Estimating health utilities using QOL data among patients with gyn malignancies

描述(由申请人提供)：本研究项目旨在确定使用生活质量(QOL)数据预测效用的算法是否可与传统的效用评估方法相媲美，这些数据用于经济分析中的质量调整寿命年(QALY)的计算。在已发表的成本效益文献中，妇科癌症的代表性不足，部分原因是在临床试验中缺乏适当的前瞻性数据收集。然而，预期的生活质量数据通常是在临床试验中收集的。从生活质量调查中准确预测效用值的能力可以打开现有的大型临床试验数据库，以便进行更准确的成本效益和比较有效性研究。这项研究将前瞻性和纵向收集妇科癌症患者治疗前、治疗中和治疗后的生活数据的效用和质量。效用预测算法将与实用工具进行比较，并将得到增强，以适用于妇科癌症患者群体。在这一人群中利用生活质量数据建立效用估计算法的性能，将增强研究人员进行妇科癌症治疗策略比较有效性研究的能力。

DESCRIPTION (provided by applicant): This research project is designed to determine if algorithms that use quality of life (QOL) data to predict utilities, which are used in the calculaton of a quality-adjusted life year (QALY) in economic analyses, are comparable to traditional methods of utility assessment. Gynecologic cancers are underrepresented in the published cost-effectiveness literature in part due to the lack of appropriate prospective utilities data collection within clinical trials. However, prospective QOL data are frequently collected within clinical trials. The ability to accurately predict utility values from QOL surveys could open existing, large clinical trial databases for more accurate cost-effectiveness and comparative effectiveness research. This study will prospectively and longitudinally collect utility and qualit of life data from gynecologic cancer patients before, during and after treatment. The utility-prediction algorithms will be compared to utility instruments and will be enhanced to be applicable to the gynecologic cancer patient population. Establishing the performance of utility-estimating algorithms using QOL data in this population will enhance the ability of investigators to conduct comparative effectiveness research of gynecologic cancer treatment strategies.