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Related papers: Designing drug regimens that mitigate nonadherence

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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

Clinicians prescribe antibiotics by looking at the patient's health record with an experienced eye. However, the therapy might be rendered futile if the patient has drug resistance. Determining drug resistance requires time-consuming…

Artificial Intelligence · Computer Science 2023-03-09 Honglin Shu , Pei Gao , Lingwei Zhu , Zheng Chen

The keyboard design is a novel phase I dose-finding method that is simple and has good operating characteristics. This paper studies theoretical properties of the keyboard design, including the optimality of its decision rules, coherence in…

Methodology · Statistics 2017-12-20 Haitao Pan , Ruitao Lin , Ying Yuan

Dynamic prediction of causal effects under different treatment regimes conditional on an individual's characteristics and longitudinal history is an essential problem in precision medicine. This is challenging in practice because outcomes…

Methodology · Statistics 2023-03-07 Yizhen Xu , Jisoo Kim , Laura K. Hummers , Ami A. Shah , Scott Zeger

Medication adherence is essential to ensure treatment effectiveness, but too often in routine care non-adherence compromises the desired outcome. We explore longitudinal causal modelling using observational data to estimate the time-varying…

Methodology · Statistics 2026-03-10 Xiaoran Liang , Deniz Türkmen , Jane A H Masoli , Luke C Pilling , Jack Bowden

Hypoxia-activated prodrugs offer a promising strategy for targeting oxygen-deficient regions in solid tumors, which are often resistant to conventional therapies. However, modeling their behavior is challenging because of the complex…

Numerical Analysis · Mathematics 2025-10-06 Alessandro Coclite , Riccardo Montanelli Eccher , Luca Possenti , Piermario Vitullo , Paolo Zunino

Some patients benefit from a treatment while others may do so less or do not benefit at all. We have previously developed a two-stage network meta-regression prediction model that synthesized randomized trials and evaluates how treatment…

Data-driven methods for personalizing treatment assignment have garnered much attention from clinicians and researchers. Dynamic treatment regimes formalize this through a sequence of decision rules that map individual patient…

Methodology · Statistics 2022-02-22 Eric J. Rose , Erica E. M. Moodie , Susan Shortreed

The effects of molecularly targeted drug perturbations on cellular activities and fates are difficult to predict using intuition alone because of the complex behaviors of cellular regulatory networks. An approach to overcoming this problem…

Systems and Control · Computer Science 2019-01-15 Afroza Shirin , Isaac Klickstein , Song Feng , Yen Ting Lin , William S. Hlavacek , Francesco Sorrentino

The traditional model specification of stepped-wedge cluster-randomized trials assumes a homogeneous treatment effect across time while adjusting for fixed-time effects. However, when treatment effects vary over time, the constant effect…

In pragmatic cluster randomized controlled trials (PCRCTs), healthcare providers are randomized while both providers and patients may deviate from the assigned intervention. In many PCRCTs, cluster-level implementation is measured using…

Applications · Statistics 2026-04-29 Anthony Sisti , Ellen McCreedy , Roee Gutman

A main research goal in various studies is to use an observational data set and provide a new set of counterfactual guidelines that can yield causal improvements. Dynamic Treatment Regimes (DTRs) are widely studied to formalize this…

Machine Learning · Computer Science 2023-06-06 Soroush Saghafian

In the context of individual-level causal inference, we study the problem of predicting whether someone will respond or not to a treatment based on their features and past examples of features, treatment indicator (e.g., drug/no drug), and…

Machine Learning · Statistics 2019-06-04 Nathan Kallus

No unmeasured confounding is often assumed in estimating treatment effects in observational data when using approaches such as propensity scores and inverse probability weighting. However, in many such studies due to the limitation of the…

Applications · Statistics 2019-08-06 Rong Huang , Ronghui Xu , Parambir S. Dulai

The sequential treatment decisions made by physicians to treat chronic diseases are formalized in the statistical literature as dynamic treatment regimes. To date, methods for dynamic treatment regimes have been developed under the…

Methodology · Statistics 2022-02-22 Janie Coulombe , Erica E. M. Moodie , Susan M. Shortreed , Christel Renoux

We propose a doubly robust approach to characterizing treatment effect heterogeneity in observational studies. We develop a frequentist inferential procedure that utilizes posterior distributions for both the propensity score and outcome…

Methodology · Statistics 2022-07-21 Heejun Shin , Joseph Antonelli

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

Chemotherapy is one of the primary modalities of cancer treatment. Chemotherapy drug administration is a complex problem that often requires expensive clinical trials to evaluate potential regimens. One way to alleviate this burden and…

Optimization and Control · Mathematics 2021-11-04 Temitayo Ajayi , Seyedmohammadhossein Hosseinian , Andrew J. Schaefer , Clifton D. Fuller

In longitudinal studies, subjects may be lost to follow-up, or miss some of the planned visits, leading to incomplete response sequences. When the probability of non-response, conditional on the available covariates and the observed…

Methodology · Statistics 2017-07-10 Alessandra Spagnoli , Maria Francesca Marino , Marco Alfò

Dynamic treatment regimes are sequential decision rules that adapt treatment according to individual time-varying characteristics and outcomes to achieve optimal effects, with applications in precision medicine, personalized…

Methodology · Statistics 2025-10-24 Yuanshan Gao , Yang Bai , Yifan Cui
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