Publications

Policy Points: Randomized trials—the gold standard of evaluating effectiveness—constitute a small minority of existing evidence on agents given accelerated approval. One‐third of randomized trials are in therapeutic areas outside of FDA approval and less than half evaluate the therapeutic benefits of these agents but use them instead as common backbone treatments. Agents receiving accelerated approval are often tested concurrently in several therapeutic areas. For most agents, no substantial time lag is apparent between the average start dates of randomized trials evaluating their effectiveness and those using them as part of background therapies. There appears to be a tendency for therapeutic agents receiving accelerated approval to quickly become an integral component of standard treatment, despite potential shortcomings in their evidence base. Context Therapeutic agents treating serious conditions are eligible for Food and Drug Administration (FDA) accelerated approval. The clinical evidence accrued on agents receiving accelerated approval has not been systematically evaluated. Our objective was to assess the timing and characteristics of available studies. Methods We first identified clinical studies of novel therapeutic agents receiving accelerated approval. We then (1) categorized those studies as randomized or nonrandomized, (2) explored whether they evaluated the FDA‐approved indications, and (3) documented the available treatment comparisons. We also meta‐analyzed the difference in start times between randomized studies that (1) did or did not evaluate approved indications and (2) were or were not designed to evaluate the agent's effectiveness. Findings In total, 37 novel therapeutic agents received accelerated approval between 2000 and 2013. Our search of ClinicalTrials.gov identified 7,757 studies, which included 1,258,315 participants. Only one‐third of identified studies were randomized controlled trials. Of 1,631 randomized trials with advanced recruitment status, 906 were conducted in therapeutic areas for which agents received initial accelerated approval, 202 were in supplemental indications, and 523 were outside approved indications. Only 411 out of 906 (45.4%) trials were designed to test the effectiveness of agents that received accelerated approval (“evaluation” trials); others used these agents as common background treatment in both arms (“background” trials). There was no detectable lag between average start times of trials conducted within and outside initially approved indications. Evaluation trials started on average 1.52 years (95% CI: 0.87 to 2.17) earlier than background trials. Conclusions Cumulative evidence on agents with accelerated approvals has major limitations. Most clinical studies including these agents are small and nonrandomized, and about a third are conducted in unapproved areas, typically concurrently with those conducted in approved areas. Most randomized trials including these therapeutic agents are not designed to directly evaluate their clinical benefits but to incorporate them as standard treatment.

As CPU cores become building blocks, we see a great expansion in the types of on-chip memory systems proposed for CMPs. Unfortunately, designing the cache and protocol controllers to support these memory systems is complex, and their concurrency and latency characteristics significantly affect the performance of any CMP. To address this problem, this paper presents a microarchitecture framework for cache and protocol controllers, which can aid in generating the RTL for new memory systems. The framework consists of three pipelined engines' request-tracking, state-manipulation, and data movement' which are programmed to implement a higher-level memory model. This approach simplifies the design and verification of CMP systems by decomposing the memory model into sequences of state and data manipulations. Moreover, implementing the framework itself produces a polymorphic memory system. To validate the approach, we implemented a scalable, flexible CMP in silicon. The memory system was then programmed to support three disparate memory models' cache coherent shared memory, streams and transactional memory. Measured overheads of this approach seem promising. Our system generates controllers with performance overheads of less than 20% compared to an ideal controller with zero internal latency. Even the overhead of directly implementing a fully programmable controller was modest. While it did double the controller's area, the amortized effective area in the system grew by roughly 7%.

The objective is to design and build a small, high-bandwidth switch.

The DASH (directory architecture for shared-memory) multiprocessor, which combines the programmability of shared-memory machines with the scalability of message-passing machines, is described. Hardware-supported coherent caches provide for low-latency access of shared data and ease of programming. Caches are kept coherent by means of a distributed directory-based protocol. Shared memory in the machine is distributed among the processing nodes, and scalable memory bandwidth is provided by connecting the nodes through a general interconnection network. The prototype DASH machine will consists of 64 high-performance microprocessors, with an aggregate performance of over 1200 MIPS and 250 scalar MFLOPS. The fundamental premise in DASH is that it is possible to build a scalable shared-memory machine with hardware-supported coherent caches by using a distributed directory-based cache coherence protocol. The mechanisms for providing scalable memory bandwidth, reducing and tolerating memory latency, and supporting efficient synchronization are described. A brief description of the machine's implementation is given.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

ABSTRACT Background Post-pandemic surveillance data on COVID-19 infections may help inform future public health policies regarding SARS-CoV-2 testing, vaccinations or other COVID-19 measures. We estimate the total SARS-CoV-2 infections in Austria after the end of the pandemic (May 5, 2023, per WHO) up to May 2024 from wastewater data. Those estimates are used in an agent-based model (ABM) to estimate average national levels of SARS-CoV-2 infection protection (IP) and COVID-19 death protection (DP). Methods We use a previously published model estimating total infections in Austria from wastewater data and extrapolate the approach up to May 2024. Utilizing those estimates in an ABM, we estimate daily national average IP and DP. These estimates are based on waning immunity estimates of previous literature and incorporate documented vaccinations. Findings We estimate approximately 3·2 million infections between May 6, 2023, and May 23, 2024, with a total of 17·8 million infections following May 12, 2020. The ABM estimates that 95% of people in Austria were infected with SARS-CoV-2 at least once. It also shows very high levels of national average DP a year after the end of the pandemic. National IP remained relatively low after the onset of Omicron. Interpretation The estimated high number of SARS-CoV-2 infections since the end of the COVID-19 pandemic in Austria has kept the national average DP very high. These findings should be considered for public health decisions on SARS-CoV-2 testing practices and vaccine booster administrations. Funding Austrian Science Fund (FWF) KLI 1188.

Trends in VLSI technology scaling demand that future computing devices be narrowly focused to achieve high performance and high efficiency, yet also target the high volumes and low costs of widely applicable general purpose designs. To address these conflicting requirements, we propose a modular reconfigurable architecture called Smart Memories, targeted at computing needs in the 0.1μ technology generation. A Smart Memories chip is made up of many processing tiles, each containing local memory, local interconnect, and a processor core. For efficient computation under a wide class of possible applications, the memories, the wires, and the computational model can all be altered to match the applications. To show the applicability of this design, two very different machines at opposite ends of the architectural spectrum, the Imagine stream processor and the Hydra speculative multiprocessor, are mapped onto the Smart Memories computing substrate. Simulations of the mappings show that the Smart Memories architecture can successfully map these architectures with only modest performance degradation.

The FokI, BsmI, ApaI, and TaqI VDR polymorphisms are not associated with BMD or with fractures, but the Cdx2 polymorphism may be associated with risk for vertebral fractures.

Abstract Background Methodological limitations affect a significant number of oncology and haematology trials, raising concerns about the applicability of their results. For example, a suboptimal control arm or limited access to best care upon progression may skew the trial results toward a benefit in the experimental arm. Beyond the fact that such limitations do not prevent drugs reaching the market, other assessment tools, such as those developed by professional societies—ESMO‐MCBS and ASCO Value Framework—do not integrate these important shortcomings. Methods We propose creating a novel framework with the scope of assessing registration cancer clinical trials in haematology and oncology (randomized or single arm)—that is trials leading to a marketing authorization. The main steps of the methods are (1) assembling a scientific board; (2) defining the scope, goal and methods through pre‐specified, pre‐registered and protocolized methodology; (3) preregistration of the protocol; (4) conducting a scoping review of limitations and biases affecting oncology trials and assessing existing scores or methods; (5) developing a list of features to be included and assessed within the framework; (6) assessing each feature through a questionnaire sent to highly cited haematologists and oncologists involved in clinical trials; and (7) finalizing the first version of framework. Results Not applicable. Conclusions Our proposal emerged in response to the lack of consideration for key limitations in current trial assessments. The goal is to create a framework specifically designed to assess single trials leading to marketing authorization in the field of oncology and haematogy.