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Understanding Preferences, Needs, and Expectations for Pharmaceutical Treatment of Symptomatic Uterine Fibroids Based on Surveys of Healthcare Providers and Patients

Title: Understanding Preferences, Needs, and Expectations for Pharmaceutical Treatment of Symptomatic Uterine Fibroids Based on Surveys of Healthcare Providers and Patients
Authors: Madueke-Laveaux,O; Hunsche,Elke; Rakov,Viatcheslav; Lickert,Cassandra; Hauber,Brett; Sukumar,Ramamirtham; Agarwal,Sanjay
Publisher Information: Dove Press
Publication Year: 2025
Collection: Dove Medical Press
Subject Terms: International Journal of Women's Health
Description: O Sandra Madueke-Laveaux,1 Elke GI Hunsche,2 Viatcheslav G Rakov,2 Cassandra Lickert,3 Brett Hauber,4 Ramamirtham Sukumar,5 Sanjay K Agarwal6 1Department of Obstetrics and Gynecology, University of Chicago, Chicago, IL, USA; 2Sumitomo Pharma Switzerland GmbH, Basel, Switzerland; 3Sumitomo Pharma America, Marlborough, MA, USA; 4Pfizer Inc., New York, NY, USA; 5Optimal Strategix Group, Bensalem, PA, USA; 6Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Diego, CA, USACorrespondence: Elke GI Hunsche, Sumitomo Pharma Switzerland GmbH, Basel, Switzerland, Tel +41 43 210 8129, Email hunsche07@gmail.comBackground: Limited evidence is available regarding preferences of women with uterine fibroids (UF) and treating healthcare providers (HCPs) regarding treatment attributes; this evidence could contribute to patient-centered shared decision-making. The aim of this study was to understand HCP and patient preferences when evaluating pharmaceutical treatments for symptomatic UF, and to identify HCP and patient segments that differ in their preferences.Methods: HCPs involved in UF management and patients diagnosed with UF completed a survey assessing the importance of treatment attributes in the UF therapy choice; an adaptive self-explication method was applied to estimate relative importance (RI), indexed to an average of 100. Attributes with RI > 100 or < 100 indicated a larger or lesser influence, respectively, in driving treatment choice. A clustering (K-means) algorithm was used to determine HCP and patient segments. Attribute RI was estimated for the overall sample and segments. Segment-specific RI estimates that were > 10 points higher or lower than the overall study population mean were considered key differentiating drivers for that segment.Results: In total, 375 HCPs and 300 patients responded to the survey. Four HCP and four patient segments were identified. Healthcare provider segments identified were: “efficacy-focused” (n=99), ...
Document Type: article in journal/newspaper
File Description: text/html
Language: English
Availability: https://www.dovepress.com/understanding-preferences-needs-and-expectations-for-pharmaceutical-tr-peer-reviewed-fulltext-article-IJWH
Rights: info:eu-repo/semantics/openAccess
Accession Number: edsbas.7B3E7FF9
Database: BASE