A Bayesian approach to benefit–risk assessment in clinical studies with longitudinal data

Yan, Dongyan; Ahn, Chul; Azadeh, Shabnam; Atlas, Mourad; Tiwari, Ram C.

doi:10.1080/10543406.2020.1726370

Cited by 2 publications

(1 citation statement)

References 13 publications

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“…Under the FDA's BRA framework, no widely accepted quantitative methods for BRA exist. In practice, one of the most commonly used BRA metrics is the general benefit-risk (GBR) index proposed by [14], which has been generalized by several researchers in terms of determining weights for every endpoint, adding possible outcomes, generalizing to longitudinal data, and applying under a Bayesian framework ( [15][16][17][18]).…”

Section: Benefit-risk Assessmentmentioning

confidence: 99%

Novel Design and Analysis for Rare Disease Drug Development

Chow,

Pong,

Chow

2024

Mathematics

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For rare disease drug development, the United States (US) Food and Drug Administration (FDA) has indicated that the same standards as those for drug products for common conditions will be applied. To assist the sponsors in rare disease drug development, the FDA has initiated several incentive programs to encourage the sponsors in rare disease drug development. In practice, these incentive programs may not help in achieving the study objectives due to the limited small patient population. To overcome this problem, some out-of-the-box innovative thinking and/or approaches, without jeopardizing the integrity, quality, and scientific validity of rare disease drug development, are necessarily considered. These innovative thinking and/or approaches include but are not limited to (i) sample size justification based on probability statements rather than conventional power analysis; (ii) demonstrating not-ineffectiveness and not-unsafeness rather than demonstrating effectiveness and safety with the small patient population (i.e., limited sample size) available; (iii) the use of complex innovative designs such as a two-stage seamless adaptive trial design and/or an n-of-1 trial design for flexibility and the efficient assessment of the test treatment under study; (iv) using real-world data (RWD) and real-world evidence (RWE) to support regulatory submission; and (v) conducting an individual benefit–risk assessment for a complete picture of the clinical performance of the test treatment under investigation. In this article, we provide a comprehensive summarization of this innovative thinking and these approaches for an efficient, accurate and reliable assessment of a test treatment used for treating patients with rare diseases under study. Statistical considerations including challenges and justifications are provided whenever possible. In addition, an innovative approach that combines innovative thinking and these approaches is proposed for regulatory consideration in rare disease drug development.

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Section: Benefit-risk Assessmentmentioning

confidence: 99%

Novel Design and Analysis for Rare Disease Drug Development

Chow,

Pong,

Chow

2024

Mathematics

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A Proposed Confidence Ellipse Approach for Benefit-Risk Assessment in Clinical Trials

Zhang,

Wang

et al. 2024

Preprint

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In clinical development, an independent data safety monitoring committee (IDMC) is often established to ensure the test treatment's integrity, quality, safety, and efficacy under investigation. In clinical trials, IDMC may recommend stopping the trial early due to safety, futility/efficacy, or both after reviewing observed data in the interim based on pre-specified stopping boundaries. In practice, the interim data is often too small to reach clinically meaningful differences with statistical significance (i.e., the observed clinically meaningful difference is reproducible and not purely by chance alone). To provide an overall assessment (or complete clinical picture) of the performance of the test treatment under investigation, the FDA (2023) published guidance on the benefit-risk assessment (BRA) framework to facilitate IDMC decision-making. Several methods have been studied in the literature following the FDA's recommended framework. However, these methods did not consider the uncertainties and heterogeneities. Alternatively, a BRA approach is proposed based on a confidence ellipse of primary safety and efficacy endpoints. The proposed confidence ellipse approach was evaluated both theoretically and via a clinical trial simulation. The results indicate that the proposed confidence ellipse provides consistent and stable metrics, particularly as sample sizes increase. The derived metrics of Benefit-Risk Difference (BRD) and Benefit-Risk Ratio (BRR) showed favorable performance across different scenarios and thresholds. Applied to the TESTING trial data, our method confirmed and extended the original finding that a reduced methylprednisolone dose offered a more favorable benefit-risk profile. Specifically, the confidence ellipse method highlighted that the reduced dose consistently provided a better balance between efficacy and safety, particularly under stricter criteria for clinical significance. This method validated the original conclusions and provided additional insights into how different dosing regimens perform across various clinical scenarios, potentially offering a more refined tool for optimizing treatment decisions in complex therapeutic contexts.

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A Bayesian approach to benefit–risk assessment in clinical studies with longitudinal data

Cited by 2 publications

References 13 publications

Novel Design and Analysis for Rare Disease Drug Development

Novel Design and Analysis for Rare Disease Drug Development

A Proposed Confidence Ellipse Approach for Benefit-Risk Assessment in Clinical Trials

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