Chapman G B, Elstein A S, Kuzel T M, Nadler R B, Sharifi R, Bennett C L
Rutgers University, Department of Psychology, Piscataway, NJ 08854-8020, USA.
Qual Life Res. 1999 May;8(3):171-80. doi: 10.1023/a:1008850610569.
Multi-attribute utility theory (MAUT) provides a way to model decisions involving trade-offs among different aspects or goals of a problem. We used MAUT to model prostate cancer patients' preferences for their own health state and we compared this model to patients' global judgments of health state utility. 57 patients with prostate cancer (mean age = 70) at two Chicago Veterans Administration health clinics were asked to evaluate health states described in terms of five health attributes affected by prostate cancer: pain, mood, sexual function, bladder and bowel function, and fatigue and energy. Each attribute had three levels that were used to form three clinically realistic health state descriptions (A = high, B = moderate, C = low). A fourth personalized health description (P) matched the patient's current health. We first measured patients' preferences using time trade-off (TTO) judgments for the three health states (A, B, and C) and for their own current health state (P). The TTO for the patient's own health state (P) was standardized by comparing it to TTO judgments for states A and C. We next constructed a multi-attribute model using the relative importance of the five attributes. The MAU scores were moderately correlated with the TTO preference judgments for the personalized state (Pearson r = 0.38, N = 57, p < 0.01). Thus, patients' preference judgments are moderately consistent and systematic. MAUT appears to be a potentially feasible method for evaluating preferences of prostate cancer patients and may prove helpful in assisting with patient decision making.
多属性效用理论（MAUT）提供了一种对涉及问题不同方面或目标之间权衡的决策进行建模的方法。我们使用MAUT对前列腺癌患者对自身健康状态的偏好进行建模，并将该模型与患者对健康状态效用的总体判断进行比较。在芝加哥的两家退伍军人管理局医疗诊所，57名前列腺癌患者（平均年龄 = 70岁）被要求对由前列腺癌影响的五个健康属性所描述的健康状态进行评估：疼痛、情绪、性功能、膀胱和肠道功能以及疲劳和精力。每个属性有三个级别，用于形成三种符合临床实际的健康状态描述（A = 高，B = 中，C = 低）。第四个个性化健康描述（P）与患者当前的健康状况相匹配。我们首先使用时间权衡（TTO）判断来测量患者对三种健康状态（A、B和C）以及他们自己当前健康状态（P）的偏好。通过将患者自身健康状态（P）的TTO与状态A和C的TTO判断进行比较，对其进行标准化。接下来，我们使用五个属性的相对重要性构建了一个多属性模型。MAU得分与个性化状态的TTO偏好判断呈中度相关（Pearson相关系数r = 0.38，N = 57，p < 0.01）。因此，患者的偏好判断具有一定程度的一致性和系统性。MAUT似乎是一种评估前列腺癌患者偏好的潜在可行方法，可能有助于辅助患者进行决策。
