Clinical Excellence Research Center, Department of Medicine, Stanford University, Stanford, CA USA.
Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, CA, USA.
Med Decis Making. 2019 Oct;39(7):816-826. doi: 10.1177/0272989X19873667. Epub 2019 Sep 26.
. Conjoint analysis is widely used in studies of consumer preference but has only recently been applied to measure patient utilities for health outcomes. We compared the reliability, feasibility, and internal and predictive validity of conjoint scaling methods against better established rating scale and time tradeoff methods for assessing prostate cancer utilities in men at risk for prostate cancer. . In total, 194 men who were biopsy negative for prostate cancer were randomly assigned to complete 2 preference assessment modules, either conjoint analysis and a rating scale module or conjoint analysis and a time tradeoff module. Each participant's most important attribute was identified and evaluated in relation to age group (age <65, age 65 and older), education (high school, some college, college graduate), race/ethnicity (white, black, Latino), and relationship status (in significant relationship v. not). The methods were also evaluated in terms of ease of use and satisfaction. . Rating scales were rated as easiest to use and respondents were more satisfied with rating scales and conjoint in comparison to time tradeoffs. Rating scales and conjoint measures demonstrated significantly higher internal validity compared to time tradeoff when evaluated through of the fitted utility function. The 3 methods were similar in terms of predictive validity, but conjoint analysis outperformed the rating scale method when patients were presented with novel combinations of attribute levels (68% correct v. 43%, = 0.003). . Rating scales and conjoint analysis exercises offer greater ease of use and higher satisfaction when measuring patient preferences in men biopsied for prostate cancer in comparison to time tradeoff exercises. Conjoint analysis may be a more robust approach to preference measurement for men at risk for prostate cancer.
联合分析被广泛应用于消费者偏好研究，但直到最近才被用于衡量患者对健康结果的效用。我们比较了联合量表方法的可靠性、可行性以及内部和预测有效性，这些方法与更成熟的评分量表和时间权衡方法相比，用于评估有前列腺癌风险的男性的前列腺癌效用。
共有 194 名前列腺癌活检阴性的男性被随机分配完成 2 个偏好评估模块，要么是联合分析和评分量表模块，要么是联合分析和时间权衡模块。确定了每个参与者最重要的属性，并根据年龄组（<65 岁，65 岁及以上）、教育程度（高中、部分大学、大学毕业）、种族/民族（白人、黑人、拉丁裔）和关系状况（有重要关系与没有）对其进行评估。还根据易用性和满意度评估了这些方法。
评分量表被评为最易用，与时间权衡相比，受访者对评分量表和联合分析的满意度更高。与时间权衡相比，评分量表和联合分析在评估拟合效用函数的 6 个方面时，表现出更高的内部有效性。在预测有效性方面，这 3 种方法相似，但当向患者呈现属性水平的新组合时，联合分析比评分量表方法表现更好（68%正确比 43%，= 0.003）。
与时间权衡相比，评分量表和联合分析在测量接受前列腺癌活检的男性患者偏好时，具有更高的易用性和满意度。对于有前列腺癌风险的男性，联合分析可能是一种更稳健的偏好测量方法。
