堀井 剛史

BACKGROUND: Anamorelin is the first drug approved for the treatment of cancer cachexia, a debilitating condition characterized by weight loss, anorexia, and muscle mass depletion. Cachexia negatively affects a patient's quality of life, survival, and response to chemotherapy. Studies describing anamorelin use are currently limited to a small number of pancreatic cancer cases. OBJECTIVES: We aimed to examine the incidence and risk factors of adverse metabolic effects on glucose levels in cachexia patients with various carcinomas treated with anamorelin. METHOD: We used real-world data of patients who received anamorelin between August 2021 and July 2022 and were registered in the JMDC claims database. We investigated the impact of metabolic adverse effects on glucose in patients receiving anamorelin with respect to the following factors: sex (male), age (>75 years), types of carcinoma, history of diabetes mellitus (DM), and concomitant use of steroids. RESULTS: The incidence of adverse metabolic effects on glucose was 12.3%, and pancreatic cancer and history of DM were associated with adverse metabolic effects on glucose. The median onset of adverse metabolic effects on glucose was 17 days after anamorelin treatment. CONCLUSIONS: This study highlights the need to monitor and manage hyperglycemia in cachexia patients receiving anamorelin, especially in those with pancreatic cancer and a history of DM.

We aimed to compare the effects of cardiovascular disease risk in Japanese patients with type 2 diabetes on sodium-glucose cotransporter 2 inhibitors (SGLT2Is) or metformin. This retrospective, real-world cohort study was carried out using a claims database and propensity score matching; 58,402 eligible patients (29,201 per group) were included. The outcomes included nonfatal myocardial infarction, angina pectoris, nonfatal stroke, hospitalization for heart failure and composite end-points. The hazard ratio (HR) for the composite end-point was 0.79, which was lower for SGLT2Is than for metformin. For male patients (HR 0.76), patients aged <65 years (HR 0.94), patients aged ≥75 years (HR 0.78) and patients with body mass index ≥25 kg/m2 (HR 0.76), the HRs for the composite end-point were significantly lower in the SGLT2I group than in the metformin group. SGLT2Is might be superior to metformin in reducing the composite risk of cardiovascular disease in patients with type 2 diabetes.

INTRODUCTION: Hypoglycemia is listed as an adverse effect in the package inserts of not only hypoglycemic agents but also many other drugs. We aimed to clarify real-world factors related to an increased risk of hypoglycemia-related hospitalization (HRH) in Japanese patients with type 2 diabetes (T2D) on non-hypoglycemic agents that have been associated with hypoglycemia. RESEARCH DESIGN AND METHODS: This cross-sectional study was performed using data from the Medical Data Vision administrative claims database. We identified patients with T2D who were enrolled in the database between April 2014 and October 2019. Logistic regression analyses were performed to identify clinical factors associated with HRH due to non-hypoglycemic agents. RESULTS: Among 703 745 patients with T2D, 10 376 patients (1.47%) experienced HRH. The use of 332 non-hypoglycemic agents was associated with hypoglycemia. Multivariate analysis was performed to calculate OR for HRH. Seventy-five drugs had an OR greater than 1, and the values were significant. The OR was the highest for diazoxide (OR 15.5, 95% CI 4.87 to 49.3). The OR was higher than 2.0 for methylphenidate (OR 5.15, 95% CI 1.53 to 17.3), disulfiram (OR 4.21, 95% CI 2.05 to 8.62) and hydrocortisone (OR 2.89, 95% CI 1.11 to 7.51). CONCLUSION: This large retrospective analysis revealed that the risk of HRH from some non-hypoglycemic agents in patients with T2D may be increased. The results of this study are expected to support treatment planning by physicians and healthcare professionals involved in diabetes care.

BACKGROUND: We aimed to clarify the relationship between coronavirus disease 2019 (COVID-19) reinfection and basic disease and smoking status. METHODS: The electronic health records of 165,320 patients with COVID-19 from January 1, 2020, to August 27, 2021, were analyzed. Data on age, race, sex, smoking status (never, current, former), and basic disease were analyzed using Cox proportional hazard models. RESULTS: In total, 6,133 patients (3.7%) were reinfected. The overall reinfection rate for never, current, and former smokers was 4.2, 3.5, and 5.7%, respectively. Although the risk of reinfection was highest among former smokers aged ≥65 years (7.7% [422/5,460]), the reinfection rate among current smokers aged ≥65 years was 6.2% (341/5,543). Among reinfected patients, the number of basic diseases was higher in former smokers (2.41 ± 1.16) than in current (2.28 ± 1.07, P = 0.07) and never smokers (2.07 ± 1.05, P < 0.001). Former smokers who are older may have been exposed to factors that increase their risk of symptomatic COVID-19 reinfection.