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We propose a novel adaptive design for clinical trials with time-to-event outcomes and covariates (which may consist of or include biomarkers). Our method is based on the expected entropy of the posterior distribution of a proportional…

Applications · Statistics 2016-03-29 James E. Barrett

Treatment effect estimation in continuous time is crucial for personalized medicine. However, existing methods for this task are limited to point estimates of the potential outcomes, whereas uncertainty estimates have been ignored. Needless…

Machine Learning · Computer Science 2024-04-04 Konstantin Hess , Valentyn Melnychuk , Dennis Frauen , Stefan Feuerriegel

Sample size reestimation can be a powerful tool to ensure that a clinical trial meets its prespecified power requirements when uncertainty regarding a design parameter exists at the planning stage. However, long term primary endpoints can…

Methodology · Statistics 2026-05-14 Aritra Mukherjee , Michael J Grayling , James J M S Wason

In this paper, a methodology is proposed that enables to analyze the sensitivity of the outcome of a therapy to unavoidable high dispersion of the patient specific parameters on one hand and to the choice of the parameters that define the…

Systems and Control · Electrical Eng. & Systems 2022-05-17 Mazen Alamir

We propose a new integrated phase I/II trial design to identify the most efficacious dose combination that also satisfies certain safety requirements for drug-combination trials. We first take a Bayesian copula-type model for dose finding…

Applications · Statistics 2011-08-09 Ying Yuan , Guosheng Yin

There are several steps to confirming the safety and efficacy of a new medicine. A sequence of trials, each with its own objectives, is usually required. Quantitative risk metrics can be useful for informing decisions about whether a…

The counterfactual distribution models the effect of the treatment in the untreated group. While most of the work focuses on the expected values of the treatment effect, one may be interested in the whole counterfactual distribution or…

Machine Learning · Statistics 2022-11-04 Diego Martinez-Taboada , Dino Sejdinovic

In this paper, a Bayesian approach is developed for simultaneously comparing multiple experimental treatments with a common control treatment in an exploratory clinical trial. The sample size is set to ensure that, at the end of the study,…

Statistics Theory · Mathematics 2019-11-14 John Whitehead , Faye Cleary , Amanda Turner

The use of drug combinations in clinical trials is increasingly common during the last years since a more favorable therapeutic response may be obtained by combining drugs. In phase I clinical trials, most of the existing methodology…

Methodology · Statistics 2020-02-17 José L. Jiménez , Sungjin Kim , Mourad Tighiouart

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…

Methodology · Statistics 2024-04-30 Shirin Golchi , James Willard

If explicit, formal consideration of clinical pharmacology at all informs the design and conduct of modern oncology dose-finding trials, the designs themselves hardly attest to this. Yet in conducting a trial, investigators affirm that they…

Methodology · Statistics 2020-12-25 David C. Norris

Survival analysis is a statistical technique used to estimate the time until an event occurs. Although it is applied across a wide range of fields, adjusting for reporting delays under practical constraints remains a significant challenge…

Machine Learning · Statistics 2025-10-27 Yuta Shikuri , Hironori Fujisawa

In most nonrandomized observational studies, differences between treatment groups may arise not only due to the treatment but also because of the effect of confounders. Therefore, causal inference regarding the treatment effect is not as…

Methodology · Statistics 2018-07-04 Debashis Ghosh

Randomization is a common technique used in clinical trials to eliminate potential bias and confounders in a patient population. Equal allocation to treatment groups is the standard due to its optimal efficiency in many cases. However, in…

Applications · Statistics 2020-04-09 Thevaa Chandereng , Xiaodan Wei , Rick Chappell

Estimates of the effects of treatment on cost from observational studies are subject to bias if there are unmeasured confounders. It is therefore advisable in practice to assess the potential magnitude of such biases. We derive a general…

Applications · Statistics 2014-01-09 Elizabeth A. Handorf , Justin E. Bekelman , Daniel F. Heitjan , Nandita Mitra

When a novel treatment has successfully passed phase I, different options to design subsequent phase II trials are available. One approach is a single-arm trial, comparing the response rate in the intervention group against a fixed…

Methodology · Statistics 2020-08-03 Johannes Krisam , Dorothea Weber , Richard F. Schlenk , Meinhard Kieser

In developing products for rare diseases, statistical challenges arise due to the limited number of patients available for participation in drug trials and other clinical research. Bayesian adaptive clinical trial designs offer the…

Applications · Statistics 2019-09-19 Xiao Wu , Yi Xu , Bradley P. Carlin

An objective of phase I dose-finding trials is to find the maximum tolerated dose; the dose with a particular risk of toxicity. Frequently, this risk is assessed across the first cycle of therapy. However, in oncology, a course of treatment…

Applications · Statistics 2021-05-03 Helen Barnett , Oliver Boix , Dimintris Kontos , Thomas Jaki

A treatment regime is a deterministic function that dictates personalized treatment based on patients' individual prognostic information. There is a fast-growing interest in finding optimal treatment regimes to maximize expected long-term…

Statistics Theory · Mathematics 2016-11-25 Runchao Jiang , Wenbin Lu , Rui Song , Marie Davidian

With medical tests becoming increasingly available, concerns about over-testing and over-treatment dramatically increase. Hence, it is important to understand the influence of testing on treatment selection in general practice. Most…

Methodology · Statistics 2020-08-11 Yun Li , Irina Bondarenko , Michael R. Elliott , Timothy P. Hofer , Jeremy M. G. Taylor