In this paper, we extend the use of assurance for a single study to explore how meeting a study's pre-defined success criteria could update our beliefs about the true treatment effect and impact the assurance of subsequent studies. This concept of conditional assurance, the assurance of a subsequent study conditional on success in an initial study, can be used assess the de-risking potential of the study requiring immediate investment, to ensure it provides value within the overall development plan. If the planned study does not discharge sufficient later phase risk, alternative designs and/or success criteria should be explored. By transparently laying out the different design options and the risks associated, this allows for decision makers to make quantitative investment choices based on their risk tolerance levels and potential return on investment. This paper lays out the derivation of conditional assurance, discusses how changing the design of a planned study will impact the conditional assurance of a future study, as well as presenting a simple illustrative example of how this methodology could be used to transparently compare development plans to aid decision making within an organisation.
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http://dx.doi.org/10.1002/pst.2128 | DOI Listing |
Front Oncol
January 2025
Department of Radiation Oncology, Jiangxi Cancer Hospital & Institute, Jiangxi Clinical Research Center for Cancer, The Second Affiliated Hospital of Nanchang Medical College, Nanchang, China.
Objectives: Implementing pre-treatment patient-specific quality assurance (prePSQA) for cancer patients is a necessary but time-consuming task, imposing a significant workload on medical physicists. Currently, the prediction methods used for prePSQA fall under the category of supervised learning, limiting their generalization ability and resulting in poor performance on new data. In the context of this work, the limitation of traditional supervised models was broken by proposing a conditional generation method utilizing unsupervised diffusion model.
View Article and Find Full Text PDFBiom J
December 2024
Biostatistics, McGill University, Montreal, Canada.
Bayesian inference and the use of posterior or posterior predictive probabilities for decision making have become increasingly popular in clinical trials. The current practice in Bayesian clinical trials relies on a hybrid Bayesian-frequentist approach where the design and decision criteria are assessed with respect to frequentist operating characteristics such as power and type I error rate conditioning on a given set of parameters. These operating characteristics are commonly obtained via simulation studies.
View Article and Find Full Text PDFCalcif Tissue Int
October 2024
Orthopaedics, Nadogaya Hospital, Shin-Kashiwa, Kashiwa, Chiba, 277-0084, Japan.
Int J Gynaecol Obstet
August 2024
FIGO Committee on Ethical Aspects of Human Reproduction and Women's Health, London, UK.
An arbitrary gestational age limit of viability cannot be set, and in clinical practice the focus should be on a periviability interval-the so-called "gray zone" of prognostic uncertainty. For cases within this interval, the most appropriate decision-making process remains debatable and periviability has emerged as one of the greatest challenges in bioethics. Universally recognized ethical principles may be interpreted differently due to socioeconomic, cultural, and religious aspects.
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