Systematic Review of Patient Preference Studies in Non-metastatic Breast Cancer Adjuvant Medication Therapy: Attribute Selection.

Context: Breast cancer poses significant challenges due to its high incidence and prevalence, necessitating heightened attention. Understanding how patients prioritize different treatment options based on various attributes can assist healthcare decision-makers in maximizing patient utility. The discrete choice experiment, a conjoint method, facilitates preference elicitation by presenting different attributes and choices. This systematic review aims to identify key factors in patient preference research related to adjuvant treatment for early breast cancer characterized by hormone receptor-positive, HER2-negative status.

Evidence Acquisition: PubMed, Embase, Web of Science, and Scopus were searched from 01.01.2000 to 31.03.2023. Original English articles reporting patient preferences in adjuvant breast cancer treatment were retrieved based on predefined inclusion and exclusion criteria. Included studies were examined through a narrative synthesis approach, with descriptive statistics employed for analysis.

Results: Out of 1163 articles reviewed, four met the inclusion criteria and were conducted in the USA, Canada, and the Netherlands. Attributes extracted from all studies included alopecia, sensory neuropathy, motor neuropathy, myalgia/arthralgia, nausea, vomiting, fatigue, neutropenia, mucositis/stomatitis, hand-foot syndrome, diarrhea, prevention of breast cancer recurrence, osteoporosis, risk of endometrial cancer, joint and muscle pain, fluid retention, libido decrease, hot flashes, ECG monitoring, efficacy, treatment regimen, 5-year invasive disease-free survival (iDFS), dosing schedule, and treatment duration. The most frequently reported attributes were side effects, efficacy, and treatment regimen. Systematic review was commonly used to determine which attributes and levels to include. The minimum number of attributes identified per study was seven, and the maximum was 12. Sample sizes ranged from 102 to 300, with none of the studies mentioning the method of sample size estimation. Ordinary Least Squares, logistic regression, and hierarchical Bayes regression were the most frequent analysis methods.

Conclusions: Side effects, 5-year iDFS, and treatment regimen are three attributes identified for conducting discrete choice experiment studies. Utilizing conjoint analysis to assess patient preferences for breast cancer treatment can aid in selecting optimal treatment regimens and improving patient adherence. Moreover, adhering to guidelines for developing experimental designs and conducting data analysis is essential for yielding robust results when employing preference elicitation methods.