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Abstract Despite an increasing desire to use historical cohorts as “synthetic” controls for new drug evaluation, limited data exist regarding the comparability of real-world outcomes to those in clinical trials. Governmental cancer data often lacks details on treatment, response, and molecular characterization of disease sub-groups. The Australasian Leukaemia and Lymphoma Group National Blood Cancer Registry (ALLG NBCR) includes source information on morphology, cytogenetics, flow cytometry, and molecular features linked to treatment received (including transplantation), response to treatment, relapse, and survival outcome. Using data from 942 AML patients enrolled between 2012–2018, we assessed age and disease-matched control and interventional populations from published randomized trials that led to the registration of midostaurin, gemtuzumab ozogamicin, CPX-351, oral azacitidine, and venetoclax. Our analyses highlight important differences in real-world outcomes compared to clinical trial populations, including variations in anthracycline type, cytarabine intensity and scheduling during consolidation, and the frequency of allogeneic hematopoietic cell transplantation in first remission. Although real-world outcomes were comparable to some published studies, notable differences were apparent in others. If historical datasets were used to assess the impact of novel therapies, this work underscores the need to assess diverse datasets to enable geographic differences in treatment outcomes to be accounted for.

Abstract In the first part of this series, we delve into the foundational aspects of “Message in a Bottle (MIAB)” (henceforth referred to as MIAB). This study builds upon the legacy of the Voyager Golden Records, launched aboard Voyager 1 and 2 in 1977, which aimed to communicate with intelligent species beyond our world. These records not only offer a snapshot of Earth and human civilization but also represent our desire to establish contact with advanced alien civilizations. Given the absence of mutually understood signs, symbols, and semiotic conventions, MIAB, like its predecessor, uses scientific methods to design an innovative means of communication that encapsulates the story of humanity. Our goal is to share our collective knowledge, emotions, innovations, and aspirations in a way that provides a universal, yet contextually relevant, understanding of human society, the evolution of life on Earth, and our hopes and concerns for the future. Through this time and space traveling capsule, we also strive to inspire and unify current and future generations to celebrate and safeguard our shared human experience.

Discovering and characterizing exoplanets at the outer edge of the transit method’s sensitivity has proven challenging owing to geometric biases and the practical difficulties associated with acquiring long observational baselines. Nonetheless, a sample of giant exoplanets on orbits longer than 100 days has been identified by transit hunting missions. We present long-term Doppler spectroscopy for 11 such systems with observation baselines spanning a few years to a decade. We model these radial velocity observations jointly with transit photometry to provide initial characterizations of these objects and the systems in which they exist. Specifically, we make new precise mass measurements for four long-period giant exoplanets (Kepler-111 c, Kepler-553 c, Kepler-849 b, and PH-2 b), we place new upper limits on mass for four others (Kepler-421 b, KOI-1431.01, Kepler-1513 b, and Kepler-952 b), and we show that several confirmed planets are in fact not planetary at all. We present these findings to complement similar efforts focused on closer-in short-period giant planets, and with the hope of inspiring future dedicated studies of cool giant exoplanets.

The search for extraterrestrial (alien) life is one of the greatest scientific quests, yet it raises fundamental questions about just what we should be looking for and how. We approach alien hunting from the perspective of an experimenter engaging in binary classification with some true- and confounding-positive probabilities (TPP and CPP). We derive the Bayes factor in such a framework between two competing hypotheses, which we use to classify experiments as either impotent, imperfect, or ideal. Similarly, the experimenter can be classified as dogmatic, biased, or agnostic. We show how the unbounded explanatory and evasion capability of aliens poses fundamental problems to experiments directly seeking aliens. Instead, we advocate framing the experiments as looking for that outside of known processes, which means the hypotheses we test do not directly concern aliens per se. To connect back to aliens requires a second level of model selection, for which we derive the final odds ratio in a Bayesian framework. This reveals that it is fundamentally impossible to ever establish alien life at some threshold odds ratio, ${{ \mathcal O }}_{\mathrm{crit}}$ , unless we deem the prior probability that some as-yet-undiscovered natural process could explain the event is less than ${(1+{{ \mathcal O }}_{\mathrm{crit}})}^{-1}$ . This elucidates how alien hunters need to carefully consider the challenging problem of how probable unknown unknowns are, such as new physics or chemistry, and how it is arguably most fruitful to focus on experiments for which our domain knowledge is thought to be asymptotically complete.

The Simulation Argument posed by Bostrom suggests that we may be living inside a sophisticated computer simulation. If posthuman civilizations eventually have both the capability and desire to generate such Bostrom-like simulations, then the number of simulated realities would greatly exceed the one base reality, ostensibly indicating a high probability that we do not live in said base reality. In this work, it is argued that since the hypothesis that such simulations are technically possible remains unproven, statistical calculations need to consider not just the number of state spaces, but the intrinsic model uncertainty. This is achievable through a Bayesian treatment of the problem, which is presented here. Using Bayesian model averaging, it is shown that the probability that we are sims is in fact less than 50%, tending towards that value in the limit of an infinite number of simulations. This result is broadly indifferent as to whether one conditions upon the fact that humanity has not yet birthed such simulations, or ignore it. As argued elsewhere, it is found that if humanity does start producing such simulations, then this would radically shift the odds and make it very probably we are in fact simulated.