Literature DB >> 29051108

A Bayesian model that jointly considers comparative effectiveness research and patients' preferences may help inform GRADE recommendations: an application to rheumatoid arthritis treatment recommendations.

Glen S Hazlewood1, Claire Bombardier2, George Tomlinson3, Deborah Marshall4.   

Abstract

OBJECTIVES: The objective of the study was to estimate the preferred treatment for early rheumatoid arthritis using a novel Bayesian approach that jointly considers patients' preferences and comparative effectiveness research. STUDY DESIGN AND
SETTING: We estimated the preferred treatment using patients' preferences measured in a discrete-choice experiment to apply weights to benefit and harm outcomes from a network meta-analysis and other considerations (dosing, rare adverse events). Using Bayesian analyses, we considered the variability in patients' preferences and the imprecision in both patients' preferences and the treatment effects; all key considerations in the Grading of Recommendations Assessment, Development, and Evaluation approach.
RESULTS: We estimated that most patients in our population would prefer triple therapy as initial treatment (78%) or after an inadequate response to methotrexate (62%). The probability of choosing triple therapy as initial treatment was further from 50% (the point of indifference) for more patients, making our prediction more confident, and suggesting a stronger recommendation could be made. After an inadequate response to methotrexate, the choice was more split, suggesting a decision aid may be helpful.
CONCLUSION: Using a novel approach, we estimated that many patients with early rheumatoid arthritis may prefer triple therapy to other treatment options, in contrast to existing guidelines. This offers an approach that may help inform Grading of Recommendations Assessment, Development, and Evaluation treatment recommendations.
Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Antirheumatic agents; Comparative effectiveness research; Patient preference; Practice guideline; Rheumatoid arthritis

Mesh:

Substances:

Year:  2017        PMID: 29051108     DOI: 10.1016/j.jclinepi.2017.10.003

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  6 in total

Review 1.  Patient preferences for rheumatoid arthritis treatment.

Authors:  Betty Hsiao; Liana Fraenkel
Journal:  Curr Opin Rheumatol       Date:  2019-05       Impact factor: 5.006

2.  P values in display items are ubiquitous and almost invariably significant: A survey of top science journals.

Authors:  Ioana Alina Cristea; John P A Ioannidis
Journal:  PLoS One       Date:  2018-05-15       Impact factor: 3.240

Review 3.  Defining certainty of net benefit: a GRADE concept paper.

Authors:  Brian S Alper; Peter Oettgen; Ilkka Kunnamo; Alfonso Iorio; Mohammed Toseef Ansari; M Hassan Murad; Joerg J Meerpohl; Amir Qaseem; Monica Hultcrantz; Holger J Schünemann; Gordon Guyatt
Journal:  BMJ Open       Date:  2019-06-04       Impact factor: 2.692

Review 4.  Systematic review of quantitative preference studies of treatments for rheumatoid arthritis among patients and at-risk populations.

Authors:  Gwenda Simons; Joshua Caplan; Rachael L DiSantostefano; Jorien Veldwijk; Matthias Englbrecht; Karin Schölin Bywall; Ulrik Kihlbom; Karim Raza; Marie Falahee
Journal:  Arthritis Res Ther       Date:  2022-02-22       Impact factor: 5.156

5.  Using a Discrete-Choice Experiment in a Decision Aid to Nudge Patients Towards Value-Concordant Treatment Choices in Rheumatoid Arthritis: A Proof-of-Concept Study.

Authors:  Glen S Hazlewood; Deborah A Marshall; Claire E H Barber; Linda C Li; Cheryl Barnabe; Vivian Bykerk; Peter Tugwell; Pauline M Hull; Nick Bansback
Journal:  Patient Prefer Adherence       Date:  2020-05-18       Impact factor: 2.711

6.  Patient preferences for maintenance therapy in Crohn's disease: A discrete-choice experiment.

Authors:  Glen S Hazlewood; Gyanendra Pokharel; Robert Deardon; Deborah A Marshall; Claire Bombardier; George Tomlinson; Christopher Ma; Cynthia H Seow; Remo Panaccione; Gilaad G Kaplan
Journal:  PLoS One       Date:  2020-01-16       Impact factor: 3.240

  6 in total

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