MIRROS: a randomized, placebo-controlled, Phase III trial of cytarabine ± idasanutlin in relapsed or refractory acute myeloid leukemia.

Patients with refractory or relapsed acute myeloid leukemia (R/R AML) have a poor prognosis, with a high unmet medical need. Idasanutlin is a small-molecule inhibitor of MDM2, a negative regulator of tumor suppressor p53. By preventing the p53–MDM2 interaction, idasanutlin allows for p53 activation, particularly in patients with TP53 wild-type (WT) status. MIRROS (NCT02545283) is a randomized Phase III trial evaluating idasanutlin + cytarabine versus placebo + cytarabine in R/R AML. The primary end point is overall survival in the TP53-WT population. Secondary end points include complete remission rate (cycle 1), overall remission rate (cycle 1) and event-free survival in the TP53-WT population. MIRROS has an innovative design that integrates a stringent interim analysis for futility; continuation criteria were met in mid-2017 and accrual is ongoing. Trial registration number: NCT0254528

Idasanutlin plus cytarabine in relapsed or refractory acute myeloid leukemia: results of the MIRROS trial

The phase III MIRROS trial (NCT02545283) evaluated the efficacy and safety of the small-molecule MDM2 antagonist idasanutlin plus cytarabine in patients with relapsed/refractory acute myeloid leukemia (R/R AML). Adults (N=447) with R/R AML whose disease relapsed or was refractory after ≤2 prior induction regimens as initial treatment or following salvage chemotherapy regimen, with Eastern Cooperative Oncology Group performance status ≤2 were enrolled regardless of TP53 mutation status and randomly assigned 2:1 to idasanutlin 300 mg or placebo orally twice daily plus cytarabine 1 g/m2 intravenously on days 1 to 5 of 28-day cycles. At primary analysis (cutoff, November 2019), 436 patients were enrolled, including 355 in the TP53 wild-type intention-to-treat (TP53WT-ITT) population. The primary endpoint, overall survival in the TP53WT-ITT population, was not met (median, 8.3 vs 9.1 months with idasanutlin-cytarabine vs placebo-cytarabine; stratified hazard ratio, 1.08; 95% CI, 0.81-1.45; p = .58). The complete remission (CR) rate, a key secondary endpoint, was 20.3% vs 17.1% (odds ratio [OR], 1.23; 95% CI, 0.70-2.18). The overall response rate (ORR) was 38.8% vs 22.0% (OR, 2.25; 95% CI, 1.36-3.72). Common any-grade adverse events (≥10% incidence in any arm) were diarrhea (87.0% vs 32.9%), febrile neutropenia (52.8% vs 49.3%), and nausea (52.5% vs 31.5%). In summary, despite improved ORR, adding idasanutlin to cytarabine did not improve overall survival or CR rates in patients with R/R AML

Combined fit to the spectrum and composition data measured by the Pierre Auger Observatory including magnetic horizon effects

The measurements by the Pierre Auger Observatory of the energy spectrum and mass composition of cosmic rays can be interpreted assuming the presence of two extragalactic source populations, one dominating the flux at energies above a few EeV and the other below. To fit the data ignoring magnetic field effects, the high-energy population needs to accelerate a mixture of nuclei with very hard spectra, at odds with the approximate E$^{-2}$ shape expected from diffusive shock acceleration. The presence of turbulent extragalactic magnetic fields in the region between the closest sources and the Earth can significantly modify the observed CR spectrum with respect to that emitted by the sources, reducing the flux of low-rigidity particles that reach the Earth. We here take into account this magnetic horizon effect in the combined fit of the spectrum and shower depth distributions, exploring the possibility that a spectrum for the high-energy population sources with a shape closer to E$^{-2}$ be able to explain the observations

Extraction of the Muon Signals Recorded with the Surface Detector of the Pierre Auger Observatory Using Recurrent Neural Networks

We present a method based on the use of Recurrent Neural Networks to extract the muon component from the time traces registered with water-Cherenkov detector (WCD) stations of the Surface Detector of the Pierre Auger Observatory. The design of the WCDs does not allow to separate the contribution of muons to the time traces obtained from the WCDs from those of photons, electrons and positrons for all events. Separating the muon and electromagnetic components is crucial for the determination of the nature of the primary cosmic rays and properties of the hadronic interactions at ultra-high energies. We trained a neural network to extract the muon and the electromagnetic components from the WCD traces using a large set of simulated air showers, with around 450 000 simulated events. For training and evaluating the performance of the neural network, simulated events with energies between 1018.5, eV and 1020 eV and zenith angles below 60 degrees were used. We also study the performance of this method on experimental data of the Pierre Auger Observatory and show that our predicted muon lateral distributions agree with the parameterizations obtained by the AGASA collaboration