Patient Preferences for Medications in Managing Type 2 Diabetes Mellitus: A Discrete Choice Experiment
To quantify patients’ maximum acceptable risk (MAR) of urinary and genital tract infections (UGTI) in exchange for benefits associated with treatments for managing type 2 diabetes mellitus (T2DM). In a discrete choice experiment, adult patients with T2DM and currently on metformin and/or sulphonylur...
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Veröffentlicht in: | Value in health 2020-07, Vol.23 (7), p.842-850 |
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Zusammenfassung: | To quantify patients’ maximum acceptable risk (MAR) of urinary and genital tract infections (UGTI) in exchange for benefits associated with treatments for managing type 2 diabetes mellitus (T2DM).
In a discrete choice experiment, adult patients with T2DM and currently on metformin and/or sulphonylurea (first-line treatments) were asked to choose between 2 hypothetical medications defined by 6 attributes: years of medication effectiveness in controlling blood glucose, weight reduction, UGTI risk, risk of hospitalization from heart failure, all-cause mortality risk, and out-of-pocket medication cost. We used latent class logistic regression parameters to estimate the conditional relative importance of treatment attributes and MAR of UGTI for various treatment benefits.
A 2-class latent class model was identified as the best fit for the responses from 147 patients. The first class (49% of sample), termed as “survival-conscious,” stated that they were willing to accept 46% (95% confidence interval [CI]: 2%-90%) UGTI risk in exchange for a reduction from 6% to 1% in all-cause mortality risk. The second class (51% of sample), termed as “UGTI/cost-conscious” were willing to accept significantly lower (6%; CI: 2%-11%, and 5%; CI: 2%-8%) UGTI risk in exchange for the same reduction in all-cause mortality and hospitalization risks, respectively.
On average, patients were willing to trade higher UGTI risk for a more effective medication. Our findings suggest that physicians should present the benefits and potential side effects of all available treatments and consider patient preferences in their treatment recommendations. |
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ISSN: | 1098-3015 1524-4733 |
DOI: | 10.1016/j.jval.2020.01.023 |