Literature DB >> 34720809

Patient Preferences: Results of a German Adaptive Choice-Based Conjoint Analysis (Market Research Study Sponsored by Eli Lilly and Company) in Patients on Palliative Treatment for Advanced Breast Cancer.

Mattea Reinisch1, Norbert Marschner2, Thorsten Otto3, Agnieszka Korfel3, Clemens Stoffregen3, Achim Wöckel4.   

Abstract

INTRODUCTION: Integration of patient preferences into shared decision making improves disease-related outcomes, but such data from patients with advanced breast cancer (aBC) are limited. The objective of this study was to demonstrate the relative importance of overall survival (OS) and progression-free survival (PFS) in relation to quality of life (QoL) and therapy-associated side effects from the perspective of patients with aBC.
METHODS: Postmenopausal patients with hormone receptor-positive, human epidermal growth factor receptor 2-negative aBC receiving first- or second-line treatment were recruited throughout Germany. Patient-relevant attributes for aBC therapy assessment were collected using a stepwise multimodal approach. A conjoint matrix was developed, resulting in 2 attributes for therapy goals (OS and PFS), 4 for QoL, and 6 for side effects. An online quantitative survey was then performed using adaptive choice-based conjoint (ACBC) methodology.
RESULTS: The quantitative survey included 104 patients: 67 (64.4%) receiving first-line treatment and 37 (35.6%) receiving second-line treatment. The QoL attribute "physical agility and mobility" received the highest utility score (19.4 of 100%), reflecting the greatest importance to patients, followed by treatment goals (OS [15.2%] and PFS [14.4%]). Therapy-related side effects were less important, with nausea/vomiting being the most important (9.3%), followed by infection (6.4%) and hair loss (5.0%). The McFadden pseudo R2 (0.805), the root likelihood (0.864), and the χ2 test (2,809.041; p < 0.0001) indicated a very good fit of the statistical model.
CONCLUSION: Using ACBC analysis, it appears that QoL, OS, and PFS are most important to postmenopausal patients with aBC in relation to cancer treatment. Side effects seem to be less important if OS or PFS are prolonged and the QoL is maintained. Thus, QoL, OS, and PFS should be considered equally when making treatment decisions in aBC.
Copyright © 2021 by S. Karger AG, Basel.

Entities:  

Keywords:  Advanced breast cancer; Conjoint analysis; Patient preferences; Survival; Treatment

Year:  2021        PMID: 34720809      PMCID: PMC8543321          DOI: 10.1159/000513139

Source DB:  PubMed          Journal:  Breast Care (Basel)        ISSN: 1661-3791            Impact factor:   2.860


  18 in total

1.  Why should regulators consider using patient preferences in benefit-risk assessment?

Authors:  Janine A van Til; Maarten J Ijzerman
Journal:  Pharmacoeconomics       Date:  2014-01       Impact factor: 4.981

2.  Patient preferences for diabetes treatment attributes and drug classes.

Authors:  Emuella M Flood; Kelly F Bell; Marie C de la Cruz; France M Ginchereau-Sowell
Journal:  Curr Med Res Opin       Date:  2016-12-02       Impact factor: 2.580

3.  Patient preferences and treatment adherence among women diagnosed with metastatic breast cancer.

Authors:  Marco daCosta DiBonaventura; Ronda Copher; Enrique Basurto; Claudio Faria; Rose Lorenzo
Journal:  Am Health Drug Benefits       Date:  2014-10

4.  Trade-off preferences regarding adjuvant endocrine therapy among women with estrogen receptor-positive breast cancer.

Authors:  H Wouters; G A Maatman; L Van Dijk; M L Bouvy; R Vree; E C G Van Geffen; J W Nortier; A M Stiggelbout
Journal:  Ann Oncol       Date:  2013-05-23       Impact factor: 32.976

5.  Use of conjoint analysis to assess breast cancer patient preferences for chemotherapy side effects.

Authors:  Kathleen Beusterien; Jessica Grinspan; Iryna Kuchuk; Sasha Mazzarello; Susan Dent; Stan Gertler; Nathaniel Bouganim; Lisa Vandermeer; Mark Clemons
Journal:  Oncologist       Date:  2014-01-28

6.  Adaptive choice-based conjoint analysis: a new patient-centered approach to the assessment of health service preferences.

Authors:  Charles E Cunningham; Ken Deal; Yvonne Chen
Journal:  Patient       Date:  2010-12-01       Impact factor: 3.883

Review 7.  Sample Size Requirements for Discrete-Choice Experiments in Healthcare: a Practical Guide.

Authors:  Esther W de Bekker-Grob; Bas Donkers; Marcel F Jonker; Elly A Stolk
Journal:  Patient       Date:  2015-10       Impact factor: 3.883

8.  Requirements for benefit assessment in Germany and England - overview and comparison.

Authors:  Victor Ivandic
Journal:  Health Econ Rev       Date:  2014-08-28

9.  Patients' preferences for postmenopausal hormone receptor-positive, human epidermal growth factor receptor 2-negative advanced breast cancer treatments in Japan.

Authors:  Yukie Omori; Sotaro Enatsu; Zhihong Cai; Hiroshi Ishiguro
Journal:  Breast Cancer       Date:  2019-04-04       Impact factor: 4.239

Review 10.  Current Landscape of Targeted Therapies for Hormone-Receptor Positive, HER2 Negative Metastatic Breast Cancer.

Authors:  Tarah J Ballinger; Jason B Meier; Valerie M Jansen
Journal:  Front Oncol       Date:  2018-08-10       Impact factor: 6.244

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