Extended Emission of Cosmic Gamma-Ray Bursts Detected in the SPI-ACS/INTEGRAL Experiment

We have carried out a systematic analysis of the gamma-ray bursts' (GRBs) light curves detected in the SPI-ACS experiment onboard the INTEGRAL observatory aimed to search extended emission. The emission occasionally recorded after the prompt active phase of a GRB in the form of an emission that is longer than the active phase and less intense is called the extended one. Out of the 739 brightest GRBs recorded from 2002 to 2017, extended emission has been detected in $\sim20\%$ of the individual light curves; its maximum duration reaches $\sim 10000$ s. Two different types of extended emission have been revealed. One of them is an additional component of the light curve and is described by a power law (PL) with an index $\alpha \sim -1$ close to the PL index of the afterglow in the optical and X-ray bands. The second type can be described by a steeper PL decay of the light curve typical of the active burst phase. Extended emission has also been found in the combined light curve of long GRBs in the individual curves of which no extended emission has been detected. The PL index of the extended emission in the combined light curve is $\alpha \sim -2.4$. It is most likely associated with the superposition of light curves at the active phase; its total duration is $\sim 800$ s

Excitation spectrum of a 2D long-range Bose-liquid with a supersymmetry

We have studied excitation spectrum of the specfic 2D model of strongly interacting Bose particles via mapping of the many-body Schrodinger equation in imaginary time to the classical stochastic dynamics. In a broad range of coupling strength $\alpha$ a roton-like spectrum is found, with the roton gap being extremely small in natural units. A single quantum phase transition between strongly correlated supefluid and quantum Berezinsky crystal is found.Comment: 6 pages, 6 figure

A review of perspectives on the use of randomization in phase II oncology trials

Historically, phase II oncology trials assessed a treatment’s efficacy by examining its tumor response rate in a single-arm trial. Then, approximately 25 years ago, certain statistical and pharmacological considerations ignited a debate around whether randomized designs should be utilized instead. Here, based upon an extensive literature review, we review the arguments on either side of this debate. In particular, we describe the numerous factors that relate to the reliance of single-arm trials on historical control data, and detail the trial scenarios in which there was general agreement on preferential utilization of single-arm or randomized design frameworks, such as the use of single-arm designs when investigating treatments for rare cancers. We then summarize the latest figures on phase II oncology trial design, contrasting current design choices against historical recommendations on best practice. Ultimately, we find several ways in which the design of recently completed phase II trials does not appear to align with said recommendations. For example, despite advice to the contrary, only 66.2% of the assessed trials that employed progression-free survival as a primary or co-primary outcome used a randomized comparative design. In addition, we identify that just 28.2% of the considered randomized comparative trials came to a positive conclusion, as opposed to 72.7% of the single-arm trials. We conclude by describing a selection of important issues influencing contemporary design, framing this discourse in light of current trends in phase II, such as the increased use of biomarkers and recent interest in novel adaptive designs

Molnupiravir versus placebo in unvaccinated and vaccinated patients with early SARS-CoV-2 infection in the UK (AGILE CST-2): a randomised, placebo-controlled, double-blind, phase 2 trial

Background The antiviral drug molnupiravir was licensed for treating at-risk patients with COVID-19 on the basis of data from unvaccinated adults. We aimed to evaluate the safety and virological efficacy of molnupiravir in vaccinated and unvaccinated individuals with COVID-19. Methods This randomised, placebo-controlled, double-blind, phase 2 trial (AGILE CST-2) was done at five National Institute for Health and Care Research sites in the UK. Eligible participants were adult (aged ≥18 years) outpatients with PCR-confirmed, mild-to-moderate SARS-CoV-2 infection who were within 5 days of symptom onset. Using permuted blocks (block size 2 or 4) and stratifying by site, participants were randomly assigned (1:1) to receive either molnupiravir (orally; 800 mg twice daily for 5 days) plus standard of care or matching placebo plus standard of care. The primary outcome was the time from randomisation to SARS-CoV-2 PCR negativity on nasopharyngeal swabs and was analysed by use of a Bayesian Cox proportional hazards model for estimating the probability of a superior virological response (hazard ratio [HR]>1) for molnupiravir versus placebo. Our primary model used a two-point prior based on equal prior probabilities (50%) that the HR was 1·0 or 1·5. We defined a priori that if the probability of a HR of more than 1 was more than 80% molnupiravir would be recommended for further testing. The primary outcome was analysed in the intention-to-treat population and safety was analysed in the safety population, comprising participants who had received at least one dose of allocated treatment. This trial is registered in ClinicalTrials.gov, NCT04746183, and the ISRCTN registry, ISRCTN27106947, and is ongoing. Findings Between Nov 18, 2020, and March 16, 2022, 1723 patients were assessed for eligibility, of whom 180 were randomly assigned to receive either molnupiravir (n=90) or placebo (n=90) and were included in the intention-to-treat analysis. 103 (57%) of 180 participants were female and 77 (43%) were male and 90 (50%) participants had received at least one dose of a COVID-19 vaccine. SARS-CoV-2 infections with the delta (B.1.617.2; 72 [40%] of 180), alpha (B.1.1.7; 37 [21%]), omicron (B.1.1.529; 38 [21%]), and EU1 (B.1.177; 28 [16%]) variants were represented. All 180 participants received at least one dose of treatment and four participants discontinued the study (one in the molnupiravir group and three in the placebo group). Participants in the molnupiravir group had a faster median time from randomisation to negative PCR (8 days [95% CI 8–9]) than participants in the placebo group (11 days [10–11]; HR 1·30, 95% credible interval 0·92–1·71; log-rank p=0·074). The probability of molnupiravir being superior to placebo (HR>1) was 75·4%, which was less than our threshold of 80%. 73 (81%) of 90 participants in the molnupiravir group and 68 (76%) of 90 participants in the placebo group had at least one adverse event by day 29. One participant in the molnupiravir group and three participants in the placebo group had an adverse event of a Common Terminology Criteria for Adverse Events grade 3 or higher severity. No participants died (due to any cause) during the trial. Interpretation We found molnupiravir to be well tolerated and, although our predefined threshold was not reached, we observed some evidence that molnupiravir has antiviral activity in vaccinated and unvaccinated individuals infected with a broad range of SARS-CoV-2 variants, although this evidence is not conclusive

A surface-free design for phase I dual-agent combination trials

In oncology, there is a growing number of therapies given in combination. Recently, several dose-finding designs for Phase I dose-escalation trials for combinations were proposed. The majority of novel designs use a pre-specified parametric model restricting the search of the target combination to a surface of a particular form. In this work, we propose a novel model-free design for combination studies, which is based on the assumption of monotonicity within each agent only. Specifically, we parametrise the ratios between each neighbouring combination by independent Beta distributions. As a result, the design does not require the specification of any particular parametric model or knowledge about increasing orderings of toxicity. We compare the performance of the proposed design to the model-based continual reassessment method for partial ordering and to another model-free alternative, the product of independent beta design. In an extensive simulation study, we show that the proposed design leads to comparable or better proportions of correct selections of the target combination while leading to the same or fewer average number of toxic responses in a trial

Improving safety of the continual reassessment method via a modified allocation rule

This article proposes a novel criterion for the allocation of patients in phase I dose-escalation clinical trials, aiming to find the maximum tolerated dose (MTD). Conventionally, using a model-based approach, the next patient is allocated to the dose with the toxicity estimate closest (in terms of the absolute or squared distance) to the maximum acceptable toxicity. This approach, however, ignores the uncertainty in point estimates and ethical concerns of assigning a lot of patients to overly toxic doses. In fact, balancing the trade-off between how accurately the MTD can be estimated and how many patients would experience adverse events is one of the primary challenges in phase I studies. Motivated by recent discussions in the theory of estimation in restricted parameter spaces, we propose a criterion that allows to balance these explicitly. The criterion requires a specification of one additional parameter only that has a simple and intuitive interpretation. We incorporate the proposed criterion into the one-parameter Bayesian continual reassessment method and show, using simulations, that it can result in similar accuracy on average as the original design, but with fewer toxic responses on average. A comparison with other model-based dose-escalation designs, such as escalation with overdose control and its modifications, demonstrates that the proposed design can result in either the same mean accuracy as alternatives but fewer toxic responses or in a higher mean accuracy but the same number of toxic responses. Therefore, the proposed design can provide a better trade-off between the accuracy and the number of patients experiencing adverse events, making the design a more ethical alternative over some of the existing methods for phase I trials