Indices for dose regulation for irinotecan (CPT-11) toxicity are diarrhea, reduction in neutrophil (NEUT) count, and level of UDP-glucuronyltransferase (UGT), which is involved in conjugation of the active metabolite SN-38. An association with the glucuronosyltransferase (UGT) 1A1 gene polymorphism has been reported. Therefore, we investigated UGT1A1 gene polymorphism and the incidence of side effects in patients who received FOLFIRI±αat our institution from November 2008 to March 2017. UGT1A1 genetic testing was performed, and 25 cases treated with FOLFIRI±αwere included. Age, sex, height, weight, and body surface area (BSA)were analyzed. UGT1A1 genotype was determined as follows:*1/*6 heterozygous (*6 he genotype), *1/*28 heterozygous (*28 he genotype), homozygous, and compound heterozygous (compound genotype). We also investigated the combination drugs (classified as he genotype) and wild type. In addition, the initial dose of CPT-11/5-FU bolus, initial relative dose intensity (RDI) (％), and blood toxicity in the first course were investigated. Mean age was 70.4±8.6 years, UGT1A1 genotype was*28 he in 5 cases, *6 he in 6 cases, and wild type in 14 cases. There were no cases of compound he or homo type. There was no significant difference between the initial dose and the initial RDI. Reduction in leukocyte count was seen in 2 cases with Grade(G)3*6 he and in 2 cases with G4*28 he. Platelet count was reduced in 2 cases with G4*28 he, 2 cases with G4*2 he, 2 cases with G4*28 he, and in 2 cases with*6 he. In this study, there was no significant difference in the initial dose and initial RDI for*6 he, *28 he, and wild type. However, *28 he and *6 he showed hematologic toxicity of G3 or more. Also, the frequency of the he genotype tended to be higher than that of wild type. Thus, it is necessary to clarify the significance of weight loss in the he type in future.

There have been few reports on suvorexant (SUV), a benzodiazepine-agonist hypnotic, used concomitantly with benzodiazepines (BZDs) or non-benzodiazepines (non-BZDs). Therefore, we investigated the use of SUV in patients taking BZDs and non-BZDs. Subjects were 73 individuals who were prescribed SUV while taking either BZDs or non-BZDs for 4 weeks or more from November 2015 to the end of March 2017. Subjects were divided into three groups as follows: those with no weight change compared to baseline (the non-weight loss group (n = 32)), those with some weight loss (the weight loss group n = 23)), and those who discontinued the drugs (the withdrawal group (n = 18)). Age, sex, presence or absence of antipsychotic medication, continuation rate of SUV in each week after 4 weeks, and diazepam equivalent value before and after SUV administration were compared in each group. In addition, we investigated the occurrence of side effects after SUV initiation. When comparing the SUV continuation rate at 24 weeks in each group, no significant difference was found between the 3 groups, but at 8 weeks, the weight loss group showed significantly decreased rates compared to the non-weight-loss group. When diazepam conversion values were compared before and after BZD and non-BZD administration, significant differences were found in the non-weight-loss group, weight-loss group, and withdrawal group before administration. Side effects were 18.8％ in the non-weightloss group, 13.0％ in the weight loss group, and 16.7％ in the withdrawal group; 6.3％, 8.6％, and 16.7％ were in the central nervous system. It was thought that continuation rate might fall by concomitant use of SUV with BZDs or non-BZDs. For patients using SUV when taking BZDs or non-BZDs, it is desirable not only to reduce or stop the BZDs or non-BZDs, but also to be aware of withdrawal symptoms. This is because side effects may increase following discontinuation. Despite causing weight reduction, it is also important to consider improved safety.

Engaru-Kosei General Hospital expanded its pharmacist duties in hospital wards in April 2018 following the nationwide switch to out-of-hospital prescriptions. The purpose of this study was to examine the effect of pharmacists’ ward duties on nursing duties. Pharmacists expanded their duties to cover drug distribution management, infusions of total parenteral nutrition (TPN) mixed with drugs, and aseptic preparation of 24-h infusions (including peripheral parenteral nutrition). The effects were compared between April 2018 before the expansion of duties and May-September 2018 after the expansion, and we compared the number of meetings set up to discuss nurses’ overtime hours and patient problems. In addition, interviews were conducted about the changes experienced on site. Drug distribution management averaged 3,150 cases/month. The number of TPN mixed infusions was 25 cases/month before expansion and this increased to 88 cases/month after expansion. The number of mixed injections of 24-h infusions was 296/month. Nurses' overtime hours did not decrease significantly, but the number of meetings increased from 47/month to 79.4/month. In the interviews, positive responses were obtained about, for example, the increased number of meetings held and more time for patient care. The pharmacist and the nurse collaborated to improve work by using their expertise, we think that the results obtained from work improvement contributed to the improvement of medical quality and medical safety.

Objective: The risk management plan (RMP) is a useful information source for healthcare professionals, including pharmacists, to ensure drug safety. The “risk minimization activities” (RMA) of the RMP are especially important elements for healthcare professionals. It is known that “Medication Guides for Patients” (MGP) and “Early post-marketing phase vigilance” (EPPV) are items listed as part of the RMA. However, the creation of MGPs and the implementation of EPPVs are not performed for all medicines. In a previous study, it was difficult to evaluate this sufficiently with the safety specifications. The aim of this investigation was to evaluate RMAs, especially MGPs and EPPVs, not in terms of the safety specifications of RMP.Methods: The previously published RMPs of 177 drugs were obtained on February 22,2016, and used in the analysis. The relationship between the creation of the MGP and the description in the RMA and the relationship between the conduct described in the EPPV and the description in RMA was investigated for each medicine.Results: An MGP was created in 151 of the analyzed drugs. Of these, it was not listed in the RMA of 40 drugs. In contrast, EPPV was not listed in RMA in 2 out of 33 drugs when underway. EPPV was described in the RMA of 33 of the EPPV finished drugs. The time lag from the end of EPPV until the revision of the RMP was 4.5 month son average.Conclusion: MGPs and EPPVs are created especially for drugs requiring patient education, information provision, or safety monitoring. Therefore, for drugs for which MGPs or EPPVs are required, they should be listed in the RMA. In this study, the time lag of RMP revision was also highlighted as a problem. In order to promote the utilization of RMP by pharmacists, these issues should be resolved.

Objective: Risk Management Plan (RMP) is created and submitted by a pharmaceutical company while applying for new drug approval; it is published to be used by healthcare professionals. For example, healthcare professionals utilize RMP when considering whether to adopt a drug. However, there is no stipulation for the release date of RMPs; moreover, surveys regarding this are limited. We conducted a cross-sectional survey on the relationship between RMP-related timing and regulatory affairs-related timing.Methods: The surveyed drugs were those for which the first version of RMP was notified by PMDA Medinavi (mail delivery service) in FY2014 and FY2018. We examined regulatory affairs-related timing (i.e., “manufacturing and marketing approval date,” “drugprice standards listing date,” and “release date”) and RMP-related timing (i.e., “RMP creation date” and “Medinavi delivery date”).Results: For 7 of 43 items in FY2014 and 5 of 41 items in FY2018, the “RMP creation date” occurred later than the “drug-price standards listing date.” For one item in FY2014, the “RMP creation date” occurred later than the “release date.” For 12 items in FY2014 and 13 items in FY2018, the “Medinavi delivery date” occurred later than the “release date.”Conclusion: No considerable difference was confirmed between FY2014 and FY2018 regarding RMP-related timing and regulatory affairs timing. It was confirmed that there were several items for which the RMP creation occurred later than drug-price standard listing and items for which the publishing notice by Medinavi was delayed for drug marketing release. To promote the utilization of RMPs by healthcare professionals, RMPs must be created and published without delay.

Drug therapy is necessary to treat metastatic and recurrent breast cancer. In Japan, two types of cyclin-dependent kinases (i.e., CDK4/6 inhibitors) are covered under the national healthinsurance system: palbociclib (since December 2017) and abemaciclib (since November 2018). Although there are many reports on the use and side effects of palbociclib in clinical practice, there are few such reports on abemaciclib. Therefore, we investigated the rate of neutropenia and associated background factors in patients taking abemaciclib. Of the 39 patients taking abemaciclib recruited for the study, 22 satisfied the inclusion criteria. Of these, 7 developed Grade 3 or higher neutropenia and had a significantly lower body weight and body mass index (BMI). Furthermore, the white blood cell and neutrophil counts before administration were significantly lower in the expression group compared with the non-expressing group. To predict the development of Grade 3 or higher neutropenia, the receiver operating characteristic (ROC) curve was used to calculate a BMI cut-off value of 23.9 (specificity 85.7%, sensitivity 73.3%, area under the ROC curve 0.80). Based on this cut-off value, BMI was divided into two groups (<23.9 and ≥23.9) and Fisher's exact test was performed. Patients with a low body mass index were more likely to develop Grade 3 or higher neutropenia as a result of increased dosage per kilogram body weight, while among patients with BMI < 25, those with BMI < 23.9 were at high risk of developing Grade 3 or higher neutropenia. Accordingly, caution is required in the treatment of such patients.

Sodium glucose co-transporter 2 (SGLT2) inhibitors typically have various secondary effects in addition to the hypoglycemic effect. Therefore, we examined their effectiveness and other secondary effects. We targeted 86 patients with type 2 diabetes treated with SGLT2 inhibitors for the first time from June 2014 to the end of March 2017 at our hospital. Mean body mass index (BMI) was 28.69±4.91kg/m2. Body weight, BMI, and levels of hemoglobin A1c (HbA1c), aspartate aminotransferase (AST), alanine aminotransferase (ALT), γ-glutamyl transpeptidase (γ-GTP), estimated glomerular filtration rate (eGFR), triglyceride (TG) and uric acid (UA) were significantly lower,while hematocrit (HCT), blood urea nitrogen (BUN), creatinine (Cre), and high-density lipoprotein cholesterol were significantly higher 2 months after than before administration of SGLT2 inhibitors. A significant negative correlation was observed between HbA1c, body weight, AST, ALT, γ-GTP, BUN, low-density lipoprotein cholesterol (LDL-C), and change in UA before and 2 months after administration of SGLT2 inhibitors. HbA1c was lower in patients with high HbA1c before treatment, and weight loss was noted in patients with increased body weight before treatment. These results suggest that SGLT2 inhibitors may be highly effective in patients with type 2 diabetes with uncontrolled obesity. In addition, potential risk factors for cardiovascular events and deranged liver function test values were identified, and there was a possibility that long-term SGLT2 inhibitor use could induce cardiovascular events, but with possible improvement of fatty liver. However, because it was observed that HCT was elevated and renal function was impaired, it may be necessary to administer rehydration therapy in the initial stages of treatment and to continuously monitor renal function.

Objective: The differences in clinical outcomes in hospitalized patients with hematological disorders (HD) who developed either coronavirus disease 2019 (COVID-19) or seasonal influenza (SI) are not fully understood. To examine these differences, we retrospectively analyzed the baseline characteristics and clinical outcomes of hospitalized patients with HD admitted from 2016 to 2021.Patients and Methods: Patients with HD who developed COVID-19 (in the past 1 year) (n=21) or SI (in the past 5 years) (n=23) in the Department of Hematology/Oncology, Asahikawa Kosei General Hospital were evaluated.Results: The median ages of the patients with HD with either COVID-19 or SI were 80 and 68 years, respectively (P=0.03). The groups showed no significant differences in sex ratio, body mass index, or Eastern Cooperative Oncology Group performance status. In the COVID-19 and SI groups, the most common primary diseases were diffuse large B-cell lymphoma (43%) and multiple myeloma (39%), respectively. The median numbers of days of oxygen administration (8 vs. 0 days), quarantine (25 vs. 6 days), and hospitalization (72 vs. 21 days) were significantly higher in HD patients with COVID-19 than those in HD patients with SI (all P<0.001). The overall 90-day survival of patients with HD and COVID-19 was significantly shorter than that of patients with HD and SI (P=0.019). Moreover, patients with HD and COVID-19 had a higher risk of in-hospital mortality (43% vs. 9%; odds ratio, 7.50; 95% confidence interval, 1.26–82.4; P=0.01) compared to patients with HD and SI.Conclusion: Patients with HD and COVID-19 required longer periods of in-hospital medical and showed poorer survival than those with SI. During the COVID-19 pandemic, hematologists should closely monitor the condition of patients with COVID-19 to closely monitor their condition to prevent deaths.

Purpose: The objective of this study was to assess the performance of ChatGPT (GPT-4) on all items, including those with diagrams, in the Japanese National License Examination for Pharmacists (JNLEP) and compare it with the previous GPT-3.5 model’s performance. Methods: The 107th JNLEP, conducted in 2022, with 344 items input into the GPT-4 model, was targeted for this study. Separately, 284 items, excluding those with diagrams, were entered into the GPT-3.5 model. The answers were categorized and analyzed to determine accuracy rates based on categories, subjects, and presence or absence of diagrams. The accuracy rates were compared to the main passing criteria (overall accuracy rate ≥62.9%). Results: The overall accuracy rate for all items in the 107th JNLEP in GPT-4 was 72.5%, successfully meeting all the passing criteria. For the set of items without diagrams, the accuracy rate was 80.0%, which was significantly higher than that of the GPT-3.5 model (43.5%). The GPT-4 model demonstrated an accuracy rate of 36.1% for items that included diagrams. Conclusion Advancements that allow GPT-4 to process images have made it possible for LLMs to answer all items in medical-related license examinations. This study’s findings confirm that ChatGPT (GPT-4) possesses sufficient knowledge to meet the passing criteria.

Purpose: The objective of this study was to assess the performance of ChatGPT (GPT-4) on all items, including those with diagrams, in the Japanese National License Examination for Pharmacists (JNLEP) and compare it with the previous GPT-3.5 model’s performance. Methods: The 107th JNLEP, conducted in 2022, with 344 items input into the GPT-4 model, was targeted for this study. Separately, 284 items, excluding those with diagrams, were entered into the GPT-3.5 model. The answers were categorized and analyzed to determine accuracy rates based on categories, subjects, and presence or absence of diagrams. The accuracy rates were compared to the main passing criteria (overall accuracy rate ≥62.9%). Results: The overall accuracy rate for all items in the 107th JNLEP in GPT-4 was 72.5%, successfully meeting all the passing criteria. For the set of items without diagrams, the accuracy rate was 80.0%, which was significantly higher than that of the GPT-3.5 model (43.5%). The GPT-4 model demonstrated an accuracy rate of 36.1% for items that included diagrams. Conclusion Advancements that allow GPT-4 to process images have made it possible for LLMs to answer all items in medical-related license examinations. This study’s findings confirm that ChatGPT (GPT-4) possesses sufficient knowledge to meet the passing criteria.