Publicacións en colaboración con investigadores/as de Complexo Hospitalario Universitario de Santiago (119)

2022

  1. A Machine Learning Model Based on Tumor and Immune Biomarkers to Predict Undetectable MRD and Survival Outcomes in Multiple Myeloma

    Clinical cancer research : an official journal of the American Association for Cancer Research

  2. Azacitidine vs. Decitabine in Unfit Newly Diagnosed Acute Myeloid Leukemia Patients: Results from the PETHEMA Registry

    Cancers, Vol. 14, Núm. 9

  3. Characteristics and Outcomes of Adult Patients in the PETHEMA Registry with Relapsed or Refractory FLT3-ITD Mutation-Positive Acute Myeloid Leukemia

    Cancers, Vol. 14, Núm. 11

  4. Comparison of transfusion-outcome in patients with massive bleeding receiving pathogen-reduced platelets prepared with two different technologies

    Transfusion and Apheresis Science, Vol. 61, Núm. 3

  5. Evaluation of the Stellae-123 prognostic gene expression signature in acute myeloid leukemia

    Frontiers in Oncology, Vol. 12

  6. Immune Checkpoint Inhibitors in Acute Myeloid Leukemia: A Meta-Analysis

    Frontiers in Oncology, Vol. 12

  7. Low-risk polycythemia vera treated with phlebotomies: clinical characteristics, hematologic control and complications in 453 patients from the Spanish Registry of Polycythemia Vera

    Annals of Hematology, Vol. 101, Núm. 10, pp. 2231-2239

  8. Predictors of thrombosis and bleeding in 1613 myelofibrosis patients from the Spanish Registry of Myelofibrosis

    British Journal of Haematology, Vol. 199, Núm. 4, pp. 529-538

  9. Prognostic Stratification of Multiple Myeloma Using Clinicogenomic Models: Validation and Performance Analysis of the IAC-50 Model

    HemaSphere, Vol. 6, Núm. 8

  10. Real-life analysis on safety and efficacy of asciminib for ponatinib pretreated patients with chronic myeloid leukemia

    Annals of Hematology, Vol. 101, Núm. 10, pp. 2263-2270

  11. Real-world analysis of main clinical outcomes in patients with polycythemia vera treated with ruxolitinib or best available therapy after developing resistance/intolerance to hydroxyurea

    Cancer, Vol. 128, Núm. 13, pp. 2441-2448

  12. Unsupervised machine learning improves risk stratification in newly diagnosed multiple myeloma: an analysis of the Spanish Myeloma Group

    Blood cancer journal, Vol. 12, Núm. 4, pp. 76

  13. Use of Venetoclax in Patients with Relapsed or Refractory Acute Myeloid Leukemia: The PETHEMA Registry Experience

    Cancers, Vol. 14, Núm. 7