ABSTRACT
Objective: In this study, we analyzed the Japanese Adverse Drug Event Report (JADER) database in order detect unexpected adverse events using three polypharmacy machine learning models.Methods: The patient’s age, weight, height, gender, date and time of onset, subsequent appearance, and the taking medicines were preprocessed. They were applied for the prediction of adverse events using three machine learning procedures such as support vector machine (SVM), deep neural network (DNN) and random forest (RF).Results: Precision, matching, reproduction and F-values were almost same between the three techniques. Polypharmacy effects were predicted in approximately 80% of adverse events. Unexpected predictions were observed between DNN and RF, but different from SVM.Conclusion: Results suggest that the combination of DNN or RF and SVM can yield accurate predictions. We also suggest that RF is more useful because of its easy validation.
ABSTRACT
The creation of the National Health Insurance program has greatly contributed to giving Japan the world’s highest level of life expectancy. However, the cost of medical care in Japan has increased as a result of an aging society. In response to this reality, the Japanese government initiated a campaign to promote the use of generic drugs (GEs). In order to clarify some of the trends that contribute to different clinical medicine department usages of GEs, we carried out a survey of 400 pharmacies. The survey data was analyzed using linear regression analysis. Analysis of linear equations derived “utilization” that indicated ease of use of GEs, and a “saturation acceptable value (maximum allowed)” that indicated usage of GEs. The breakdown for different clinical medicine department usages of GEs was determined as the following: psychosomatic medicine or psychiatry was 11±0.13%, internal medicine was 29±0.18%, orthopedics was 18±0.14%, ophthalmology or otolaryngology was 15±0.14%, other departments was 17±0.15%. Furthermore, the highest utilization derived by linear regression analysis was orthopedics. The highest acceptable saturation value was for psychosomatic medicine or psychiatry, while the lowest acceptable saturation value was orthopedics. The results of the study confirm the importance of establishing evaluation methods for GE usage, and that linear regression analysis is a powerful tool for revealing trends in GE usage among different departments. Additionally, the study suggests that determining GE spread measures is valuable, since they can serve as an aid to future pharmaceutical administration consideration.
ABSTRACT
<b>Objective: </b>Oral mucositis is one of the serious and frequent acute side effects due to chemoradiotherapy (CRT) for head and neck cancer. In this study, we prepared an oral rinse as a hospital preparation for the treatment of oral mucositis, which was a suspension of polaprezinc (PZ), a zinc-containing therapeutic agent for gastric ulcer, in carboxyvinyl polymer (CP), a water-soluble large molecule.<br><b>Methods: </b>We carried out stability tests of the PZ-CP oral rinse, and investigated its effects on the radiation-induced oral mucositis in patients who received CRT for head and neck cancer.<br><b>Results: </b>In the stability test, the pH, viscosity, adhesion and PZ content in the preparations did not change throughout 28 days after preparation. In the clinical evaluation on the basis of the distribution of the Grade of oral mucositis, the Grade of oral mucositis in the PZ group was significantly lower than in the control group at 6 and 7 weeks (<i>p</i>=0.016, <i>p</i>=0.018). The incidence of severe oral mucositis of Grade 3 was 15.0% (3 cases) in the PZ group and 41.7% (10 cases) in the control group at 6 weeks, and was 15.0% (3 cases) in the PZ group and 33.3% (8 cases) in the control group at 7 weeks.<br><b>Conclusion: </b>These results suggest that PZ-CP oral rinse inhibits the aggravation of oral mucositis induced by CRT or promotes its healing.
ABSTRACT
<b>Objective: </b>Recently, the cost of medical care in Japan has increased as a result of an aging society. In response to this reality, the Japanese government initiated a campaign to promote the use of generic drugs. In spite of this campaign, Japanese consumers have doubts about the safety and reliability of generic drugs, resulting in lower usage of these drugs compared to usage in Europe and the US.<br><b>Methods: </b>In order to clarify some of the factors that contribute to low rates of generic drug use, we carried out a survey of 400 pharmacies. The survey data was analyzed using factor analysis and cluster analysis, which is a technique known as multivariate analysis.<br><b>Results: </b>The results from factor analysis derived four factors: 1) generic drug usage related to generic drug prescription class, 2) the amount of generic drug prescriptions related to patient preferences, 3) patient willingness to use generic drug prescriptions, and 4) pharmacy willingness. Cluster analysis was used to classify pharmacies participating in the survey. The results of cluster analysis revealed three main pharmacy groups: a) low usage of generic drugs, b) moderate usage of generic drugs, and c) high usage of generic drugs.<br><b>Conclusion: </b>The results of multivariate analysis showed that pharmacists are more willing to issue generic drugs unless doctors instruct them to use a brand-name drug.