Stakeholder-informed positivity thresholds for disease markers and risk scores: a methodological framework and an application in obstructive lung disease.

Autor: Sadatsafavi M; Respiratory Evaluation Sciences Program, Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada; Collaboration for Outcomes Research and Evaluation, University of British Columbia, Vancouver, BC, Canada. Electronic address: mohsen.sadatsafavi@ubc.ca., Khakban A; Collaboration for Outcomes Research and Evaluation, University of British Columbia, Vancouver, BC, Canada., Mohammadi T; Centre for Advancing Health Outcomes, St Paul's Hospital, Vancouver, BC, Canada., Gupta S; Keenan Research Center in the Li Ka Shing Knowledge Institute of St. Michael's Hospital, University of Toronto, Toronto, ON, Canada., Bansback N; Centre for Advancing Health Outcomes, St Paul's Hospital, Vancouver, BC, Canada; School of Population and Public Health, The University of British Columbia, Vancouver, BC, Canada.
Jazyk: angličtina
Zdroj: Journal of clinical epidemiology [J Clin Epidemiol] 2024 Aug 30; Vol. 175, pp. 111509. Date of Electronic Publication: 2024 Aug 30.
DOI: 10.1016/j.jclinepi.2024.111509
Abstrakt: Objectives: A positivity threshold is often applied to markers or predicted risks to guide disease management. These thresholds are often decided exclusively by clinical experts despite being sensitive to the preferences of patients and general public as ultimate stakeholders.
Study Design and Setting: We propose an analytical framework for quantifying the net benefit (NB) of an evidence-based positivity threshold based on combining preference-sensitive (eg, how individuals weight benefits and harms of treatment) and preference-agnostic (eg, the magnitude of benefit and the risk of harm) parameters. We propose parsimonious choice experiments to elicit preference-sensitive parameters from stakeholders, and targeted evidence synthesis to quantify the value of preference-agnostic parameters. We apply this framework to maintenance of azithromycin therapy for chronic obstructive pulmonary disease using a discrete choice experiment to estimate preference weights for attribute level associated with treatment. We identify the positivity threshold on 12-month moderate or severe exacerbation risk that would maximize the NB of treatment in terms of severe exacerbations avoided.
Results: In the case study, the prevention of moderate and severe exacerbations (benefits) and the risk of hearing loss and gastrointestinal symptoms (harms) emerged as important attributes. Four hundred seventy seven respondents completed the discrete choice experiment survey. Relative to each percent risk of severe exacerbation, preference weights for each percent risk of moderate exacerbation, hearing loss, and gastrointestinal symptoms were 0.395 (95% confidence interval [CI] 0.338-0.456), 1.180 (95% CI 1.071-1.201), and 0.253 (95% CI 0.207-0.299), respectively. The optimal threshold that maximized NB was to treat patients with a 12-month risk of moderate or severe exacerbations ≥12%.
Conclusion: The proposed methodology can be applied to many contexts where the objective is to devise positivity thresholds that need to incorporate stakeholder preferences. Applying this framework to chronic obstructive pulmonary disease pharmacotherapy resulted in a stakeholder-informed treatment threshold that was substantially lower than the implicit thresholds in contemporary guidelines.
Plain Language Summary: Doctors often compare disease markers (such as laboratory results) or risk scores for a patient with cut-off values from guidelines to decide which patients need to be treated. For example, guidelines recommend that patients whose 10-year risk of heart attack is more than 10% be given statin pills. However, guidelines that recommend such treatment rules might not consider what matters most to patients (like how much they do not like side effects of the drugs). In this study, we propose a mathematical method where preferences of individuals on the trade-off between treatment benefits and harms can be used to determine the best treatment rule. We apply this method to the choice of antibiotic therapy for patients with lung airway diseases. We find that, given patient and public preferences on treatment benefit and risks, those with a 12% or more risk of experiencing a lung attack should receive antibiotic therapy. This patient-oriented cut-off is significantly lower than the cut-off values currently used by guidelines, which are in the 60%-70% range. We recommend applying this method whenever scientists must make recommendations on treatment rules where patient or public preferences might influence those rules.
Competing Interests: Declaration of competing interest M. S. has received financial support from the British Columbia SUPPORT Unit and the Canadian Institutes of Health Research. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this article.
(Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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