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患者报告结局测量信息系统(PROMIS)偏好评分系统:基于偏好的总结评分估算。

Estimation of a Preference-Based Summary Score for the Patient-Reported Outcomes Measurement Information System: The PROMIS-Preference (PROPr) Scoring System.

机构信息

Carnegie Mellon University, Department of Engineering and Public Policy, Pittsburgh, PA, USA.

McMaster University Faculty of Social Sciences, Hamilton, ON, Canada.

出版信息

Med Decis Making. 2018 Aug;38(6):683-698. doi: 10.1177/0272989X18776637. Epub 2018 Jun 26.

Abstract

BACKGROUND

Health-related quality of life (HRQL) preference-based scores are used to assess the health of populations and patients and for cost-effectiveness analyses. The National Institutes of Health Patient-Reported Outcomes Measurement Information System (PROMIS) consists of patient-reported outcome measures developed using item response theory. PROMIS is in need of a direct preference-based scoring system for assigning values to health states.

OBJECTIVE

To produce societal preference-based scores for 7 PROMIS domains: Cognitive Function-Abilities, Depression, Fatigue, Pain Interference, Physical Function, Sleep Disturbance, and Ability to Participate in Social Roles and Activities.

SETTING

Online survey of a US nationally representative sample ( n = 983).

METHODS

Preferences for PROMIS health states were elicited with the standard gamble to obtain both single-attribute scoring functions for each of the 7 PROMIS domains and a multiplicative multiattribute utility (scoring) function.

RESULTS

The 7 single-attribute scoring functions were fit using isotonic regression with linear interpolation. The multiplicative multiattribute summary function estimates utilities for PROMIS multiattribute health states on a scale where 0 is the utility of being dead and 1 the utility of "full health." The lowest possible score is -0.022 (for a state viewed as worse than dead), and the highest possible score is 1.

LIMITATIONS

The online survey systematically excludes some subgroups, such as the visually impaired and illiterate.

CONCLUSIONS

A generic societal preference-based scoring system is now available for all studies using these 7 PROMIS health domains.

摘要

背景

健康相关生活质量(HRQL)偏好评分用于评估人群和患者的健康状况,并进行成本效益分析。美国国立卫生研究院患者报告结局测量信息系统(PROMIS)由使用项目反应理论开发的患者报告结局测量组成。PROMIS 需要一个直接的偏好评分系统,以便为健康状况赋值。

目的

为 7 个 PROMIS 领域(认知功能-能力、抑郁、疲劳、疼痛干扰、身体功能、睡眠障碍以及参与社会角色和活动的能力)生成基于社会的偏好评分。

设置

在美国全国代表性样本(n=983)的在线调查。

方法

使用标准博弈法得出 PROMIS 健康状态的偏好,以获得 7 个 PROMIS 领域中的每一个的单一属性评分函数和一个乘法多属性效用(评分)函数。

结果

使用具有线性插值的等渗回归拟合 7 个单一属性评分函数。乘法多属性综合函数估计 PROMIS 多属性健康状态的效用,其范围为 0 是死亡的效用,1 是“完全健康”的效用。可能的最低得分为-0.022(表示比死亡状态更差的状态),可能的最高得分为 1。

局限性

在线调查系统地排除了一些亚组,例如视力障碍者和文盲。

结论

现在,对于使用这 7 个 PROMIS 健康领域的所有研究,都有一个通用的基于社会的偏好评分系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67cb/6502464/5b57330da55f/nihms-962433-f0001.jpg

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