Chinese Herbal Medicine Improved Survival in Stage IV Breast Cancer Patients: Data Mining of the Incorporated Taiwan Cancer Registry Database and Hospital Database.

BACKGROUND: According to recent research, breast cancer has become the most commonly diagnosed non-skin cancer type among the entire population. Meanwhile, Chinese herbal medicine (CHM) has become an important therapy to improve the survival rate and quality of life in metastatic cancer patients, as part of a wider trend toward more personalized medicine. However, there is a lack of research in terms of the association between stage IV breast cancer and CHM. Therefore, this study aimed to investigate the association between CHM and the survival rate in breast cancer patients at different cancer stages, with a particular focus on patients diagnosed with stage IV. METHODS: Patients with an initial diagnosis of breast cancer identified from the Taiwan Cancer Registry Database (TCRD) and China Medical University Hospital (CMUH) database were included in this study. Demographic characteristics including gender, age, and comorbidities were evaluated. Between-group differences for continuous and categorical variables were evaluated by the Student's t-test and Chi-square test, respectively. Patients diagnosed with breast cancer were recruited and divided into cohorts of CHM users and non-users with a 1:1 propensity score matching. The survival of breast cancer patients was assessed by the Cox proportional hazard model. The cumulative incidence of survival was assessed by Kaplan-Meier analysis. RESULTS: The adjuvant CHM treatment was associated with a higher survival rate in stage IV breast cancer patients (HR: 0.45, 95% CI: 0.2853-0.7044]. Additionally, the use of CHM had a positive impact on survival in stage IV breast cancer patients who had received surgery (P: .0273, HR: 0.3406, 95% CI: 0.1309-0.8865), chemotherapy (P: .0004, HR: 0.3893, 95% CI: 0.231-0.656), and hormone therapy (P: .0013, HR: 0.3491, 95% CI: 0.1836-0.6636). In terms of the specific CHM associated with survival, Zhi-Gan-Cao-Tang (ZGCT), Phellodendron chinense Schneid. (huang-bai), and Paeonia lactiflora Pall. (chi-shao) were the 3 most commonly prescribed herbal medicines correlated with a higher survival rate among stage IV breast cancer patients. CONCLUSIONS: CHM associated with conventional management achieved significant survival benefits in patients with stage IV breast cancer. Additional randomized controlled trials for prospective study are recommended for further validation.

Prescription system to calculate precise doses of Chinese herbal medicine to avoid toxic effects.

Background and objectives: Traditional Chinese Medicine (TCM) is a therapeutic system which has been practiced for thousands of years. Although for much of its history the decoction of medicinal herbs was the most common method of consuming the herbal treatments, TCM prescriptions are now primarily prepared using concentrated Chinese herbal extracts (CCHE) in powder or granular form. However, determining the precise dose of each single Chinese herbal constituent within a prescription creates a challenge in clinical practice due to the potential risk of toxicity. To alleviate this, we invented the Chinese Intelligence Prescription System (CIPS) to calculate the exact dose of each single herb within an individual prescription. Methods: In this study, we applied CIPS in a real-world setting to analyze clinical prescriptions collected and prepared at the TCM Pharmacy of China Medical University Hospital (CMUH). Results: Our investigation revealed that 3% of all prescriptions filled in a 1-month period contained inexact dosages, suggesting that more than 170,000 prescriptions filled in Taiwan in a given month may contain potentially toxic components. We further analyzed the data to determine the excess dosages and outline the possible associated side effects. Conclusions: In conclusion, CIPS offers TCM practitioners the ability to prepare exact Chinese herbal medicine (CHM) prescriptions in order to avoid toxic effects, thereby ensuring patient safety.

Chinese Intelligence Prescription System improves prescription accuracy while decreasing labor and drug costs.

BACKGROUND AND AIM: The traditional method of taking Chinese Medicine involves creating a decoction by cooking medicinal Chinese herbs. However, this method has become less popular, being replaced by the more convenient method of consuming concentrated Chinese herbal extracts, which creates challenges related to the complexity of stacking multiple formulas. METHODS: We developed the Chinese Intelligence Prescription System (CIPS) to simplify the prescription process. In this study, we used data from our institutions pharmacy to calculate the number of reductions, average dispensing time, and resulting cost savings. RESULTS: The mean number of prescriptions was reduced from 8.19 ± 3.65 to 7.37 ± 3.34 ([Formula: see text]). The reduction in the number of prescriptions directly resulted in decreased dispensing time, reducing it from 1.79 ± 0.25 to 1.63 ± 0.66 min ([Formula: see text]). The reduced dispensing time totaled 3.75 h per month per pharmacist, equivalent to an annual labor cost savings of $15,488 NTD per pharmacist. In addition, drug loss was reduced during the prescription process, with a mean savings of $4,517 NTD per year. The combined savings adds up to a not insignificant $20,005 NTD per year per pharmacist. When taking all TCM clinics/hospitals in Taiwan into account, the total annual savings would be $77 million NTD. CONCLUSION: CIPS assists clinicians and pharmacists to formulate precise prescriptions in a clinical setting to simplify the dispensing process while reducing medical resource waste and labor costs.

Evaluation of the efficacy of traditional Chinese medicine for the reproductive and pregnancy outcomes in women with endometriosis: A nationwide population-based study.

OBJECTIVE: Patients with endometriosis may seek traditional Chinese medicine (TCM) to help them conceive. The present study aims to evaluate the effects of TCM on reproductive and pregnancy outcomes in patients with endometriosis. MATERIALS AND METHODS: The patients with endometriosis taken from the National Health Insurance (NHI) research database between 2000 and 2012 were divided into two cohorts based on the use of TCM treatment. The two cohorts were matched by age and comorbidities and followed up until a new diagnosis of infertility, ectopic pregnancy, or miscarriage. Multivariable Cox proportional hazards models were used to evaluate the hazard ratio (HR) of reproductive and pregnancy outcomes. RESULTS: A total of 5244 patients with endometriosis were analyzed, including 1748 TCM users and 3496 matched control subjects. The proportion of infertility was higher in TCM users than in non-TCM users (adjusted hazard ratio [HR]: 1.34, 95% confidence interval [CI]: 1.13-1.60). However, there was no significant difference in the proportion of ectopic pregnancies between TCM users and non-TCM users (adjusted HR: 0.82, 95% CI: 0.60-1.13). There was no significant difference in the proportion of miscarriages between TCM users and non-TCM users (adjusted HR: 1.23, 95% CI: 0.95-1.61). CONCLUSION: TCM treatment showed insignificant efficacy in decreasing the risk of ectopic pregnancy and miscarriage in patients with endometriosis.

Principles and treatment strategies for the use of Chinese herbal medicine in patients at different stages of coronavirus infection.

Coronavirus disease 2019 (COVID-19) is a novel, human-infecting ß-coronavirus enveloped, positive-sense single-stranded RNA viruses, similar to the severe acute respiratory syndrome (SARS) infection that emerged in November 2002. In traditional Chinese medicine (TCM), the epidemic disease concepts of "febrile epidemics" (wenyi) or "warm diseases" (wenbing) are based on geographic and cultural aspects, and Chinese herbal medicine (CHM) played an important role in the treatment of epidemic diseases. CHM was widely used to treat patients suffered with SARS almost two decades ago during outbreak of SARS, with proven safety and potential benefits. TCM has also been widely used to treat cancer patients for a long history and much of them associate with immunomodulatory activity and are used to treat coronavirus-related diseases. We propose the use of CHM treatment principles for clinical practice, based on four main stages of COVID-19 infection: early, intermediate, severe, and convalescence. We suggest corresponding decoctions that exhibit antiviral activity and anti-inflammatory effects in the early stage of infection; preventing the disease from progressing from an intermediate to severe stage of infection; restoring normal lung function and improving consciousness in the severe stage; and ameliorating pulmonary and vascular injury in the convalescent stage. We summarize the pharmaceutical mechanisms of CHM for treating coronavirus via antiviral, anti-inflammatory and immunomodulatory effects.

Evaluation of the efficacy of Chinese herbal medicine and acupuncture for the prevention of mental disorders in interstitial cystitis patients: A nationwide population-based study.

Traditional Chinese medicine (TCM) is commonly used for urinary symptoms in Eastern countries. Since there are few effective treatments available for patients with interstitial cystitis/bladder pain syndrome (IC/BPS), the psychological burden leads to increased healthcare-seeking behavior. Some patients may therefore seek TCM treatment for related urinary symptoms. Due to limited clinical research evaluating the effects of TCM on IC/BPS, we conducted a nationwide population-based cohort study to investigate the relationship between TCM and mental disorders among these patients. The IC/BPS cohort and its matched non-IC/BPS comparison cohort were recruited from the National Health Insurance (NHI) Research Database between 2000 and 2011. Patients with the use of Chinese herbal medicine (CHM) granules or acupuncture over 90 days per year were enrolled as the TCM users. Multivariable Cox proportional hazards models were used to evaluate the hazard ratio (HR) of mental disorders related to interstitial cystitis. The incidence of mental disorders in the 2 cohorts was assessed with Kaplan-Meier curves. A total of 1123 patients with IC/BPS and 4492 matched non-IC/BPS subjects were included in this study. The IC/BPS cohort demonstrated higher incidence rate of mental disorders than the cohort without IC/BPS (adjusted HR: 2.21, 95% confidence interval [CI]: 1.73-2.81). There was no statistically significant difference in the risk of mental disorders between IC/BPS patients with and without CHM granules or acupuncture treatment (adjusted HR: 0.99, 95% CI: 0.58-1.68). Our results indicated that CHM and acupuncture showed insignificant efficacy in the prevention of mental disorders in IC/BPS patients.

Application of Neural Network and Cluster Analyses to Differentiate TCM Patterns in Patients With Breast Cancer.

BACKGROUND AND PURPOSE: Pattern differentiation is a critical element of the prescription process for Traditional Chinese Medicine (TCM) practitioners. Application of advanced machine learning techniques will enhance the effectiveness of TCM in clinical practice. The aim of this study is to explore the relationships between clinical features and TCM patterns in breast cancer patients. METHODS: The dataset of breast cancer patients receiving TCM treatment was recruited from a single medical center. We utilized a neural network model to standardize terminologies and address TCM pattern differentiation in breast cancer cases. Cluster analysis was applied to classify the clinical features in the breast cancer patient dataset. To evaluate the performance of the proposed method, we further compared the TCM patterns to therapeutic principles of Chinese herbal medication in Taiwan. RESULTS: A total of 2,738 breast cancer cases were recruited and standardized. They were divided into 5 groups according to clinical features via cluster analysis. The pattern differentiation model revealed that liver-gallbladder dampness-heat was the primary TCM pattern identified in patients. The main therapeutic goals of the top 10 Chinese herbal medicines prescribed for breast cancer patients were to clear heat, drain dampness, and detoxify. These results demonstrated that the neural network successfully identified patterns from a dataset similar to the prescriptions of TCM clinical practitioners. CONCLUSION: This is the first study using machine-learning methodology to standardize and analyze TCM electronic medical records. The patterns revealed by the analyses were highly correlated with the therapeutic principles of TCM practitioners. Machine learning technology could assist TCM practitioners to comprehensively differentiate patterns and identify effective Chinese herbal medicine treatments in clinical practice.

Neural network analysis of Chinese herbal medicine prescriptions for patients with colorectal cancer.

Traditional Chinese Medicine (TCM) is an experiential form of medicine with a history dating back thousands of years. The present study aimed to utilize neural network analysis to examine specific prescriptions for colorectal cancer (CRC) in clinical practice to arrive at the most effective prescription strategy. The study analyzed the data of 261 CRC cases recruited from a total of 141,962 cases of renowned veteran TCM doctors collected from datasets of both the DeepMedic software and TCM cancer treatment books. The DeepMedic software was applied to normalize the symptoms/signs and Chinese herbal medicine (CHM) prescriptions using standardized terminologies. Over 20 percent of CRC patients demonstrated symptoms of poor appetite, fatigue, loose stool, and abdominal pain. By analyzing the prescription patterns of CHM, we found that Atractylodes macrocephala (Bai-zhu) and Poria (Fu-ling) were the most commonly prescribed single herbs identified through analysis of medical records, and supported by the neural network analysis; although there was a slight difference in the sequential order. The study revealed an 81.9% degree of similarity of CHM prescriptions between the medical records and the neural network suggestions. The patterns of nourishing Qi and eliminating dampness were the most common goals of clinical prescriptions, which corresponds with treatments of CRC patients in clinical practice. This is the first study to employ machine learning, specifically neural network analytics to support TCM clinical diagnoses and prescriptions. The DeepMedic software may be used to deliver accurate TCM diagnoses and suggest prescriptions to treat CRC.