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Phase I dose-escalation trials must be guided by a safety model in order to avoid exposing patients to unacceptably high risk of toxicities. Traditionally, these trials are based on one type of schedule. In more recent practice, however,…

统计方法学 · 统计学 2020-08-18 Burak Kürsad Günhan , Sebastian Weber , Tim Friede

Accurate models of clinical actions and their impacts on disease progression are critical for estimating personalized optimal dynamic treatment regimes (DTRs) in medical/health research, especially in managing chronic conditions.…

统计方法学 · 统计学 2021-02-19 William Hua , Hongyuan Mei , Sarah Zohar , Magali Giral , Yanxun Xu

Phase I dose-escalation trials constitute the first step in investigating the safety of potentially promising drugs in humans. Conventional methods for phase I dose-escalation trials are based on a single treatment schedule only. More…

应用统计 · 统计学 2021-03-04 Burak Kürsad Günhan , Sebastian Weber , Abdelkader Seroutou , Tim Friede

We present a novel method to improve pharmacokinetics modeling, an essential step of drug development. Conventional models frequently fail to fully represent the intricacies of drug absorption and distribution, which limits their predictive…

定量方法 · 定量生物学 2024-12-31 Nazanin Ahmadi , Shupeng Wang , George Karniadakis

An important task in drug development is to identify patients, which respond better or worse to an experimental treatment. Identifying predictive covariates, which influence the treatment effect and can be used to define subgroups of…

统计方法学 · 统计学 2018-11-27 Marius Thomas , Björn Bornkamp , Katja Ickstadt

Medication adherence is a well-known problem for pharmaceutical treatment of chronic diseases. Understanding how nonadherence affects treatment efficacy is made difficult by the ethics of clinical trials that force patients to skip doses of…

定量方法 · 定量生物学 2021-12-30 Elijah D Counterman , Sean D Lawley

We consider the effects of parameter uncertainty on the optimal radiation schedule in the context of the linear-quadratic model. Our interest arises from the observation that if inter-patient variations in OAR and tumor sensitivities to…

组织与器官 · 定量生物学 2015-06-05 Hamidreza Badri , Yoichi Watanabe , Kevin Leder

In comparative effectiveness research, treated and control patients might have a different start of follow-up as treatment is often started later in the disease trajectory. This typically occurs when data from treated and controls are not…

统计方法学 · 统计学 2024-06-10 Rik van Eekelen , Patrick M. M. Bossuyt , Nan van Geloven

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…

系统与控制 · 计算机科学 2019-01-15 Afroza Shirin , Isaac Klickstein , Song Feng , Yen Ting Lin , William S. Hlavacek , Francesco Sorrentino

The use of case-crossover designs has become widespread in epidemiological and medical investigations of transient associations. However, the most popular reference-select strategy, the time-stratified schema, is not a suitable solution for…

统计方法学 · 统计学 2020-01-22 Xiaoming Wang , Sukun Wang

One of the most significant barriers to medication treatment is patients' non-adherence to a prescribed medication regimen. The extent of the impact of poor adherence on resulting health measures is often unknown, and typical analyses…

应用统计 · 统计学 2018-12-04 Luis F. Campos , Mark E. Glickman , Kristen B. Hunter

Pragmatic trials increasingly define outcomes using real-world data such as electronic health records, where assessments are collected during routine care rather than at fixed timepoints. Consequently, these uncontrolled assessments may be…

Causal effect estimation for dynamic treatment regimes (DTRs) contributes to sequential decision making. However, censoring and time-dependent confounding under DTRs are challenging as the amount of observational data declines over time due…

机器学习 · 统计学 2021-09-27 Adi Lin , Jie Lu , Junyu Xuan , Fujin Zhu , Guangquan Zhang

We investigate how to exploit structural similarities of an individual's potential outcomes (POs) under different treatments to obtain better estimates of conditional average treatment effects in finite samples. Especially when it is…

机器学习 · 统计学 2021-10-26 Alicia Curth , Mihaela van der Schaar

In this article, we propose a phase I-II design in two stages for the combination of molecularly targeted therapies. The design is motivated by a published case study that combines a MEK and a PIK3CA inhibitors; a setting in which higher…

统计方法学 · 统计学 2025-05-21 José L. Jiménez , Mourad Tighiouart

Denoising Diffusion Probabilistic Models have shown an impressive generation quality, although their long sampling chain leads to high computational costs. In this paper, we observe that a long sampling chain also leads to an error…

机器学习 · 计算机科学 2023-06-21 Mang Ning , Enver Sangineto , Angelo Porrello , Simone Calderara , Rita Cucchiara

Estimating treatment effects is crucial for personalized decision-making in medicine, but this task faces unique challenges in clinical practice. At training time, models for estimating treatment effects are typically trained on…

机器学习 · 计算机科学 2025-10-31 Yuchen Ma , Dennis Frauen , Jonas Schweisthal , Stefan Feuerriegel

Aims: Combinations of treatments can offer additional benefit over the treatments individually. However, trials of these combinations are lower priority than the development of novel therapies, which can restrict funding, timelines and…

Many drugs used therapeutically or recreationally induce tolerance: the effect of the substance decreases with repeated use. This phenomenon may reduce the efficacy of the substance unless dosage is increased beyond what is healthy for the…

动力系统 · 数学 2024-03-19 Golrokh Nouri , Paul Tupper

Marginal structural models are a popular tool for investigating the effects of time-varying treatments, but they require an assumption of no unobserved confounders between the treatment and outcome. With observational data, this assumption…

统计方法学 · 统计学 2021-06-10 Matthew Blackwell , Soichiro Yamauchi
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