EQ-5D VAS映射模型比较
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摘要
目的比较EQ-5D-3L量表与EQ-5D VAS映射模型及值域表,提出不同人群EQ-5D VAS映射模型的选择策略。方法通过对某功能社区的现场调查,获取EQ-5D-3L量表和EQ-5D VAS的实测值,对比国内外12个映射模型和本研究建立的预测模型的相关性和绝对误差。所有模型均为一般线性模型,数据处理采用R语言。结果 (1)欧洲及英国、芬兰等7个国家及新西兰之间EQ-5D VAS映射模型的相关系数均大于0.9。以芬兰作为国外VAS映射模型的代表,芬兰模型与中国2次调查和本研究的相关系数分别为0.969、0.939和0.976;(2)本研究和芬兰模型的VAS预测值与实测值的拟合曲线相似,平均绝对误差分别为17.11和16.96;(3)VAS预测值比TTO预测值平均少20分,更接近实测值。结论 2008年和2013年在第四次和第五次国家卫生服务调查建立的EQ-5D VAS映射模型,对于相对健康人群,2008年建立的N3模型误差较小。国外模型中,芬兰模型误差较小。根据特定人群建立的映射模型不能外推到其他人群。
Objective This study was conducted in order to compare the EQ-5 D-3 L scale with mapping models and range tables of EQ visual analogue scale(VAS),and then propose a selection strategy for the EQ-5 D VAS mapping models.Methods The actual measurements of the EQ-5 D-3 L scale and EQ-5 D VAS were obtained through a field investigation conducted at a functional community.The correlation and absolute errors were then analyzed after comparing the 12 mapping models obtained at home and abroad with the prediction models established in this study.All models were generalized linear models.R language was used for the data processing.Results(1) The correlation coefficients of the EQ-5 D VAS mapping models pertaining to the seven countries in Europe(the United Kingdom,Finland,etc.) and New Zealand,were greater than 0.9.Taking Finland as the representative for the VAS mapping models obtained from the foreign countries,the correlation coefficients between the Finnish model and China's two surveys and our study were 0.969,0.939,and 0.976,respectively;(2) The fitted curve of the predicted and observed VAS values of this study was similar to those of the Finnish model.The average absolute errors were 17.11 and 16.96,respectively;(3) The VAS prediction was 20 points less than that in the time trade-off(TTO) prediction,which was closer to the observed values.Conclusion The N3 model established in 2008 China's surveys has smaller errors for relatively healthy generalpopulations,according to the EQ-5 D VAS mapping model established in the fourth and fifth National Health Service Survey in 2008 and 2013.The error in the Finnish model is also minor relative to the other models in the foreign country group.Mapping models established based on a specific population cannot be extrapolated to the data from other population.
Objective This study was conducted in order to compare the EQ-5 D-3 L scale with mapping models and range tables of EQ visual analogue scale(VAS),and then propose a selection strategy for the EQ-5 D VAS mapping models.Methods The actual measurements of the EQ-5 D-3 L scale and EQ-5 D VAS were obtained through a field investigation conducted at a functional community.The correlation and absolute errors were then analyzed after comparing the 12 mapping models obtained at home and abroad with the prediction models established in this study.All models were generalized linear models.R language was used for the data processing.Results(1) The correlation coefficients of the EQ-5 D VAS mapping models pertaining to the seven countries in Europe(the United Kingdom,Finland,etc.) and New Zealand,were greater than 0.9.Taking Finland as the representative for the VAS mapping models obtained from the foreign countries,the correlation coefficients between the Finnish model and China's two surveys and our study were 0.969,0.939,and 0.976,respectively;(2) The fitted curve of the predicted and observed VAS values of this study was similar to those of the Finnish model.The average absolute errors were 17.11 and 16.96,respectively;(3) The VAS prediction was 20 points less than that in the time trade-off(TTO) prediction,which was closer to the observed values.Conclusion The N3 model established in 2008 China's surveys has smaller errors for relatively healthy generalpopulations,according to the EQ-5 D VAS mapping model established in the fourth and fifth National Health Service Survey in 2008 and 2013.The error in the Finnish model is also minor relative to the other models in the foreign country group.Mapping models established based on a specific population cannot be extrapolated to the data from other population.
引文
[1] EuroQol.EQ-5D-5L User Guide:Basic information on how to use the EQ-5D-5L instrument.https://euroqol.org/wp-content/uploads/2016/09/EQ-5D-5L_UserGuide_2015.pdf.
[2] Tan Z,Liang Y,Liu S,et al.Health-Related Quality of Life as measured with EQ-5D among Populations with and without Specific Chronic Conditions:A Population-Based Survey in Shaanxi Province,China.PLoS ONE 2013;8(7):e65958.
[3] Sun S,Jiaying C,Magnus J,et al.Population health status in China:EQ-5D results,by age,sex and socio-economic status,from the National Health Services Survey 2008.Quality of Life Research.2011,20(3):309-320.
[4] 姚强,张耀光,徐玲.中国居民健康相关生命质量状况及影响因素研究-基于国家卫生服务调查实证分析.人口与发展.2018,24(3):85-95.
[5] 周挺,官海静,刘国恩,马爱霞.基于EQ-5D量表的中国疾病人群生命质量系统评价.中国循证医学杂志.2016,16(2):135-142.
[6] Szende A,Oppe M,Devlin N.EQ-5D Value Sets:Inventory.Comparative Review and User Guide,2009:1-12.
[7] FeenyD.A Utility Approach to the Assessment of Health-Related Quality of Life.MEDICAL CARE.2000,38( 9) Supplement II,I-151-II-154.
[8] Leidl R,Reitmeir P.An Experience-Based Value Set for the EQ-5D-5L in German.Value in Health2017,20(8):1150-1156.
[9] 伍红艳,刘国恩,官海静.EQ-5D健康量表效用积分体系的构建研究-基于我国西南地区的实证分析.药物经济学.2016,27(14):1877-1880.
[10] Liu GG,Wu H,Li M,et al.Chinese time trade-off values for EQ-5D health states.Value in Health.2014,17(5):597-604.
[11] Ludwig K,Graf von der Schulenburg JM,Greiner W.German Value Set for the EQ-5D-5L.Pharmacoeconomics 2018,36(6):663-674.
[12] XieF,PullenayegumE,GaebelK,et al.A Time Trade-off-derived Value Set of the EQ-5D-5L for Canada.Medical Care 2016,54(1):98-105.
[13] Luo N,Liu G,Li MH,et al.Estimating an EQ-5D-5L Value Set for China.Value in Health.2017,20(4):662-669.
[2] Tan Z,Liang Y,Liu S,et al.Health-Related Quality of Life as measured with EQ-5D among Populations with and without Specific Chronic Conditions:A Population-Based Survey in Shaanxi Province,China.PLoS ONE 2013;8(7):e65958.
[3] Sun S,Jiaying C,Magnus J,et al.Population health status in China:EQ-5D results,by age,sex and socio-economic status,from the National Health Services Survey 2008.Quality of Life Research.2011,20(3):309-320.
[4] 姚强,张耀光,徐玲.中国居民健康相关生命质量状况及影响因素研究-基于国家卫生服务调查实证分析.人口与发展.2018,24(3):85-95.
[5] 周挺,官海静,刘国恩,马爱霞.基于EQ-5D量表的中国疾病人群生命质量系统评价.中国循证医学杂志.2016,16(2):135-142.
[6] Szende A,Oppe M,Devlin N.EQ-5D Value Sets:Inventory.Comparative Review and User Guide,2009:1-12.
[7] FeenyD.A Utility Approach to the Assessment of Health-Related Quality of Life.MEDICAL CARE.2000,38( 9) Supplement II,I-151-II-154.
[8] Leidl R,Reitmeir P.An Experience-Based Value Set for the EQ-5D-5L in German.Value in Health2017,20(8):1150-1156.
[9] 伍红艳,刘国恩,官海静.EQ-5D健康量表效用积分体系的构建研究-基于我国西南地区的实证分析.药物经济学.2016,27(14):1877-1880.
[10] Liu GG,Wu H,Li M,et al.Chinese time trade-off values for EQ-5D health states.Value in Health.2014,17(5):597-604.
[11] Ludwig K,Graf von der Schulenburg JM,Greiner W.German Value Set for the EQ-5D-5L.Pharmacoeconomics 2018,36(6):663-674.
[12] XieF,PullenayegumE,GaebelK,et al.A Time Trade-off-derived Value Set of the EQ-5D-5L for Canada.Medical Care 2016,54(1):98-105.
[13] Luo N,Liu G,Li MH,et al.Estimating an EQ-5D-5L Value Set for China.Value in Health.2017,20(4):662-669.