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Cancer cell lines have frequently been used to link drug sensitivity and resistance with genomic profiles. To capture genomic complexity in cancer, the Cancer Genome Project (CGP) (Garnett et al., 2012) screened 639 human tumor cell lines…

Applications · Statistics 2017-02-09 Hongmei Liu , J. Sunil Rao

We consider basket trials in which a biomarker-targeting drug may be efficacious for patients across different disease indications. Patients are enrolled if their cells exhibit some levels of biomarker expression. The threshold level is…

Applications · Statistics 2025-05-20 Shijie Yuan , Jiaxin Liu , Zhihua Gong , Xia Qin , Crystal Qin , Yuan Ji , Peter Müller

Radiotherapy planning is a critical aspect of cancer treatment, where the optimal selection of beam directions and dose distributions significantly impacts treatment efficacy and patient outcomes. Traditionally, this process involves…

Medical Physics · Physics 2023-12-05 Keshav Kumar K. , NVSL Narasimham , A. Ramakrishna Prasad

Most statistical tests for treatment effects used in randomized clinical trials with survival outcomes are based on the proportional hazards assumption, which often fails in practice. Data from early exploratory studies may provide evidence…

Statistics Theory · Mathematics 2020-05-28 Andrea Arfé , Brian Alexander , Lorenzo Trippa

When treatment effect modifiers influence the decision to participate in a randomized trial, the average treatment effect in the population represented by the randomized individuals will differ from the effect in other populations. In this…

Cancer remains a global challenge due to its growing clinical and economic burden. Its uniquely personal manifestation, which makes treatment difficult, has fuelled the quest for personalized treatment strategies. Thus, genomic profiling is…

Matching is a widely used causal inference design that aims to approximate a randomized experiment using observational data by forming matched sets of treated and control units based on similarities in their covariates. Ideally, treated…

Methodology · Statistics 2026-04-06 Jianan Zhu , Jeffrey Zhang , Zijian Guo , Siyu Heng

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

The effects of treatments may differ between persons with different characteristics. Addressing such treatment heterogeneity is crucial to investigate whether patients with specific characteristics are likely to benefit from a new…

Methodology · Statistics 2024-03-29 Xynthia Kavelaars , Joris Mulder , Maurits Kaptein

This paper proposes Bayesian Adaptive Trials (BAT) as both an efficient method to conduct trials and a unifying framework for evaluation social policy interventions, addressing limitations inherent in traditional methods such as Randomized…

For randomized clinical trials where a single, primary, binary endpoint would require unfeasibly large sample sizes, composite endpoints are widely chosen as the primary endpoint. Despite being commonly used, composite endpoints entail…

Methodology · Statistics 2022-09-27 Marta Bofill Roig , Guadalupe Gómez Melis , Martin Posch , Franz Koenig

Personalized cancer treatments based on the molecular profile of a patient's tumor are an emerging and exciting class of treatments in oncology. As genomic tumor profiling is becoming more common, targeted treatments to specific molecular…

We consider comparisons of statistical learning algorithms using multiple data sets, via leave-one-in cross-study validation: each of the algorithms is trained on one data set; the resulting model is then validated on each remaining data…

Applications · Statistics 2015-06-02 Lorenzo Trippa , Levi Waldron , Curtis Huttenhower , Giovanni Parmigiani

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

Response-adaptive designs allow the randomization probabilities to change during the course of a trial based on cumulated response data, so that a greater proportion of patients can be allocated to the better performing treatments. A major…

Methodology · Statistics 2020-06-03 David S. Robertson , James M. S. Wason

Reliably predicting the future spread of brain tumors using imaging data and on a subject-specific basis requires quantifying uncertainties in data, biophysical models of tumor growth, and spatial heterogeneity of tumor and host tissue.…

Computational Engineering, Finance, and Science · Computer Science 2022-09-27 Baoshan Liang , Jingye Tan , Luke Lozenski , David A. Hormuth , Thomas E. Yankeelov , Umberto Villa , Danial Faghihi

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 I-SPY2 phase 2 clinical trial is a long-running platform trial that evaluates neoadjuvant treatments for locally advanced breast cancer, assigning subjects to novel agents using response-adaptive randomization. Recently, I-SPY2 was…

The emerging field of precision oncology relies on the accurate pinpointing of alterations in the molecular profile of a tumor to provide personalized targeted treatments. Current methodologies in the field commonly include the application…

The use of Bayesian adaptive designs for randomised controlled trials has been hindered by the lack of software readily available to statisticians. We have developed a new software package (Bayesian Adaptive Trials Simulator Software -…

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