Patient Preferences in Targeted Pharmacotherapy for Cancers: A Systematic Review of Discrete Choice Experiments

Abstract

Background Targeted pharmacotherapy has been increasingly applied in cancer treatment due to its breakthroughs. However, the unmet needs of cancer patients are still significant, highlighting the urgency to investigate patient preferences. It is unclear how patients deliberate their choices between different aspects of targeted therapy, including cost, efficacy, and adverse events. Since discrete choice experiments (DCEs) have been widely applied to patient preference elicitation, we reviewed DCEs on targeted therapy for different cancers. We also synthesized evidence on the factors influencing patients' choices and their willingness-to-pay (WTP) for survival when treated by targeted therapy. Methods We searched databases, including PubMed, EMBASE and MEDLINE, up to August 16, 2022, supplemented by a reference screening. The attributes from the selected studies were categorized into three groups: outcomes, costs, and process. We also calculated the relative importance of attributes and WTP for survival whenever possible. The purpose, respondents, explanation, findings, significance (PREFS) checklist was used to evaluate the quality of the included DCE studies. Results The review identified 34 eligible studies from 13 countries covering 14 cancers, such as breast, ovarian, kidney, prostate, and skin cancers. It also reveals a rising trend of DCEs on this topic, as most studies were published after 2018. We found that patients placed higher weights on the outcome (e.g., overall survival) and cost attributes than on process attributes.

Blood Donors' Preferences Toward Incentives for Donation in China

“…The comparison of the results from the 2 models indicated that the addition of the opt-out option did not significantly change the respondents’ preferences. This finding contrasts with previous literature suggesting that restricted choice tasks may bias the analysis results . One possible explanation is that all respondents were donors who had already revealed their preference for blood donation.…”

“…Research is needed for comprehending the utility of nonmonetary incentives for blood donation within the context of a voluntary nonremunerated system. The discrete choice experiment (DCE) is an established stated preference approach, designed to simulate the impact of various attributes of a good or service on individual choice . In a DCE, respondents are asked to choose between 2 or more hypothetical incentive scenarios specified by several dimensions (called attributes ) that differ in their settings (called levels ) between the alternatives .…”

Patient versus physician preferences for lipid‐lowering drug therapy: A discrete choice experiment

“…Numerous patient preference studies have consistently highlighted efficacy and safety as the most important attributes 14,30 . Our study confirmed and extended these findings, revealing that the mode and frequency of administration also influenced patient preferences, although to a lesser degree than the risk of liver damage.…”

“…The attributes of DCE in the study were based on a comprehensive literature review and focus group discussion. Our literature review on DCEs for drug treatment preferences revealed that these attributes commonly encompass outcome (e.g., efficacy and adverse effects), process (e.g., mode of administration) and cost 9,10,14–18 . Additionally, we conducted a literature review to gain insights into the characteristics of lipid‐lowering drugs, and the search strategy can be found in Supporting Information S1: Appendix .…”

Preferences of patients with diabetes mellitus for primary healthcare institutions: a discrete choice experiment in China

“…Relative Attribute Importance (RAI) score of an attribute is equal to the percentage of the preference weight of this attribute (utility value of the best level minus that of the worst level within the same attribute) in the sum of all attribute weights 30. We divide the utility value of the attribute level by the utility value of the cost attribute to derive the willingness to pay (WTP) of an attribute level 31. The WTP results provide attribute trade-off information and express how much additional cost patients are willing to pay for changes in other attributes.…”