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相关论文: Surrogacy Validation for Time-to-Event Outcomes wi…

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A surrogate endpoint S in a clinical trial is an outcome that may be measured earlier or more easily than the true outcome of interest T. In this work, we extend causal inference approaches to validate such a surrogate using potential…

统计方法学 · 统计学 2022-02-04 Emily Roberts , Michael Elliott , Jeremy M. G. Taylor

The use of valid surrogate endpoints is an important stake in clinical research to help reduce both the duration and cost of a clinical trial and speed up the evaluation of interesting treatments. Several methods have been proposed in the…

统计方法学 · 统计学 2025-02-13 Quentin Le Coent , Virginie Rondeau , Catherine Legrand

Candidate binary endpoints are often considered as surrogates for time-to-event (TTE) clinical endpoints, primarily because they can be assessed at earlier time points. To be submitted for regulatory approval candidate binary endpoints need…

应用统计 · 统计学 2026-03-23 Renee Y. Ge , Azadeh Shohoudi , Malini Iyengar , Quefeng Li , Judy Li

In meta-analytic modeling, the functional relationship between a primary and surrogate endpoint is estimated using summary data from a set of completed clinical trials. Parameters in the meta-analytic model are used to assess the quality of…

统计方法学 · 统计学 2025-08-07 James P. Long , Abhishikta Roy , Ehsan Irajizad , Kim-Anh Do , Yu Shen

Surrogate markers offer the potential to reduce the burden of data collection by replacing costly or invasive primary outcomes with more accessible measurements, provided that they can faithfully indicate the effectiveness of a treatment.…

统计方法学 · 统计学 2026-04-15 Silvaneo V. dos Santos , Layla Parast

Surrogate endpoints play an important role in drug development when they can be used to measure treatment effect early compared to the final clinical outcome and to predict clinical benefit or harm. Such endpoints are assessed for their…

Surrogate endpoints are often used in place of expensive, delayed, or rare true endpoints in clinical trials. However, regulatory authorities require thorough evaluation to accept these surrogate endpoints as reliable substitutes. One…

统计方法学 · 统计学 2024-10-08 Gokce Deliorman , Florian Stijven , Wim Van der Elst , Maria del Carmen Pardo , Ariel Alonso

For many rare diseases with no approved preventive interventions, promising interventions exist, yet it has been difficult to conduct a pivotal phase 3 trial that could provide direct evidence demonstrating a beneficial effect on the target…

Inferring causal effects on long-term outcomes using short-term surrogates is crucial to rapid innovation. However, even when treatments are randomized and surrogates fully mediate their effect on outcomes, it's possible that we get the…

统计方法学 · 统计学 2023-11-09 Aurélien Bibaut , Nathan Kallus , Simon Ejdemyr , Michael Zhao

Estimating the long-term effects of treatments is of interest in many fields. A common challenge in estimating such treatment effects is that long-term outcomes are unobserved in the time frame needed to make policy decisions. One approach…

统计方法学 · 统计学 2024-08-23 Susan Athey , Raj Chetty , Guido Imbens , Hyunseung Kang

Clinical trials or studies oftentimes require long-term and/or costly follow-up of participants to evaluate a novel treatment/drug/vaccine. There has been increasing interest in the past few decades in using short-term surrogate outcomes as…

统计方法学 · 统计学 2024-12-19 Xuan Wang , Tianxi Cai , Lu Tian , Layla Parast

In many real-world causal inference applications, the primary outcomes (labels) are often partially missing, especially if they are expensive or difficult to collect. If the missingness depends on covariates (i.e., missingness is not…

We propose a novel methodology to quantify the effect of stochastic interventions on non-terminal time-to-events that lie on the pathway between an exposure and a terminal time-to-event outcome. Investigating these effects is particularly…

统计方法学 · 统计学 2024-07-17 Linda Valeri , Cécile Proust-Lima , Weijia Fan , Jarvis T. Chen , Hélène Jacqmin-Gadda

Surrogate endpoint (SE) for overall survival in cancer patients is essential to improving the efficiency of oncology drug development. In practice, we may discover a new patient level association with survival, based on one or more clinical…

应用统计 · 统计学 2022-11-08 Wei Zou

Surrogate markers are often employed in clinical trials to replace primary outcomes that may be difficult, expensive, or time-consuming to measure directly. These markers can accelerate the evaluation of new treatments, provided they…

统计方法学 · 统计学 2026-03-17 Pietro Carlotti , Layla Parast

In semicompeting risks problems, nonterminal time-to-event outcomes such as time to hospital readmission are subject to truncation by death. These settings are often modeled with illness-death models for the hazards of the terminal and…

统计方法学 · 统计学 2019-02-27 Leah Comment , Fabrizia Mealli , Sebastien Haneuse , Corwin Zigler

Bivariate meta-analysis provides a useful framework for combining information across related studies and has been utilised to combine evidence from clinical studies to evaluate treatment efficacy on two outcomes. It has also been used to…

应用统计 · 统计学 2022-05-20 Tasos Papanikos , John R Thompson , Keith R Abrams , Sylwia Bujkiewicz

In randomized trials and observational studies, it is often necessary to evaluate the extent to which an intervention affects a time-to-event outcome, which is only partially observed due to right censoring. For instance, in infectious…

统计方法学 · 统计学 2024-12-16 Yutong Jin , Peter B. Gilbert , Aaron Hudson

Given the long follow-up periods that are often required for treatment or intervention studies, the potential to use surrogate markers to decrease the required follow-up time is a very attractive goal. However, previous studies have shown…

统计方法学 · 统计学 2016-08-12 Layla Parast , Tianxi Cai , Lu Tian

In clinical studies, the risk of the primary (terminal) event may be modified by intermediate events, resulting in semicompeting risks. To study the treatment effect on the terminal event mediated by the intermediate event, researchers wish…

统计方法学 · 统计学 2026-05-26 Yuhao Deng , Rui Wang , Tao Zhang , Xiang Zhan
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