Health State Preference Weights for the Glasgow Outcome Scale Following Traumatic Brain Injury: A Systematic Review and Mapping Study.
Health State Preference Weights for the Glasgow Outcome Scale Following Traumatic Brain Injury: A Systematic Review and Mapping Study.
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DOI：
10.1016/j.jval.2016.09.2398
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发表时间：
2017-01
期刊：
影响因子：
--
通讯作者：
Gabbe B
中科院分区：
文献类型：
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作者：
Ward Fuller G;Hernandez M;Pallot D;Lecky F;Stevenson M;Gabbe B
格拉斯哥结果量表 (GOS) 类别的健康状态偏好权重 (HSPW) 的有效且相关的估计是评估创伤性脑损伤 (TBI) 治疗的经济模型的关键输入。描述现有 HSPW 估计的特征，并对 GOS 的 EuroQol 五维问卷 (EQ-5D) 进行建模，为未来经济模型的参数化提供信息。使用 1975 年至 2016 年间在广泛信息源中实施的高度敏感搜索策略，对 TBI 后 GOS 类别的 HSPW 进行了系统回顾。还对来自维多利亚州创伤登记处的严重 TBI（头部区域简写损伤量表评分≥3）的患者进行了 GOS 健康状况与三级 EQ-5D 英国关税指数值的横断面映射研究。使用有限因变量混合模型来估计作为 GOS 类别、年龄和其他解释变量的函数的 12 个月 EQ-5D UK 值集。从五项符合条件的研究中确定了六种独特的 HSPW。所有研究均存在较高的偏倚风险，且适用性有限。研究之间 HSPW 的程度存在显着差异。三类混合模型与观察到的维多利亚州创伤登记数据表现出极好的拟合度。 GOS 类别、受伤年龄、性别、合并症和严重颅外损伤均对平均 EQ-5D 效用值具有显着的独立影响。少数可用的 GOS 类别 HSPW 面临着潜在偏差和通用性有限的挑战。混合模型旨在为 GOS 类别提供与国家健康与护理卓越研究所参考案例一致的 HSPW。
Valid and relevant estimates of health state preference weights (HSPWs) for Glasgow Outcome Scale (GOS) categories are a key input of economic models evaluating treatments for traumatic brain injury (TBI). To characterize existing HSPW estimates, and model the EuroQol five-dimensional questionnaire (EQ-5D) from the GOS, to inform parameterization of future economic models. A systematic review of HSPWs for GOS categories following TBI was conducted using a highly sensitive search strategy implemented in an extensive range of information sources between 1975 and 2016. A cross-sectional mapping study of GOS health states onto the three-level EQ-5D UK tariff index values was also performed in patients with significant TBI (head region Abbreviated Injury Scale score ≥3) from the Victoria State Trauma Registry. A limited dependent variable mixture model was used to estimate the 12-month EQ-5D UK value set as a function of GOS category, age, and other explanatory variables. Six unique HSPWs from five eligible studies were identified. All studies were at high risk of bias with limited applicability. The magnitude of HSPWs differed significantly between studies. Three class mixture models demonstrated excellent goodness of fit to the observed Victoria State Trauma Registry data. GOS category, age at injury, sex, comorbidity, and major extracranial injury all had significant independent effects on mean EQ-5D utility values. The few available HSPWs for GOS categories are challenged by potential biases and restricted generalizability. Mixture models are presented to provide HSPWs for GOS categories consistent with the National Institute for Health and Care Excellence reference case.