Literature DB >> 26800458

Recommendations for benefit-risk assessment methodologies and visual representations.

Diana Hughes1, Ed Waddingham2, Shahrul Mt-Isa2, Alesia Goginsky3, Edmond Chan4, Gerald F Downey5, Christine E Hallgreen2,6, Kimberley S Hockley2, Juhaeri Juhaeri7, Alfons Lieftucht8, Marilyn A Metcalf9, Rebecca A Noel10, Lawrence D Phillips11, Deborah Ashby2, Alain Micaleff12.   

Abstract

PURPOSE: The purpose of this study is to draw on the practical experience from the PROTECT BR case studies and make recommendations regarding the application of a number of methodologies and visual representations for benefit-risk assessment.
METHODS: Eight case studies based on the benefit-risk balance of real medicines were used to test various methodologies that had been identified from the literature as having potential applications in benefit-risk assessment. Recommendations were drawn up based on the results of the case studies.
RESULTS: A general pathway through the case studies was evident, with various classes of methodologies having roles to play at different stages. Descriptive and quantitative frameworks were widely used throughout to structure problems, with other methods such as metrics, estimation techniques and elicitation techniques providing ways to incorporate technical or numerical data from various sources. Similarly, tree diagrams and effects tables were universally adopted, with other visualisations available to suit specific methodologies or tasks as required. Every assessment was found to follow five broad stages: (i) Planning, (ii) Evidence gathering and data preparation, (iii) Analysis, (iv) Exploration and (v) Conclusion and dissemination.
CONCLUSIONS: Adopting formal, structured approaches to benefit-risk assessment was feasible in real-world problems and facilitated clear, transparent decision-making. Prior to this work, no extensive practical application and appraisal of methodologies had been conducted using real-world case examples, leaving users with limited knowledge of their usefulness in the real world. The practical guidance provided here takes us one step closer to a harmonised approach to benefit-risk assessment from multiple perspectives.
Copyright © 2016 John Wiley & Sons, Ltd.

Keywords:  benefit-risk; decision-making; drug development; pharmacoepidemiology; regulation

Mesh:

Year:  2016        PMID: 26800458     DOI: 10.1002/pds.3958

Source DB:  PubMed          Journal:  Pharmacoepidemiol Drug Saf        ISSN: 1053-8569            Impact factor:   2.890


  17 in total

1.  Bayesian credible subgroup identification for treatment effectiveness in time-to-event data.

Authors:  Duy Ngo; Richard Baumgartner; Shahrul Mt-Isa; Dai Feng; Jie Chen; Patrick Schnell
Journal:  PLoS One       Date:  2020-02-26       Impact factor: 3.240

2.  Incorporating Quantitative Patient Preference Data into Healthcare Decision Making Processes: Is HTA Falling Behind?

Authors:  David John Mott
Journal:  Patient       Date:  2018-06       Impact factor: 3.883

Review 3.  Benefit-risk assessment and reporting in clinical trials of chronic pain treatments: IMMPACT recommendations.

Authors:  Bethea A Kleykamp; Robert H Dworkin; Dennis C Turk; Zubin Bhagwagar; Penney Cowan; Christopher Eccleston; Susan S Ellenberg; Scott R Evans; John T Farrar; Roy L Freeman; Louis P Garrison; Jennifer S Gewandter; Veeraindar Goli; Smriti Iyengar; Alejandro R Jadad; Mark P Jensen; Roderick Junor; Nathaniel P Katz; J Patrick Kesslak; Ernest A Kopecky; Dmitri Lissin; John D Markman; Michael P McDermott; Philip J Mease; Alec B O'Connor; Kushang V Patel; Srinivasa N Raja; Michael C Rowbotham; Cristina Sampaio; Jasvinder A Singh; Ilona Steigerwald; Vibeke Strand; Leslie A Tive; Jeffrey Tobias; Ajay D Wasan; Hilary D Wilson
Journal:  Pain       Date:  2021-09-09       Impact factor: 7.926

4.  Value of Information Analysis in Models to Inform Health Policy.

Authors:  Christopher H Jackson; Gianluca Baio; Anna Heath; Mark Strong; Nicky J Welton; Edward C F Wilson
Journal:  Annu Rev Stat Appl       Date:  2022-03-07       Impact factor: 7.917

5.  Advancing regulatory science, advancing regulatory practice.

Authors:  Xavier Kurz
Journal:  Pharmacoepidemiol Drug Saf       Date:  2017-02-21       Impact factor: 2.890

6.  A novel measure of drug benefit-risk assessment based on Scale Loss Score.

Authors:  Gaelle Saint-Hilary; Veronique Robert; Mauro Gasparini; Thomas Jaki; Pavel Mozgunov
Journal:  Stat Methods Med Res       Date:  2018-07-20       Impact factor: 3.021

Review 7.  Benefit-risk evaluation: the past, present and future.

Authors:  Juhaeri Juhaeri
Journal:  Ther Adv Drug Saf       Date:  2019-08-26

8.  Benefit-Risk Assessment of Vaccines. Part II: Proposal Towards Consolidated Standards of Reporting Quantitative Benefit-Risk Models Applied to Vaccines (BRIVAC).

Authors:  Hugo Arlegui; Kaatje Bollaerts; Vincent Bauchau; Gaëlle Nachbaur; Bernard Bégaud; Nicolas Praet
Journal:  Drug Saf       Date:  2020-11       Impact factor: 5.606

9.  Early Health Technology Assessment during Nonalcoholic Steatohepatitis Drug Development: A Two-Round, Cross-Country, Multicriteria Decision Analysis.

Authors:  Aris Angelis; Mark Thursz; Vlad Ratziu; Alastair O'Brien; Lawrence Serfaty; Ali Canbay; Ingolf Schiefke; Joao Bana E Costa; Pascal Lecomte; Panos Kanavos
Journal:  Med Decis Making       Date:  2020-08       Impact factor: 2.583

Review 10.  Benefit-Risk Assessment of Vaccines. Part I: A Systematic Review to Identify and Describe Studies About Quantitative Benefit-Risk Models Applied to Vaccines.

Authors:  Hugo Arlegui; Kaatje Bollaerts; Francesco Salvo; Vincent Bauchau; Gaëlle Nachbaur; Bernard Bégaud; Nicolas Praet
Journal:  Drug Saf       Date:  2020-11       Impact factor: 5.606

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