scholarly journals Hedyotis diffusaCombined withScutellaria barbataAre the Core Treatment of Chinese Herbal Medicine Used for Breast Cancer Patients: A Population-Based Study

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Yuan-Chieh Yeh ◽  
Hsing-Yu Chen ◽  
Sien-Hung Yang ◽  
Yi-Hsien Lin ◽  
Jen-Hwey Chiu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Herbal Medicine ◽  
Association Rule ◽  
Association Rule Mining ◽  
Breast Cancer Patients ◽  
Rule Mining ◽  
The Core ◽  
Chinese Herbal ◽  
Hedyotis Diffusa ◽  
Treat Breast Cancer

Traditional Chinese medicine (TCM), which is the most common type of complementary and alternative medicine (CAM) used in Taiwan, is increasingly used to treat patients with breast cancer. However, large-scale studies on the patterns of TCM prescriptions for breast cancer are still lacking. The aim of this study was to determine the core treatment of TCM prescriptions used for breast cancer recorded in the Taiwan National Health Insurance Research Database. TCM visits made for breast cancer in 2008 were identified using ICD-9 codes. The prescriptions obtained at these TCM visits were evaluated using association rule mining to evaluate the combinations of Chinese herbal medicine (CHM) used to treat breast cancer patients. A total of 37,176 prescriptions were made for 4,436 outpatients with breast cancer. Association rule mining and network analysis identifiedHedyotis diffusaplusScutellaria barbataas the most common duplex medicinal (10.9%) used for the core treatment of breast cancer.Jia-Wei-Xiao-Yao-San(19.6%) andHedyotis diffusa(41.9%) were the most commonly prescribed herbal formula (HF) and single herb (SH), respectively. Only 35% of the commonly used CHM had been studied for efficacy. More clinical trials are needed to evaluate the efficacy and safety of these CHM used to treat breast cancer.

scholarly journals Chinese Herbal Medicine for Reducing Chemotherapy-Associated Side-Effects in Breast Cancer Patients: A Systematic Review and Meta-Analysis

2020 ◽  
Vol 10 ◽  
Author(s):  
Sha Li ◽  
Tsz-him So ◽  
Guoyi Tang ◽  
Hor-Yue Tan ◽  
Ning Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Systematic Review ◽  
Side Effects ◽  
Herbal Medicine ◽  
Cancer Patients ◽  
Chinese Herbal Medicine ◽  
Meta Analysis ◽  
Chemotherapeutic Agents ◽  
Breast Cancer Patients ◽  
Chinese Herbal

BackgroundChemotherapy usually induces a variety of side-effects in cancer treatment as it cannot tell normal cells apart from cancer cells and kills both. Chinese herbal medicine (CHM) has been regarded as a potential effective intervention for relieving the side-effects of chemotherapy in breast cancer patients.ObjectiveThis study aims to conduct a comprehensive systematic review and meta-analysis to evaluate the efficacy of CHM as adjuvant therapy for reducing the chemotherapy-induced side-effects in the treatment of breast cancer.MethodsMain electronic databases were searched up to May 2020 for Randomized Controlled Trials (RCTs) evaluating the effect of CHM on breast cancer patients with chemotherapy. The PRISMA statement was adopted in this study and meta-analyses were performed.ResultsThe included studies showed unsatisfied quality. Results based on available literature indicated that the adjunctive use of CHM with chemotherapy may reduce the chemotherapeutic agents-associated adverse events, including nausea and vomiting, diarrhea, alopecia, myelosuppression, and impaired immune function.ConclusionA confident conclusion could not be have due to the lack of large scale and high quality trials.

scholarly journals Identifying Core Herbal Treatments for Children with Asthma: Implication from a Chinese Herbal Medicine Database in Taiwan

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Hsing-Yu Chen ◽  
Yi-Hsuan Lin ◽  
Peck-Foong Thien ◽  
Shih-Chieh Chang ◽  
Yu-Chun Chen ◽  
...  
Keyword(s):  
Herbal Medicine ◽  
Chinese Herbal Medicine ◽  
Association Rule ◽  
Research Database ◽  
Clinical Database ◽  
Rule Mining ◽  
Asthmatic Children ◽  
Chinese Herbal ◽  
Children With Asthma ◽  
Great Burden

Asthma is one of the most common allergic respiratory diseases around the world and places great burden on medical payment. Chinese herbal medicine (CHM) is commonly used for Taiwanese children to control diseases. The aim of this study is to analyze the CHM prescriptions for asthmatic children by using a nationwide clinical database. The National Health Insurance Research Database (NHIRD) was used to perform this study. Medical records from 1997 to 2009 with diagnosis with asthma made for children aged 6 to 18 were included into the analysis. Association rule mining and social network analysis were used to analyze the prevalence of single CHM and its combinations. Ma-Xing-Gan-Shi-Tang (MXGST) was the most commonly used herbal formula (HF) (20.2% of all prescriptions), followed by Xiao-Qing-Long-Tang (13.1%) and Xing-Su-San (12.8%). Zhe Bei Mu is the most frequently used single herb (SH) (14.6%), followed by Xing Ren (10.7%). MXGST was commonly used with Zhe Bei Mu (3.5%) and other single herbs capable of dispelling phlegm. Besides, MXGST was the core formula to relieve asthma. Further studies about efficacy and drug safety are needed for the CHM commonly used for asthma based on the result of this study.

scholarly journals An Interval Type-2 Fuzzy Association Rule Mining Approach to Pattern Discovery in Breast Cancer Dataset

2021 ◽  
Vol 17 (3) ◽  
pp. 330-348
Author(s):  
Olufunke Oladipupo ◽  
Oluwole Olajide ◽  
Stephen Adubi ◽  
Jelili Oyelade ◽  
Zacchaeus Omogbadegun
Keyword(s):  
Breast Cancer ◽  
Association Rule ◽  
Association Rule Mining ◽  
Breast Cancer Dataset ◽  
Rule Mining ◽  
Cancer Dataset ◽  
Fuzzy Association Rule ◽  
Interval Type ◽  
Fuzzy Association Rule Mining

scholarly journals Efficacy and Safety of Chinese Herbal Medicine on Treatment of Breast Cancer: A Meta-analysis of Randomized Controlled Trials

2021 ◽  
pp. 1-19
Author(s):  
Venice Wing-Tung Ho ◽  
Hor-Yue Tan ◽  
Wei Guo ◽  
Sha Li ◽  
Ning Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Herbal Medicine ◽  
Cancer Patients ◽  
Chinese Herbal Medicine ◽  
Tumor Response ◽  
Controlled Trials ◽  
Breast Cancer Patients ◽  
Who Criteria ◽  
Randomized Controlled ◽  
Chinese Herbal

Breast cancer is currently the most common cancer in women, and it accounts for 11.6% of all cancer diagnoses in 2018. Breast cancer patients frequently resort to alternative medicine in addition to conventional Western therapy. This study is to evaluate clinical effectiveness of Chinese herbal medicine (CHM) on breast cancer by conducting meta-analyses on 81 randomized controlled trials (RCTs) with a total of 7215 subjects from eight databases. All RCTs compared patients using Western therapy alone and those using additional CHM therapy to evaluate the difference of primary (tumor response, mean time to progression (mTTP), overall survival (OS) and progression free survival (PFS)) and secondary outcome measures (tumor markers). Results showed that under the RECIST1.1 criteria, 52% patients with additional CHM therapy (67%, under WHO criteria) achieved either a complete response (CR) or a partial response (PR), compared to 38% patients with Western therapy alone (53%, under the WHO criteria). The risk ratio was 1.31 ([Formula: see text]¡ 0.00001, 95% CI = 1.15–1.50) for patients with CHM plus Western therapy and 1.25 ([Formula: see text]¡ 0.00001, 95% CI = 1.18–1.98) for those with Western therapy. Moreover, patients with complementary CHM therapy were associated with an mTTP of 2.79 months longer ([Formula: see text]¡ 0.00001) and an OS of 1.90 months longer ([Formula: see text] ¡ 0.00001); they also had an increase in 3-year PFS ([Formula: see text]= 0.002), 2- ([Formula: see text]= 0.0002) and 5-year ([Formula: see text]= 0.006) OS rates. Therefore, complementary CHM therapy might demonstrate clinical benefits for breast cancer patients in terms of tumor response and survival. Clinical studies with further stratification of tumor stages and intervention types are highly warranted.

scholarly journals An approach to improve the efficiency of apriori algorithm

2015 ◽  
Author(s):  
Sakshi Aggarwal ◽  
Ritu Sindhu
Keyword(s):  
Data Mining ◽  
Association Rule ◽  
Association Rule Mining ◽  
Apriori Algorithm ◽  
Core Concept ◽  
Rule Mining ◽  
Algorithm Efficiency ◽  
The Core ◽  
Database Size

Association rule mining has a great importance in data mining. Apriori is the key algorithm in association rule mining. Many approaches are proposed in past to improve Apriori but the core concept of the algorithm is same i.e. support and confidence of item sets and previous studies finds that classical Apriori is inefficient due to many scans on database. In this paper, we are proposing a method to improve Apriori algorithm efficiency by reducing the database size as well as reducing the time wasted on scanning the transactions.

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