In:
BMJ Open, BMJ, Vol. 8, No. 8 ( 2018-08), p. e020939-
Kurzfassung:
The transition from chronic non-atrophic gastritis (CNAG) to chronic atrophic gastritis (CAG) and gastric carcinoma (GC) is regarded as a representative disease model of gastric mucosa malignant transformation led by uncontrolled inflammation. Traditional Chinese medicine (TCM) syndrome-targeted therapies have been applied in treating chronic gastritis (CG) malignant transformation in China with satisfying efficacy. This study aims to validate TCM syndrome features in each stage of CG malignant transformation. The findings may shed light on the TCM hypothesis of CG malignant transformation, and thus optimise syndrome-targeted treatment strategies of CNAG, CAG and GC, respectively. Methods and analysis The present study is a cross-sectional study conducted in China. A total of 2000 eligible patients, including 500 CNAG cases, 1000 CAG cases and 500 GC cases, will be recruited from four TCM hospitals. Primary outcome measures include the prevalence of TCM syndrome patterns in varied stages of CG malignant transformation. Secondary outcome measures include prevalence and severity of all the presenting signs and symptoms collected by using TCM four diagnostic methods. Descriptive analysis, comparative analysis and correlation analysis of all the measurement data will be performed by biostatisticians. Unsupervised data mining analyses, including exploratory factor analysis, association rule analysis, hierarchical clustering analysis, complex system entropy clustering analysis, and so on, will also be performed by data scientists respectively for in-depth analyses of TCM syndrome-related indicators. Ethics and dissemination The protocol has been approved by the Ethical Review Board of Dongzhimen Hospital Affiliated to Beijing University of Chinese Medicine (No ECPJ-BDY-2014-02). All the study outcomes will be disseminated through national conference reports and in the meantime published on peer-reviewed journals. Trial registration number NCT03314038 ; Pre-results.
Materialart:
Online-Ressource
ISSN:
2044-6055
,
2044-6055
DOI:
10.1136/bmjopen-2017-020939
Sprache:
Englisch
Verlag:
BMJ
Publikationsdatum:
2018
ZDB Id:
2599832-8
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