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Related papers: Meta-analysis of Censored Adverse Events

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Accurate assessment of adverse event (AE) incidence is critical in clinical cancer research for drug safety evaluation and regulatory approval. While meta-analysis serves as an essential tool to comprehensively synthesize the evidence…

Methodology · Statistics 2025-03-11 Zihan Zhou , Zizhong Tian , Christine B. Peterson , Le Bao , Shouhao Zhou

The analysis of adverse events (AEs) is a key component in the assessment of a drug's safety profile. Inappropriate analysis methods may result in misleading conclusions about a therapy's safety and consequently its benefit-risk ratio. The…

Safety analyses in terms of adverse events (AEs) are an important aspect of benefit-risk assessments of therapies. Compared to efficacy analyses AE analyses are often rather simplistic. The probability of an AE of a specific type is…

Applications · Statistics 2021-05-20 Regina Stegherr , Claudia Schmoor , Michael Lübbert , Tim Friede , Jan Beyersmann

Meta-analysis is a systematic approach for understanding a phenomenon by analyzing the results of many previously published experimental studies. It is central to deriving conclusions about the summary effect of treatments and interventions…

Computers and Society · Computer Science 2021-04-13 Lu Cheng , Dmitriy A. Katz-Rogozhnikov , Kush R. Varshney , Ioana Baldini

To investigate intervention effects on rare events, meta-analysis techniques are commonly applied in order to assess the accumulated evidence. When it comes to adverse effects in clinical trials, these are often most adequately handled…

Methodology · Statistics 2026-04-03 Christian Röver , Qiong Wu , Anja Loos , Tim Friede

Adverse drug events (ADEs) are a major safety issue in clinical trials. Thus, predicting ADEs is key to developing safer medications and enhancing patient outcomes. To support this effort, we introduce CT-ADE, a dataset for multilabel ADE…

Computation and Language · Computer Science 2025-03-11 Anthony Yazdani , Alban Bornet , Philipp Khlebnikov , Boya Zhang , Hossein Rouhizadeh , Poorya Amini , Douglas Teodoro

Analyses of adverse events (AEs) are an important aspect of the evaluation of experimental therapies. The SAVVY (Survival analysis for AdVerse events with Varying follow-up times) project aims to improve the analyses of AE data in clinical…

Random-effects meta-analyses of observational studies can produce biased estimates if the synthesized studies are subject to unmeasured confounding. We propose sensitivity analyses quantifying the extent to which unmeasured confounding of…

Methodology · Statistics 2017-10-10 Maya B. Mathur , Tyler J. VanderWeele

We introduce a Bayesian nonparametric inference approach for aggregate adverse event (AE) monitoring across studies. The proposed model seamlessly integrates external data from historical trials to define a relevant background rate and…

Methodology · Statistics 2025-09-10 Shijie Yuan , Kevin Roberts , Noirrit Kiran Chandra , Yuan Ji , Peter Müller

Meta-analysis, by synthesizing effect estimates from multiple studies conducted in diverse settings, stands at the top of the evidence hierarchy in clinical research. Yet, conventional approaches based on fixed- or random-effects models…

Meta-analysis is a statistical method used in evidence synthesis for combining, analyzing and summarizing studies that have the same target endpoint and aims to derive a pooled quantitative estimate using fixed and random effects models or…

Methodology · Statistics 2022-04-25 Ivette Raices Cruz , Matthias C. M. Troffaes , Johan Lindström , Ullrika Sahlin

Meta-analysis is a powerful tool to synthesize findings from multiple studies. The normal-normal random-effects model is widely used to account for between-study heterogeneity. However, meta-analysis of sparse data, which may arise when the…

Methodology · Statistics 2024-06-10 Taojun Hu , Yi Zhou , Satoshi Hattori

Ideally, a meta-analysis will summarize data from several unbiased studies. Here we consider the less than ideal situation in which contributing studies may be compromised by measurement error. Measurement error affects every study design,…

Throughout the different phases of a drug development program, randomized trials are used to establish the tolerability, safety, and efficacy of a candidate drug. At each stage one aims to optimize the design of future studies by…

Applications · Statistics 2021-02-08 Sebastian Weber , Andrew Gelman , Daniel Lee , Michael Betancourt , Aki Vehtari , Amy Racine

Observational studies of recurrent event rates are common in biomedical statistics. Broadly, the goal is to estimate differences in event rates under two treatments within a defined target population over a specified followup window.…

Methodology · Statistics 2024-11-13 Arman Oganisian , Anthony Girard , Jon A. Steingrimsson , Patience Moyo

The mining of adverse drug events (ADEs) is pivotal in pharmacovigilance, enhancing patient safety by identifying potential risks associated with medications, facilitating early detection of adverse events, and guiding regulatory…

Artificial Intelligence · Computer Science 2024-10-04 Pranab Sahoo , Ayush Kumar Singh , Sriparna Saha , Aman Chadha , Samrat Mondal

The SAVVY project aims to improve the analyses of adverse event (AE) data in clinical trials through the use of survival techniques appropriately dealing with varying follow-up times and competing events (CEs). Although statistical…

Random effects meta-analysis is widely used for synthesizing studies under the assumption that underlying effects come from a normal distribution. However, under certain conditions the use of alternative distributions might be more…

[See paper for full abstract] Meta-analysis is a crucial tool for answering scientific questions. It is usually conducted on a relatively small amount of ``trusted'' data -- ideally from randomized, controlled trials -- which allow causal…

Machine Learning · Statistics 2024-07-15 Shiva Kaul , Geoffrey J. Gordon

In the realm of cancer treatment, summarizing adverse drug events (ADEs) reported by patients using prescribed drugs is crucial for enhancing pharmacovigilance practices and improving drug-related decision-making. While the volume and…

Computation and Language · Computer Science 2025-05-08 Sofia Jamil , Aryan Dabad , Bollampalli Areen Reddy , Sriparna Saha , Rajiv Misra , Adil A. Shakur
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