Please wait a minute...
Traditional Medicine Research  2017, Vol. 2 Issue (2): 88-93    DOI: 10.12032/TMR201706042
The applications of Bayesian models in real-world studies of traditional Chinese medicine: a primer
Zhai Jing-Bo1, Li Jiang2, Chen Jing3,*()
1Institute of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 312 Anshanxi Road, Nankai District, Tianjin 300193, China. 2Program office for Cancer Screening in Urban China, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China. 3Baokang hospital, Tianjin university of traditional Chinese medicine, Tianjin, 300193, China.
Download: HTML     PDF(244KB)
Export: BibTeX | EndNote (RIS)      


Real-world study is valuable for traditional Chinese medicine. However, there are no gold standards of statistical approaches for analyzing data from real-world study of traditional Chinese medicine. In the present study, we discussed why and when to use Bayesian analysis and the challenge in the real-world study of traditional Chinese medicine.


Real-world study is valuable for traditional Chinese medicine. However, there are no gold standards of statistical approaches for analyzing data from real-world study of traditional Chinese medicine. With the development of computer technology, researchers have increasingly paid attention to Bayesian statistics in the biomedical field. In present study, real-world study and Bayesian statistics were introduced. It was discussed that why and when to use Bayesian analysis and the challenge in the real-world study of traditional Chinese medicine.

Key wordsTraditional Chinese medicine      Real-world study      Bayesian models     
Published: 05 April 2017
Corresponding Authors: Chen Jing     E-mail:
About author: Executive Editor: Cui-Hong Zhu English Editor: Lin Li, Li-Yun-Cui, Ya-Song Wang, Xiao-Hua Zhang, Xiao-Dong Wang, Hong-Xu Zhu, Zhen-Yan Liu, Yi-Cheng Shi
Cite this article:

Zhai Jing-Bo, Li Jiang, Chen Jing. The applications of Bayesian models in real-world studies of traditional Chinese medicine: a primer. Traditional Medicine Research, 2017, 2(2): 88-93. doi: 10.12032/TMR201706042

URL:     OR

Figure 1 the flow chart of evidence updated by bayesian methods.
1.   Tian F, Xie YM.Real-world study: a potential new approach to effectiveness evaluation of traditional Chinese medicine interventions. J Chin Integr Med 2010, 8(4): 301-306.
doi: 10.3736/jcim20100401 pmid: 20388468
2.   Hung TC, Lee WY, Chen KB, et al.Investigation of Potent Lead for Acquired Immune deficiency Syndrome from Traditional Chinese Medicine. Biomed Res Int 2014, 2014: 205890.
doi: 10.1155/2014/205890
3.   Chen Z, Chen LY, Wang P, et al.Tumor Microenvironment Varies under Different TCM ZHENG Models and Correlates with Treatment Response to Herbal Medicine. Evid Based Complement Alternat Med 2012, 2012: 635702.
doi: 10.1155/2012/635702 pmid: 3368347
4.   Wang L, Zhang L, Feng X, et al.The Functional Difference of Dendritic Cells in HBeAg Negative Chronic Hepatitis B Patients with Three Different Spleen Deficiency Syndromes and the Therapeutic Evaluation of Chinese Medicine Intervention Based on Syndrome Differentiation. Evid Based Complement Alternat Med 2014, 2014: 802402.
5.   Altan A, Shiozawa A, Bancroft T, et al.A real-world study of switching from allopurinol to febuxostat in a health plan database. J Clin Rheumatol 2015, 21(8): 411-418.
doi: 10.1097/RHU.0000000000000322 pmid: 26580304
6.   Doyle A, Marsh P, Gill R, et al.Sorafenib in the treatment of hepatocellular carcinoma: a multi-centre real-world study. Scand J Gastroenterol 2016, 51(8): 979-985.
doi: 10.3109/00365521.2016.1166518 pmid: 27161568
7.   Fiorillo A, Del Vecchio V, Luciano M, et al.Efficacy of psycho educational family intervention for bipolar I disorder: A controlled, multicentric, real-worlds tudy. J Affect Disord 2015, 172: 291-299.
doi: 10.1016/j.jad.2014.10.021 pmid: 25451428
8.   Bhattacharya R, Zhou S, Wei W, et al.A real-world study of the effect of timing of insulin initiation on outcomes in older medicare beneficiaries with type 2 diabetes mellitus. J Am Geriatr Soc 2015, 63(5): 893-901.
doi: 10.1111/jgs.13388 pmid: 25955280
9.   Li J, Gao W, Punja S, et al.Reporting quality of N-of-1 trials published between 1985 and 2013: a systematic review. J Clin Epidemiol 2016, 76: 57-64.
doi: 10.1016/j.jclinepi.2015.11.016 pmid: 26769257
10.   Zhai JB, Cao HB, Ren M, et al.Reporting of core items in hierarchical Bayesian analysis for aggregating N-of-1 trials to estimate population treatment effects is suboptimal. J Clin Epidemiol 2016, 76: 99-107.
11.   Duan N, Kravitz RL, Schmid CH.Single-patient (n-of-1) trials: a pragmatic clinical decision methodology for patient-centered comparative effectiveness research. J Clin Epidemiol 2013, 66(8): S21-S28.
doi: 10.1016/j.jclinepi.2013.04.006 pmid: 3972259
12.   Zucker DR, Schmid CH, McIntosh MW, et al. Combining Single Patient (N-of-1) Trials to Estimate Population Treatment Effects to and to Evaluate Individual Patient Responses to Treatment. J Clin Epidemiol 1997, 50(4): 401-410.
13.   Schmid CH, Brown EN.Bayesian hierarchical models. Methods Enzymol 2000, 321: 305-330.
14.   Gabler NB, Duan N, Vohra S, et al.N-of-1 Trials in the Medical Literature: A Systematic Review. Med Care 2011, 49(8): 761-768.
doi: 10.1097/MLR.0b013e318215d90d pmid: 21478771
15.   Pennello G, Thompson L.Experience with Reviewing BayesianMedical Device Trials. J Biopharm Stat 2008, 18(1): 81-115.
doi: 10.1080/10543400701668274 pmid: 18161543
16.   Lunn DJ, Thomas A, Best N, et al.WinBUGS - A Bayesian modelling framework: Concepts, structure, and extensibility. Stat Comput 2000, 10(4): 325-337.
doi: 10.1023/A:1008929526011
17.   Lewis RJ.Bayesian modeling and real-world problems. Acad Emerg Med 2003, 10(7): 780-782.
doi: 10.1197/aemj.10.7.780 pmid: 12837653
18.   Young KD, Lewis RJ.What is confidence? Part 2: detailed definition and determination of confidence intervals. Ann Emerg Med 1997, 30(3): 311-318.
19.   Chen HJ, Chen R, Yang M, et al.Identification of Minimal Hepatic Encephalopathyin Patients with Cirrhosis Based on White Matter Imaging andBayesian Data Mining. Am J Neuroradiol 2015, 36(3): 481-487.
doi: 10.3174/ajnr.A4146 pmid: 25500314
20.   Chen R, Young K, Chao LL, et al.Prediction of Conversion from Mild CognitiveImpairment to Alzheimer DiseaseBased on Bayesian Data Miningwith Ensemble Learning. Neuroradiol J 2012, 25(1): 5-16.
doi: 10.1177/197140091202500101 pmid: 24028870
[1] Su-Tong Liu, Su-Fang Zhang, Kai-Qi Su, Ying-Bin Luo, Zhi-Hong Fang, Yuan Fang, Jing Xu, Jian-Chun Wu, Yan Li. The effect of long-term traditional Chinese medicine treatment on disease-free survival of postoperative stage I-III lung cancer patients: a retrospective cohort study[J]. Traditional Medicine Research, 2019, 4(2): 91-98.
[2] Wei-Jie Xie, Yu-Mei Wu, Shuai-Shuai Chen, Jian Xu, Fang-Fang Yang, Yong-Ping Zhang, Xiao-Bo Sun. In vitro evaluation of transdermal permeation effects of Fu’s cupping therapy via six diffusion kinetics models[J]. Traditional Medicine Research, 2019, 4(1): 42-53.
[3] Liang-Jun Yang, Dao-Rui Hou, Ya Li, Zhi-Peng Hu, Yong Zhang. A network pharmacology approach to investigate the mechanisms of Si-Jun-Zi decoction in the treatment of gastric precancerous lesions[J]. Traditional Medicine Research, 2018, 3(6): 273-285.
[4] Jian Hao, Shi-Jun Li. Recent advances in network pharmacology applications in Chinese herbal medicine[J]. Traditional Medicine Research, 2018, 3(6): 260-272.
[5] Yue Ji, Jun-Chen Li, Jing-Yan Meng, Xue-Rou Yan, Jian-ang Li, Qing-Yun Zhao, Kang Yang, Chun- Liu. Study of dual-directional regulatory effect of Banxia (Pinellia ternata) and Huanglian (Coptis chinensis) drug pair on gastrointestinal movement of mice[J]. Traditional Medicine Research, 2018, 3(3): 148-156.
[6] Wen-Qi Huang, Zhu Yang, Dong-Xin Tang, Feng-Xi Long, Li Luo, Bing Yang, Juan Li, Jie Chen. Pharmacological intervention of traditional Chinese medicine for the quality of life in patients with colorectal cancer: a systematic review and meta-analysis[J]. Traditional Medicine Research, 2018, 3(2): 95-105.
[7] Li-Lin Yang, Jie Gao, Hai-Wang Wu, Song-Ping Luo. History of recurrent miscarriage in traditional Chinese medicine literature[J]. Traditional Medicine Research, 2018, 3(2): 62-69.
[8] Tian Ran, Dai Liang, Shang Hong-Cai, Li You-Ping, Bian Zhao-Xiang. How to establish precise proprietary Chinese medicine in post-marketing reappraisal?[J]. Traditional Medicine Research, 2017, 2(4): 155-160.
[9] Yang Xue, Wu Xiong-Zhi. The combination of disease and Zheng (syndrome) on the basic of differentiation of six channels: a new pattern of disease diagnosis and treatment of traditional Chinese medicine[J]. Traditional Medicine Research, 2017, 2(2): 100-104.
[10] Xu Wei, Chai Ni, Cheng Yue-Lei, Yang Qiong, Zhu Hui-Rong. Analysis on the principles of differentiation and prescription of traditional Chinese medicine in the treatment of cancerous fever[J]. Traditional Medicine Research, 2017, 2(1): 41-50.
[11] Shang Hong-Cai, Wu Xiong-Zhi, Qiu Rui-Jin, Wang Ya-Han, Wang Yong-Yan. Traditional Chinese medicine should not be ignored during the development of precision medicine with Chinese characteristics[J]. Traditional Medicine Research, 2016, 1(3): 105-114.
[12] Liu Li-Juan, Zhou Chao, Song Fu-Cheng, Zhang Sen-Sen, Teng Wen-Jing, Zhuang Jing, Sun Chang-Gang, Si Hong-Zong. Molecular docking study on the molecular mechanism of rhaponticin for treatment of chronic myelocytic leukemia[J]. Traditional Medicine Research, 2016, 1(3): 122-127.
[13] Yang Dao-Zheng, Luan Xin-Yuan, Wang Shu-Bin. Epigenetic regulations of hematopoietic stem cells ageing and the regulation of traditional Chinese medicine[J]. Traditional Medicine Research, 2016, 1(2): 75-82.
[14] Cui-HongZhu, Hao Jian, Yang Xue, Wang Xiao-Dong, Xiong-ZhiWu. Complete response of hepatocellular carcinoma treated with traditional Chinese medicine treatment: A case report[J]. Traditional Medicine Research, 2016, 1(1): 52-57.