blood.v98.6.1746. Blood. 2001. PMID: 11535507 Free article.
Minimal residual disease in adolescent (older than 14 years) and adult acute lymphoblastic leukemias: early immunophenotypic evaluation has high clinical value.
Vidriales MB, Pérez JJ, López-Berges MC, Gutiérrez N, Ciudad J, Lucio P, Vazquez L, García-Sanz R, del Cañizo MC, Fernández-Calvo J, Ramos F, Rodríguez MJ, Calmuntia MJ, Porwith A, Orfao A, San-Miguel JF. Vidriales MB, et al. Blood. 2003 Jun 15;101(12):4695-700. doi: 10.1182/blood-2002-08-2613. Epub 2003 Feb 13. Blood. 2003. PMID: 12586618 Free article.
222 results