Person:
Martín Jiménez, Miguel José

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First Name
Miguel José
Last Name
Martín Jiménez
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Medicina
Department
Medicina
Area
Medicina
Identifiers
UCM identifierORCIDScopus Author IDWeb of Science ResearcherIDDialnet ID

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  • Publication
    Anthracyclines Strike Back: Rediscovering Non-Pegylated Liposomal Doxorubicin in Current Therapeutic Scenarios of Breast Cancer
    (MPDI, 2021-09-01) Schettini, Francesco; Giuliano, Mario; Lambertini, Matteo; Bartsch, Rupert; Pinato, David James; Onesti, Concetta Elisa; Harbeck, Nadia; Lüftner, Diana; Rottey, Sylvie; van Dam, Peter A.; Zaman, Khalil; Mustacchi, Giorgio; Gligorov, Joseph; Awada, Ahmad; Campone, Mario; Wildiers, Hans; Gennari, Alessandra; Tjan-Heijnen, Vivianne C. G.; Cortes, Javier; Locci, Mariavittoria; Paris, Ida; Del Mastro, Lucia; De Placido, Sabino; Martín Jiménez, Miguel José; Jerusalem, Guy; Venturini, Sergio; Curigliano, Giuseppe; Generali, Daniele
    Anthracyclines are among the most active chemotherapies (CT) in breast cancer (BC). However, cardiotoxicity is a risk and peculiar side effect that has been limiting their use in clinical practice, especially after the introduction of taxanes. Non-pegylated liposomal doxorubicin (NPLD) has been developed to optimize the toxicity profile induced by anthracyclines, while maintaining its unquestionable therapeutic index, thanks to its delivering characteristics that increase its diffusion in tumor tissues and reduce it in normal tissues. This feature allows NPLD to be safely administered beyond the standard doxorubicin maximum cumulative dose of 450–480 mg/m2. Following three pivotal first-line phase III trials in HER2-negative metastatic BC (MBC), this drug was finally approved in combination with cyclophosphamide in this specific setting. Given the increasing complexity of the therapeutic scenario of HER2-negative MBC, we have carefully revised the most updated literature on the topic and dissected the potential role of NPLD in the evolving therapeutic algorithms.