English
Related papers

Related papers: A Flexible Multi-Metric Bayesian Framework for Dec…

200 papers

Clinical decision making regarding treatments based on personal characteristics leads to effective health improvements. Machine learning (ML) has been the primary concern of diagnosis support according to comprehensive patient information.…

Machine Learning · Computer Science 2021-06-09 Kazuki Nakamura , Ryosuke Kojima , Eiichiro Uchino , Koichi Murashita , Ken Itoh , Shigeyuki Nakaji , Yasushi Okuno

Precision medicine has led to a paradigm shift allowing the development of targeted drugs that are agnostic to the tumor location. In this context, basket trials aim to identify which tumor types - or baskets - would benefit from the…

Methodology · Statistics 2026-01-05 Marcio A. Diniz , Hulya Kocyigit , Erin Moshier , Madhu Mazumdar , Deukwoo Kwon

Multi-arm multi-stage (MAMS) trials have gained popularity to enhance the efficiency of clinical trials, potentially reducing both duration and costs. This paper focuses on designing MAMS trials where no control treatment exists. This can…

Methodology · Statistics 2025-02-12 Peter Greenstreet , Thomas Jaki , Alun Bedding , Pavel Mozgunov

The standard paradigm for confirmatory clinical trials is to compare experimental treatments with a control, for example the standard of care or a placebo. However, it is not always the case that a suitable control exists. Efficient…

Methodology · Statistics 2024-10-29 Thomas Burnett , Thomas Jaki

An important goal of precision medicine is to personalize medical treatment by identifying individuals who are most likely to benefit from a specific treatment. The Likely Responder (LR) framework, which identifies a subpopulation where…

Methodology · Statistics 2026-03-13 Annan Deng , Carole Siegel , Hyung G. Park

Precision medicine is an emerging field that takes into account individual heterogeneity to inform better clinical practice. In clinical trials, the evaluation of treatment effect heterogeneity is an important component, and recently, many…

Methodology · Statistics 2023-02-24 Yuejia Xu , Angela M. Wood , Brian D. M. Tom

Trial level surrogates are useful tools for improving the speed and cost effectiveness of trials, but surrogates that have not been properly evaluated can cause misleading results. The evaluation procedure is often contextual and depends on…

Methodology · Statistics 2022-08-23 Michael C Sachs , Erin E Gabriel , Alessio Crippa , Michael J Daniels

The Bayesian Optimal Phase II (BOP2) framework is a flexible trial design that can naturally facilitate complex adaptations due to its Bayesian setting. BOP2 uses equal randomisation and equally placed interim analyses in its design, but it…

Applications · Statistics 2025-11-19 Connor Fitchett , Ayon Mukherjee , Sofía S. Villar , David S. Robertson

This paper develops a Bayesian approach for assessing equivalence and non-inferiority hypotheses in two-arm trials using relative belief ratios. A relative belief ratio is a measure of statistical evidence and can indicate evidence either…

Applications · Statistics 2014-01-20 Saman Muthukumarana , Michael Evans

This study investigates minimax and Bayes optimal strategies for fixed-budget best-arm identification. We consider an adaptive procedure consisting of a sampling phase followed by a recommendation phase, and we design an adaptive experiment…

Econometrics · Economics 2026-02-05 Masahiro Kato

In this paper we consider the problem of multiple testing when the hypotheses are dependent. In most of the existing literature, either Bayesian or non-Bayesian, the decision rules mainly focus on the validity of the test procedure rather…

Methodology · Statistics 2018-07-10 Noirrit K. Chandra , Sourabh Bhattacharya

Discovering novel materials with desired properties is essential for driving innovation. Industry 4.0 and smart manufacturing have promised transformative advances in this area through real-time data integration and automated production…

Machine Learning · Computer Science 2025-04-08 Avijit Saha Asru , Hamed Khosravi , Imtiaz Ahmed , Abdullahil Azeem

Parameter ensembles or sets of random effects constitute one of the cornerstones of modern statistical practice. This is especially the case in Bayesian hierarchical models, where several decision theoretic frameworks can be deployed. The…

Statistics Theory · Mathematics 2015-03-19 Cedric E. Ginestet

In recent years new cancer treatments improved survival in multiple histologies. Some of these therapeutics, and in particular treatment combinations, are often associated with severe treatment-related adverse events (AEs). It is therefore…

Applications · Statistics 2022-03-10 Steffen Ventz , Lorenzo Trippa

Active-controlled trials with non-inferiority objectives are often used when effective interventions are available, but new options may offer advantages or meet public health needs. In these trials, participants are randomized to an…

Methodology · Statistics 2025-10-28 Antonio Olivas-Martinez , Fei Gao , Holly Janes

Most Bayesian response-adaptive designs unbalance randomization rates towards the most promising arms with the goal of increasing the number of positive treatment outcomes during the study, even though the primary aim of the trial is…

Applications · Statistics 2018-07-02 Steffen Ventz , Matteo Cellamare , Sergio Bacallado , Lorenzo Trippa

A multi-arm multi-stage trial is a multi-arm trial which includes interim analyses - analysing the data at certain specified points, generally discontinuing treatments which are concluded to not work and proceeding with the remainder. It is…

Methodology · Statistics 2022-11-14 Martin Law

Precision medicine stands as a transformative approach in healthcare, offering tailored treatments that can enhance patient outcomes and reduce healthcare costs. As understanding of complex disease improves, clinical trials are being…

Methodology · Statistics 2024-05-15 Lara Maleyeff , Shirin Golchi , Erica E. M. Moodie , Marie Hudson

Multi-arm multi-stage trial designs can bring notable gains in efficiency to the drug development process. However, for normally distributed endpoints, the determination of a design typically depends on the assumption that the patient…

Methodology · Statistics 2017-10-11 Michael Grayling , James Wason , Adrian Mander

Count outcomes in longitudinal studies are frequent in clinical and engineering studies. In frequentist and Bayesian statistical analysis, methods such as Mixed linear models allow the variability or correlation within individuals to be…

Methodology · Statistics 2024-07-15 Alejandra Estefanía Patiño Hoyos , Johnatan Cardona Jiménez