Chinese Herbal Medicines (CHM) are the most common interventions of traditional Chinese medicine (TCM), typically administered as either single herbs or formulas. Systematic reviews (SRs) are essential references for evaluating the efficacy and safety of CHM treatments accurately and reliably. Unfortunately, the reporting quality of SRs with CHM is not optimal, especially the reporting of CHM interventions and the rationale of why these interventions were selected. To address this problem, a group of TCM clinical experts, methodologists, epidemiologists, and editors has developed a PRISMA extension for CHM interventions (PRISMA-CHM) through a comprehensive process, including registration, literature review, consensus meeting, three-round Delphi survey, and finalization. The PRISMA checklist was extended by introducing the concept of TCM Pattern and the characteristics of CHM interventions. A total of twenty-four items (including sub-items) are included in the checklist, relating to title (1), structured summary (2), rationale (3), objectives (4), eligibility criteria (6), data items (11), synthesis of results (14, 21), additional analyses (16, 23), study characteristics (18), summary of evidence (24), and conclusions (26). Illustrative examples and explanations are also provided. The group hopes that PRISMA-CHM 2020 will improve the reporting quality of SRs of CHM.

Ulcerative colitis (UC) is a chronic relapsing inflammatory bowel disease with an increasing incidence and prevalence worldwide. The diagnosis for UC mainly relies on clinical symptoms and laboratory examinations. As some previous studies have revealed that there is an association between gene expression signature and disease severity, we thereby aim to assess whether genes can help to diagnose UC and predict its correlation with immune regulation. A total of ten eligible microarrays (including 387 UC patients and 139 healthy subjects) were included in this study, specifically with six microarrays (GSE48634, GSE6731, GSE114527, GSE13367, GSE36807, and GSE3629) in the training group and four microarrays (GSE53306, GSE87473, GSE74265, and GSE96665) in the testing group. After the data processing, we found 87 differently expressed genes. Furthermore, a total of six machine learning methods, including support vector machine, least absolute shrinkage and selection operator, random forest, gradient boosting machine, principal component analysis, and neural network were adopted to identify potentially useful genes. The synthetic minority oversampling (SMOTE) was used to adjust the imbalanced sample size for two groups (if any). Consequently, six genes were selected for model establishment. According to the receiver operating characteristic, two genes of OLFM4 and C4BPB were finally identified. The average values of area under curve for these two genes are higher than 0.8, either in the original datasets or SMOTE-adjusted datasets. Besides, these two genes also significantly correlated to six immune cells, namely Macrophages M1, Macrophages M2, Mast cells activated, Mast cells resting, Monocytes, and NK cells activated (P  <  0.05). OLFM4 and C4BPB may be conducive to identifying patients with UC. Further verification studies could be conducted.

BackgroundChinese herbal medicines (CHMs) are the major interventions of traditional Chinese medicine (TCM), which are typically administered as either single herbs or formulas. The Cochrane systematic reviews (SRs) of CHMs are essential references for evaluating the efficacy and safety of CHMs interventions; they are expected to be accurate and reliable. This study aimed to assess the reporting quality of these SRs, particularly whether necessary information related to CHM was adequately reported.MethodsThe Cochrane Database was systematically searched for all SRs of CHM that were published up to 31 December 2017. The primary analysis was to assess their reporting quality based on 27-item of the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) and 9-item of CHM-related information designed according to TCM theory. Descriptive statistics were additionally used to analyze their baseline characteristics.ResultsA total of 109 Cochrane SRs of CHM were identified from 1999 to 2017. For 27-item of PRISMA, 26 had the reporting compliances higher than 50%, of which 11 were fully reporting (100%). However, for CHM-related information, 65 (59.6%) SRs did not report the specific name of the CHM in the title, 42 (38.5%) lacked TCM-related rationales in the introduction, 62 (56.9%) did not include CHM-related characteristics in the additional analyses, and 77 (70.6%) did not analyze CHM results in terms of TCM-related theories in the discussion. Of 97 SRs that included clinical trials, 38 (39.2%) did not provide the details of composition and dosage of CHMs, 85 (87.6%) did not report the CHM sources, 13 (13.4%) did not provide the dosage form, 95 (97.9%) lacked CHM quality control information, and 57 (58.8%) did not describe details of the controls. For 62 (72.9%) of 85 SRs that included meta-analysis, it was impossible to assess whether meta-analysis had been properly conducted due to inadequate reporting of CHM interventions.ConclusionAlthough the Cochrane SRs of CHM showed reporting compliance with PRISMA checklist, their reporting quality needs improvement, especially about full reporting of CHM interventions and of TCM-related rationales. Reporting guideline of “PRISMA extension for CHM interventions” should be developed thus to improve their quality.

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