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Published on: August 1, 2019
Patient preferences for the diagnosis of coeliac disease: A discrete choice experiment
Mohamed G Shiha1,2, Nyantara Wickramasekera3, Suneil A Raju1,2
1Division of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Sheffield, UK.
Background:
There is potential for a paradigm shift from a biopsy-to a serology-based diagnosis of coeliac disease in selected adult patients. However, it remains unknown if this approach would be acceptable to patients. We aimed to explore patients' preferences regarding the no-biopsy approach for coeliac disease diagnosis.
Methods:
We developed a discrete choice experiment survey containing 12 different scenarios with two possible alternatives (endoscopy & biopsy or serology) to estimate patient preferences. The scenarios were based on 5 attributes: risk of false positive results, risk of missed diagnosis, waiting time to start treatment, risk of complications, discomfort, or pain. Patient preferences and the relative importance of the attributes were estimated using a mixed logit model.
Results:
In total, 385 people (70.6% female, 98.2% white) across the four nations of the United Kingdom completed the survey. Respondents preferred a serology-based diagnosis over endoscopy and duodenal biopsies (59% vs. 41%, β coefficient 1.54, p < 0.001). Diagnostic test accuracy (p < 0.001), shorter waiting time to start treatment (p < 0.001), and discomfort levels during the procedure (p < 0.001) were the most important attributes to respondents. The risk of complications, including perforation and bleeding, did not significantly influence respondents' choices. Respondents with previous endoscopy experience were more willing to undergo endoscopy compared with those who never had one.
Conclusion:
The no-biopsy approach to diagnosing coeliac disease is acceptable and preferred by patients over endoscopy and biopsy. Our findings highlight the importance of patient-centred care and shared decision-making in guiding diagnostic strategies for optimal patient outcomes.
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