Continuous evaluation of drug safety is needed following approval to determine adverse events (AEs) in patient populations with diverse backgrounds. Spontaneous reporting systems are an important source of information for the detection of AEs not identified in clinical trials and for safety assessments that reflect the real-world use of drugs in specific populations and clinical settings. The use of spontaneous reporting systems is expected to detect drug-related AEs early after the launch of a new drug. Spontaneous reporting systems do not contain data on the total number of patients that use a drug; therefore, signal detection by disproportionality analysis, focusing on differences in the ratio of AE reports, is frequently used. In recent years, new analyses have been devised, including signal detection methods focused on the difference in the time to onset of an AE, methods that consider the patient background and those that identify drug–drug interactions. However, unlike commonly used statistics, the results of these analyses are open to misinterpretation if the method and the characteristics of the spontaneous reporting system cannot be evaluated properly. Therefore, this review describes signal detection using data mining, considering traditional methods and the latest knowledge, and their limitations.

The objective of our study was to clarify the impact of adverse events associated with the initial course of outpatient chemotherapy on the quality of life of breast cancer patients. We conducted a survey to assess the quality of life in 48 breast cancer patients before and after receiving their first course of outpatient chemotherapy at Gifu Municipal Hospital. Patients completed the European Quality of Life 5 Dimensions and Quality of Life Questionnaire for Cancer Patients Treated with Anticancer Drugs before and after 1 course of outpatient chemotherapy. European Quality of Life 5 Dimensions utility value and Quality of Life Questionnaire for Cancer Patients Treated with Anticancer Drugs total score decreased significantly after chemotherapy (p<0.001 and p = 0.018, respectively). The mean scores for the activity, physical condition, and psychological condition subscales of the Quality of Life Questionnaire for Cancer Patients Treated with Anticancer Drugs decreased significantly after chemotherapy (p = 0.003, p<0.001, and p = 0.032, respectively), whereas the social relationships score increased significantly (p<0.001). Furthermore, in the evaluation of quality of life according to individual adverse events, the decrease in quality of life after chemotherapy in terms of the European Quality of Life 5 Dimensions utility value and the Quality of Life Questionnaire for Cancer Patients Treated with Anticancer Drugs total score was greater in anorexic patients than in non-anorexic patients (p = 0.009 and p<0.001, respectively). This suggests that anorexia greatly reduces quality of life. Our findings reveal that anticancer drug-related adverse events, particularly anorexia, reduce overall quality of life following the first course of outpatient chemotherapy in current breast cancer patients. These findings are extremely useful and important in understanding the impact of anticancer drug-related adverse events on quality of life.

Concomitant use of multiple drugs for therapeutic purposes is known as “polypharmacy situations,” which has been recognized as an important social problem recently. In polypharmacy situations, each drug not only induces adverse events (AEs) but also increases the risk of AEs due to drug–drug interactions (DDIs). The proportion of AEs caused by DDIs is estimated to be around 30% of unexpected AEs. The randomized clinical trials in pre-marketing typically focus emphasis on the verification of single drug safety and efficacy rather than the surveys of DDI, and therefore, patients on multiple drugs are usually excluded. However, unlike pre-marketing randomized clinical trials, in clinical practice (= post marketing), many patients use multiple drugs. The spontaneous reporting system is one of the significant sources drug safety surveillance in post-marketing. Commonly, signals of potential drug-induced AEs detected from this source are validated in real-world settings. Recently, not only methodological studies on signal detection of “single” drug, but also on several methodological studies on signal detection of DDIs have been conducted. On the other hand, there are few articles that systematically summarize the statistical methodology for signal detection of DDIs. Therefore, this article reviews the studies on the latest statistical methodologies from classical methodologies for signal detection of DDIs using spontaneous reporting system. This article describes how to calculate for each detection method and the major findings from the published literatures about DDIs. Finally, this article presented several limitations related to the currently used methodologies for signal detection of DDIs and suggestions for further studies.

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A relationship between Epstein-Barr virus (EBV) infection and cancer of lymphoid and epithelial tissues such as Burkitt's lymphoma, Hodgkin's disease, nasopharyngeal carcinoma (NPC), gastric carcinoma, and oral cancer has been reported. EBV is transmitted orally and infects B cells and epithelial cells. However, it has remained uncertain whether EBV plays a role in carcinogenesis of oral mucosal tissue. In the present study, we detected the EBV genome and latent EBV gene expression in normal mucosal epithelia, epithelial dysplasia, and oral squamous cell carcinoma (OSCC) to clarify whether EBV is involved in carcinogenesis of the oral cavity. We examined 333 formalin-fixed, paraffin-embedded tissue samples (morphologically normal oral mucosa 30 samples, gingivitis 32, tonsillitis 17, oral epithelial dysplasia 83, OSCC 150, and NPC 21). EBV latent infection genes (EBNA-2, LMP-1) were detected not only in OSCC (50.2 %, 10.7 %) but also in severe epithelial dysplasia (66.7 %, 44.4 %), mild to moderate epithelial dysplasia (43.1 %, 18.5 %), gingivitis (78.1 %, 21.9 %), and normal mucosa (83.3 %, 23.3 %). Furthermore, the intensity of EBV latent infection gene expression (EBER, LMP-1) was significantly higher in severe epithelial dysplasia (94.4 %, 72.2 %) than in OSCC (34.7 %, 38.7 %). These results suggest that EBV latent infection genes and their increased expression in severe epithelial dysplasia might play an important role in the dysplasia-carcinoma sequence in the oral cavity.