Mapping the Constitution in Chinese Medicine Questionnaire to SF-6Dv1 / 中医杂志
Journal of Traditional Chinese Medicine
; (12): 1866-1871, 2023.
Article
de Zh
| WPRIM
| ID: wpr-987271
Bibliothèque responsable:
WPRO
ABSTRACT
ObjectiveTo construct and evaluate the transformation model of the Constitution in Chinese Medicine Questionnaire (CCMQ) to SF-6Dv1 health utility and broaden the applications of CCMQ. MethodsThe data of CCMQ and SF-6Dv1 were collected from 595 participants at baseline, 3 months and 6 months after the comprehensive intervention suitable for the corresponding traditional Chinese medicine (TCM) constitution. The estimation and validation datasets were constructed, and four statistical algorithms including the ordinary least squares (OLS), MM robust regression (MM), censored least absolute deviations (CLAD) and the Tobit model were used to create alternative models. The mean absolute error (MAE), root mean square error (RMSE) and intraclass correlation coefficient (ICC) were used to evaluate the prediction performance of the model. ResultsThe constitution scores of all TCM constitutions by CCMQ was significantly correlated with the SF-6Dv1 health utility value measured at three timepoints; the health utility value of the SF-6Dv1 was positively correlated with gentleness type (r=0.596, r=0.578, r=0.606, all P<0.05) and negatively correlated with eight unbalanced constitutions (r=-0.586~-0.301, all P<0.05). The MM established based on the subscale scores of CCMQ was the optimal mapping model, and the MAE, RMSE, and ICC values were 0.0741, 0.0930 and 0.766, respectively. Gentleness type, qi-deficiency type, phlegm-wetness type, qi-constraint type, and age were the primary factors included in the model. The measured and predicted value of SF-6Dv1 had a moderate positive correlation (r=0.673, r=0.617, P<0.05) and a good consistency as shown by the Bland-Altman plot. ConclusionBy using MM, the CCMQ can be transformed into SF-6Dv1 health utility value for health economics analysis.
Texte intégral:
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Indice:
WPRIM
langue:
Zh
Texte intégral:
Journal of Traditional Chinese Medicine
Année:
2023
Type:
Article