Liu Frank Xiaoqing, Witt Edward A, Ebbinghaus Scot, DiBonaventura Beyer Grace, Shinde Reshma, Basurto Enrique, Joseph Richard W
Merck & Co., Inc., Kenilworth, NJ, USA.
Kantar Health, New York, NY, USA.
Patient Prefer Adherence. 2017 Aug 14;11:1389-1399. doi: 10.2147/PPA.S140226. eCollection 2017.
To examine and compare patient and oncologist preferences for advanced melanoma treatment attributes and to document their trade-offs for benefits with risks.
A discrete choice experiment (DCE) was conducted among advanced melanoma patients and oncologists. Qualitative pilot testing was used to inform the DCE design. A series of scenarios asked stakeholders to choose between two hypothetical medications, each with seven attributes: mode of administration (MoA), dosing schedule (DS), median duration of therapy (MDT), objective response rate (ORR), progression-free survival (PFS), overall survival (OS), and grade 3-4 adverse events (AEs). Hierarchical Bayesian logistic regression models were used to determine patients' and oncologists' choice-based preferences, analysis of variance models were used to estimate the relative importance of attributes, and independent -tests were used to compare relative importance estimates between stakeholders.
In total, 200 patients and 226 oncologists completed the study. OS was most important to patients (33%), followed by AEs (29%) and ORR (25%). For oncologists, AEs were most important (49%), followed by OS (34%) and ORR (12%). An improvement from 55% to 75% in 1-year OS was valued similar in magnitude to a 23% decrease (from 55% to 32%) in likelihood of AEs for oncologists.
Patients valued OS, AEs, and ORR sequentially as the most important attributes in making a treatment decision, whereas oncologists valued AEs most, followed by OS and ORR. In comparison, patients differed significantly from oncologists on the importance of ORR, AEs, and PFS, but were consistent in OS and the rest of attributes.
研究并比较患者和肿瘤学家对晚期黑色素瘤治疗属性的偏好,并记录他们在收益与风险之间的权衡。
在晚期黑色素瘤患者和肿瘤学家中进行了一项离散选择实验(DCE)。采用定性预试验为DCE设计提供信息。一系列情景要求利益相关者在两种假设药物之间进行选择,每种药物具有七个属性:给药方式(MoA)、给药方案(DS)、中位治疗持续时间(MDT)、客观缓解率(ORR)、无进展生存期(PFS)、总生存期(OS)和3-4级不良事件(AE)。使用分层贝叶斯逻辑回归模型确定患者和肿瘤学家基于选择的偏好,使用方差分析模型估计属性的相对重要性,并使用独立检验比较利益相关者之间的相对重要性估计。
共有200名患者和226名肿瘤学家完成了研究。总生存期对患者最重要(33%),其次是不良事件(29%)和客观缓解率(25%)。对于肿瘤学家来说,不良事件最重要(49%),其次是总生存期(34%)和客观缓解率(12%)。1年总生存期从55%提高到75%的价值在程度上与肿瘤学家不良事件发生率降低23%(从55%降至32%)相似。
患者在做出治疗决策时依次将总生存期、不良事件和客观缓解率视为最重要的属性,而肿瘤学家最看重不良事件,其次是总生存期和客观缓解率。相比之下,患者在客观缓解率、不良事件和无进展生存期的重要性方面与肿瘤学家有显著差异,但在总生存期和其他属性方面是一致的。