Journal of ethnopharmacology · 2025
Revealing disease-specific medication patterns of Wuling Powder: A large-scale data mining analysis of randomized controlled trials.
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Lai Yu, Chen Guoren, Wu Qiuting, Chen Xuannan, Zhang Huize
Аннотация
ETHNOPHARMACOLOGICAL RELEVANCE: Wuling Powder (WLP) is a classical formula extensively employed in traditional Chinese medicine (TCM) clinical practice, frequently combined with other formulas or medications to tackle various disorders.
AIM OF THE STUDY: This research sought to systematically uncover disease-specific medication rules and prescription modification patterns of WLP utilizing multiple data mining methodologies.
METHODS: WLP-related studies from Chinese and English databases up to December 13, 2024, were screened for inclusion. Randomized controlled trials (RCTs) involving oral administration of original or modified WLP were included, and disease and prescription data were extracted to build a dedicated WLP database in Microsoft Office Excel 2019. For the descriptive analysis, Microsoft Office Excel 2019 was utilized. Association rule analysis was conducted with IBM SPSS Modeler 18.0. Origin 2021 was employed to carry out systematic cluster analysis. Lantern 5.0 software was utilized to perform latent structure analysis. Additionally, Origin 2021 was also employed for data visualization.
RESULTS: 855 WLP-related RCTs were incorporated into the final analysis. The disease-specific medication rules and prescription modification patterns of WLP were deciphered. Particularly, WLP is most frequently combined with blood-activating and stasis-resolving therapies, especially in the treatment of diseases of the digestive system, diseases of the genitourinary system, diseases of the circulatory system, diseases of the musculoskeletal system, diseases of the visual system, and heart failure, highlighting the significance of the TCM theory of homogeny of fluid and blood.
CONCLUSION: This research effectively constructed an evidence-driven decision support framework for the clinical use of WLP by conducting an in-depth data mining analysis of a vast collection of RCTs.
AIM OF THE STUDY: This research sought to systematically uncover disease-specific medication rules and prescription modification patterns of WLP utilizing multiple data mining methodologies.
METHODS: WLP-related studies from Chinese and English databases up to December 13, 2024, were screened for inclusion. Randomized controlled trials (RCTs) involving oral administration of original or modified WLP were included, and disease and prescription data were extracted to build a dedicated WLP database in Microsoft Office Excel 2019. For the descriptive analysis, Microsoft Office Excel 2019 was utilized. Association rule analysis was conducted with IBM SPSS Modeler 18.0. Origin 2021 was employed to carry out systematic cluster analysis. Lantern 5.0 software was utilized to perform latent structure analysis. Additionally, Origin 2021 was also employed for data visualization.
RESULTS: 855 WLP-related RCTs were incorporated into the final analysis. The disease-specific medication rules and prescription modification patterns of WLP were deciphered. Particularly, WLP is most frequently combined with blood-activating and stasis-resolving therapies, especially in the treatment of diseases of the digestive system, diseases of the genitourinary system, diseases of the circulatory system, diseases of the musculoskeletal system, diseases of the visual system, and heart failure, highlighting the significance of the TCM theory of homogeny of fluid and blood.
CONCLUSION: This research effectively constructed an evidence-driven decision support framework for the clinical use of WLP by conducting an in-depth data mining analysis of a vast collection of RCTs.