2026-06-07T19:00:06Zhttps://docta.ucm.es/rest/oai/request

oai:docta.ucm.es:20.500.14352/1027492024-04-05T23:57:09Zcom_20.500.14352_14col_20.500.14352_15

00925njm 22002777a 4500 dc Onecha, Esther author Ruiz‐Heredia, Yanira author Martínez‐Cuadrón, David author Barragán, Eva author Martínez Sánchez, María Del Pilar author Linares Gómez, María author Rapado, Inmaculada author Perez‐Oteyza, Jaime author Magro, Elena author Herrera, Pilar author Rojas, José Luis author Gorrochategui, Julián author Villoria, Jesús author Boluda, Blanca author Sargas, Claudia author Ballesteros, Joan author Montesinos, Pau author Martínez López, Joaquín author Ayala Díaz, Rosa María author 2020-02-18 Refractoriness to induction therapy and relapse after complete remission are the leading causes of death in patients with acute myeloid leukaemia (AML). This study focussed on the prediction of response to standard induction therapy and outcome of patients with AML using a combined strategy of mutational profiling by next-generation sequencing (NGS, n = 190) and ex vivo PharmaFlow testing (n = 74) for the 10 most widely used drugs for AML induction therapy, in a cohort of adult patients uniformly treated according to Spanish PETHEMA guidelines. We identified an adverse mutational profile (EZH2, KMT2A, U2AF1 and/or TP53 mutations) that carries a greater risk of death [hazard ratio (HR): 3 29, P < 0 0001]. A high correlation was found between the ex vivo PharmaFlow results and clinical induction response (69%). Clinical correlation analysis showed that the pattern of multiresistance revealed by ex vivo PharmaFlow identified patients with a high risk of death (HR: 2 58). Patients with mutation status also ran a high risk (HR 4 19), and the risk was increased further in patients with both adverse profiles (HR 4 82). We have developed a new score based on NGS and ex vivo drug testing for AML patients that improves upon current prognostic risk stratification and allows clinicians to tailor treatments to minimise drug resistance. 0007-1048 1365-2141 10.1111/bjh.16432 https://hdl.handle.net/20.500.14352/102749 Improving the prediction of acute myeloid leukaemia outcomes by complementing mutational profiling with ex vivo chemosensitivity