OP03 Patient Characteristics Affect Their Treatment Choice: A Discrete Choice Experiment With Breast Cancer Patients In Six European Countries

Abstract

Introduction

The evolution of breast cancer treatments over the last decade has resulted in tailored therapies for the different types and stages of breast cancer. Each treatment has a profile of benefits and adverse effects which are taken into consideration when planning a treatment pathway. The objective of this study is to examine whether patients’ preferences are in line with what is considered important from policy-makers viewpoint.

Methods

An online discrete choice experiment (DCE) was conducted in six European countries (France, Germany, Ireland, Poland, Spain, UK) with breast cancer (BC) patients. The DCE comprised of six attributes: overall survival (OS), hyperglycaemia, rash, pain, functional well-being (FWB) and out-of-pocket payment (OOP). Sixteen choice sets with two hypothetical treatments and a “no treatment” option were presented. Sociodemographic and disease related data were collected. Heteroscedastic conditional and mixed logistic models accounted for scale and preference heterogeneity between countries and patients respectively. Latent class analysis categorized patients in classes. Marginal rates of substitution (MRS) were estimated for OOP versus the rest of attributes to establish the ranking of preferences for each attribute.

Results

Two hundred and forty-seven patients with advanced or metastatic BC and 314 with early-stage BC responded. Forty-nine percent of patients were less than 44 years old and 65 percent had completed university education. The MRS of the analysis demonstrated that “severe pain” is the highest dis-preferred attribute level, followed by “severe impairment in FWB” and OS. Four classes of patients as “decision-makers” were identified. Additionally, there is sensitivity in preferences for both levels of pain and FWB depending on the stage of the disease.

Conclusions

This study suggests that there is heterogeneity in treatment preferences of breast cancer patients depending on their sociodemographic and disease related characteristics. In combination with clinical guidelines, patient preferences can support the selection and tailoring of treatment options.