Abstract

BackgroundAlmost all traditional Chinese medicine (TCM) quality of life measures are non-preference-based measures (non-PBMs), which do not provide utilities for cost-utility analysis in pharmacoeconomic evaluation. Whereas the mapping has become a new instrument to obtain utilities, which builds a bridge between non-PBMs and PBMs.PurposeTo develop mapping algorithms from the health status scale of traditional Chinese medicine (TCM-HSS) onto the three-level EuroQol five-dimensional questionnaire (EQ-5D-3L).MethodsThe cross-sectional data were collected by questionnaire survey from a tertiary hospital visit population and community residents in China, and randomly divided into training and validation set by 2:1. Based on the training set, direct and indirect mapping methods (7 regression methods and 4 model specifications) were conducted to establish alternative models, which were comprehensively evaluated based on the validation set by mean absolute error, root mean square error, and Spearman correlation coefficient between predicted and observed values. Based on the whole sample, the preferred mapping algorithm was developed.ResultsA total of 639 samples were included, with an average age of 45.24 years and 61.66% of respondents were female. The mean EQ-5D-3L index was 0.9225 [SD = 0.1458], and the mean TCM-HSS index was 3.4144 [SD = 3.1154]. The final mapping algorithm was a two-part regression model including the TCM-HSS subscales, interaction terms, and demographic covariates (age and gender). The prediction performance was good. The mean error was 0.0003, the mean absolute error was 0.0566, the root mean square error was 0.1039, and 83.10% of the prediction errors were within 0.1; the Spearman correlation coefficient between predicted and observed EQ-5D-3L values was 0.6479.ConclusionIt is the first study to develop a mapping algorithm between the TCM-HSS and EQ-5D-3L, which demonstrates excellent prediction accuracy and estimates utility value for economic evaluation from TCM quality of life measures.

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