scholarly journals A Bayesian approach for individual‐level drug benefit‐risk assessment

2019 ◽  
Vol 38 (16) ◽  
pp. 3040-3052 ◽  
Author(s):  
Kan Li ◽  
Sheng Luo ◽  
Sammy Yuan ◽  
Shahrul Mt‐Isa
Keyword(s):  
Risk Assessment ◽  
Bayesian Approach ◽  
Drug Benefit ◽  
Individual Level ◽  
Benefit Risk Assessment

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

2020 ◽  
Vol 30 (3) ◽  
pp. 574-591
Author(s):  
Dongyan Yan ◽  
Chul Ahn ◽  
Shabnam Azadeh ◽  
Mourad Atlas ◽  
Ram Tiwari
Keyword(s):  
Risk Assessment ◽  
Longitudinal Data ◽  
Bayesian Approach ◽  
Clinical Studies ◽  
Benefit Risk Assessment

A Bayesian Approach for Benefit-Risk Assessment

2014 ◽  
Vol 6 (4) ◽  
pp. 326-337 ◽  
Author(s):  
Yueqin Zhao ◽  
Jyoti Zalkikar ◽  
Ram C. Tiwari ◽  
Lisa M. LaVange
Keyword(s):  
Risk Assessment ◽  
Bayesian Approach ◽  
Benefit Risk Assessment

Current State of Drug Benefit-Risk Assessment (BRA) Worldwide

Yakhak Hoeji ◽  
2019 ◽  
Vol 63 (2) ◽  
pp. 103-112
Author(s):  
Sohyun Jeong ◽  
Sunmee Jang
Keyword(s):  
Risk Assessment ◽  
Drug Benefit ◽  
Current State ◽  
Benefit Risk Assessment

The Case for a Bayesian Approach to Benefit-Risk Assessment: Overview and Future Directions

2017 ◽  
Vol 51 (5) ◽  
pp. 568-574 ◽  
Author(s):  
Maria J. Costa ◽  
Weili He ◽  
Yannis Jemiai ◽  
Yueqin Zhao ◽  
Carl Di Casoli
Keyword(s):  
Risk Assessment ◽  
Bayesian Approach ◽  
Future Directions ◽  
Benefit Risk Assessment

Quantitative Drug Benefit-Risk Assessment

2014 ◽  
Vol 48 (3) ◽  
pp. 306-313 ◽  
Author(s):  
Victor Crentsil ◽  
Jung Lee ◽  
Andre Jackson
Keyword(s):  
Risk Assessment ◽  
Drug Benefit ◽  
Benefit Risk Assessment

scholarly journals A novel measure of drug benefit–risk assessment based on Scale Loss Score

2018 ◽  
Vol 28 (9) ◽  
pp. 2738-2753 ◽  
Author(s):  
Gaelle Saint-Hilary ◽  
Veronique Robert ◽  
Mauro Gasparini ◽  
Thomas Jaki ◽  
Pavel Mozgunov
Keyword(s):  
Risk Assessment ◽  
Decision Analysis ◽  
Quantitative Methods ◽  
Utility Score ◽  
Community Acquired Pneumonia ◽  
Multicriteria Decision Analysis ◽  
Drug Benefit ◽  
Multicriteria Decision ◽  
Extreme Risk ◽  
Benefit Risk Assessment

Quantitative methods have been proposed to assess and compare the benefit-risk balance of treatments. Among them, multicriteria decision analysis (MCDA) is a popular decision tool as it permits to summarise the benefits and the risks of a drug in a single utility score, accounting for the preferences of the decision-makers. However, the utility score is often derived using a linear model which might lead to counter-intuitive conclusions; for example, drugs with no benefit or extreme risk could be recommended. Moreover, it assumes that the relative importance of benefits against risks is constant for all levels of benefit or risk, which might not hold for all drugs. We propose Scale Loss Score (SLoS) as a new tool for the benefit–risk assessment, which offers the same advantages as the linear multicriteria decision analysis utility score but has, in addition, desirable properties permitting to avoid recommendations of non-effective or extremely unsafe treatments, and to tolerate larger increases in risk for a given increase in benefit when the amount of benefit is small than when it is high. We present an application to a real case study on telithromycin in Community Acquired Pneumonia and Acute Bacterial Sinusitis, and we investigated the patterns of behaviour of Scale Loss Score, as compared to the linear multicriteria decision analysis, in a comprehensive simulation study.

Bayesian Approach to Personalized Benefit-Risk Assessment

2016 ◽  
Vol 8 (3) ◽  
pp. 316-324 ◽  
Author(s):  
Shiqi Cui ◽  
Yueqin Zhao ◽  
Ram C. Tiwari
Keyword(s):  
Risk Assessment ◽  
Bayesian Approach ◽  
Benefit Risk Assessment
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