STATISTICAL METHODS FOR QUALITY-OF-LIFE OUTCOME RESEARCH

患者的生活质量结果测量正在发挥越来越大的作用 在决定新技术的有效性和净效益方面发挥重要作用 以及现有的药物疗法。对《质量》的解读 用于治疗决策和政策规划的生活数据需要) 关于测量和统计特性的有效假设 评估中使用的生活质量量表，b)代表性 分析模型将患者特定的生活质量结果与 有效性、效用、成本和总体净收益，以及3)适当 推论统计方法学检验治疗效果和 不同之处。虽然有大量的文献在争论 各种模型、工具和工具的含义、有用性和有效性 生活质量的定义，很少有研究集中在这些方面 影响生活质量分析和解释的几个问题 用于确定以下各项相对风险和收益的结果数据 可供选择的药物方案。这次会议的主要目标是 建议是a)评估和分析当前和潜在的测量 和统计技术在生活质量相关患者中的应用 通过对治疗和统计的详尽回顾得出的结果 文献，b)完善现有的分析和统计方法 因此，它适合于治疗科学和评估 药物疗法和c)开发数据分析、演示 三个主要生活质量分析领域的项目，通过应用 现有生活质量临床试验的选择方法 高血压(n=2500)、糖尿病(n=300)和艾滋病毒(n= 1000)。所有这些数据库都包含大量关于质量的前瞻性数据 替代药物的随机多中心临床试验期间的寿命 心理治疗。模型评审、开发和管理的三步法 将在以下主要领域进行演示：1) 健康相关问卷的信度、反应度、效度和敏感度 生活质量测量；2)多变量、纵向模型(两者 参数和非参数)以评估生活质量治疗效果 在随机临床试验和3)汇总估计的全球模型中 用于质量调整的生存、成本效益、成本效用 和健康状态转移马尔可夫模型。它的最终产品是 研究将是生活质量分析的全面提纲 适用于生活质量的模型、适当的统计方法 相关的治疗结果研究和实际数据分析 对临床研究人员、卫生政策有用的示范项目 规划者和监管机构负责设计、评估和 解释药物疗法的生活质量研究。

Quality-of-life patient outcomes measures are playing an increasingly important role in determining the effectiveness and net benefit of new and existing pharmaceutical therapies. The interpretation of quality-of- life data for therapeutic decision making and policy planning requires a) valid assumptions concerning measurement and statistical properties of the quality-of-life scales used in assessment, b) representative analytical models relating patient-specific quality-of-life outcomes to effectiveness, utility, costs and overall net benefits and 3) appropriate inferential statistical methodology to test therapeutic effects and differences. While a large body of literature exists debating the meaning, usefulness and validity of various models, instruments and definitions of quality of life, little research has focused upon those issues impacting on the analysis and interpretation of quality-of-life outcome data used in determining the relative risks and benefits of alternative pharmaceutical regimens. The major objectives of this proposal are a) to evaluate and analyze current and potential measurement and statistical techniques used in quality-of-life related patient outcomes through an exhaustive review of the therapeutic and statistical literature, b) to refine existing analytical and statistical methodology so that it is appropriate for therapeutic science and the evaluation of pharmacologic therapies and c) to develop data analysis, demonstration projects within three major quality-of-life analytical areas by applying the selected methods to existing quality-of-life clinical trials databases of hypertension (n = 2,500) diabetes (n = 300) and HIV (n = 1000). All these databases contain extensive prospective data on quality of life during randomized multicenter clinical trials of alternative drug therapy. The three-step methodology of model review, development and demonstration will be employed in the following major areas: 1) reliability, responsiveness, validity and sensitivity of health-related quality-of-life measures; 2) multivariate, longitudinal models (both parametric and nonparametric) to assess quality-of-life treatment effects in randomized clinical trials and 3) global models for summary estimates for use in quality-adjusted survival, cost-effectiveness, cost-utility and health state transition Markov models . The final product of this research will be a comprehensive compendium of quality-of-life analytical models, appropriate statistical methods suitable for quality-of-life related therapeutic outcomes research, and practical data analysis demonstration projects useful to clinical investigators, health policy planners and regulatory agencies for designing, evaluating and interpreting quality-of-life studies of pharmacologic therapies.