Postmarket safety communications on drugs approved in Japan: A 25-year analysis.

Drug safety communications (DSCs) are essential tools for communicating important postmarket serious drug safety information to healthcare professionals and patients. Previous studies characterized DSCs issued by the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA); however, knowledge about the activities of the Pharmaceuticals and Medical Devices Agency (PMDA)/the Ministry of Health, Labor and Welfare (MHLW) is limited. This study characterized DSCs by the PMDA/MHLW in comparison with previously reported DSCs by the FDA and the EMA. We retrospectively analyzed 37 DSCs of 41 adverse drug reactions (ADRs) for 33 drugs in Japan from 1997 to 2022. Most DSCs were related to non-oncology drugs (30/37, 81.1%), and the median (interquartile range) time from approval to DSC issuance was 19 (10-51) months. Notably, the regulatory review reports and the latest labels before DSC issuance did not describe 16/28 (57.1%) and 12/37 (32.4%) of the ADRs related to DSCs, respectively. Most DSCs resulted in label revisions (36/37, 97.3%) and seven drugs were eventually withdrawn. Some DSC characteristics are similar among the PMDA/MHLW, the FDA, and the EMA; however, the number, contents, and range of new safety issues addressed by DSCs differ among the three jurisdictions. Our study emphasized the importance of continuous efforts to gather postmarket drug safety information because substantial ADRs that led to DSCs were recognized after approval and were associated with critical label revisions and withdrawals. Future studies are required to address global challenges for regulatory harmonization of safety-related regulatory actions.

Removal of α1-Microglobulin Using Post-Dilution Online Hemodiafiltration with Polymethylmethacrylate Membrane: An Open-Label, Single-Arm Study.

INTRODUCTION: The removal of low- and medium-molecular-weight proteins has been improved with online hemodiafiltration (OL-HDF) and hemodialysis using high-flux membranes; however, the outcomes of patients with end-stage kidney disease (ESKD) undergoing dialysis treatment are still worse than in the general population. α1-Microglobulin (α1-m), with a molecular weight of 33,000 Da, may contribute to dialysis-related disorders and mortality. However, the removal is insufficient even with current OL-HDF using the polysulfone (PS) membrane, which is common in Japan. Polymethylmethacrylate (PMMA) membranes can remove medium- to high-molecular-weight proteins by adsorption. This study aimed to assess the efficacy of removing medium- to high-molecular-weight proteins, such as α1-m and ß2-microglobulin (ß2-m), through post-dilution OL-HDF with PMMA (Post-PMMA). The assessment was conducted in comparison to pre-dilution OL-HDF with PS (Pre-PS), using an open-label, single-arm study. METHODS: Seven patients with ESKD on Pre-PS underwent Post-PMMA with replacement volume of 30 mL/min (low flow) and 50 mL/min (high flow). Clearance and removal rates of α1-m, ß2-m, small molecules, inflammatory cytokines, and albumin were measured at 60 and 240 min of treatment. RESULTS: Clearance rates of α1-m at 60 min were -2.8 ± 5.2 mL/min with Pre-PS, -0.4 ± 2.6 mL/min with Post-PMMA (low), and 0.6 ± 3.4 mL/min with Post-PMMA (high). The removal rate of α1-m was higher in Post-PMMA than that in Pre-HDF-PS (Post-PMMA [high] 17.7 ± 5.9%, Post-PMMA [low] 15.0 ± 5.6%, and Pre-PS 4.1 ± 5.5%). Adsorption clearance of ß2-m was increased with Post-PMMA. Albumin leakage in Post-PMMA was not higher than that in Pre-PS. CONCLUSION: The removal rate of α1-m with Post-PMMA was higher than that with Pre-PS. The PMMA membrane adsorbed ß2-m, suggesting the removal effect of medium- to high-molecular-weight proteins by the adsorption method. Since Post-PMMA effectively removes α1-m without excessive albumin leakage, it will be useful for patients with ESKD, especially those with a poor nutritional status.

Practical guidance to handle missing values in the 25-question Geriatric Locomotive Function Scale (GLFS-25): a simulation study.

OBJECTIVES: Despite the possible large number of missing values on the 25-question Geriatric Locomotive Function Scale (GLFS-25), how we should treat them is unknown. In a simulation study, we investigated how to handle missing values in the GLFS-25. DESIGN, SETTING AND PARTICIPANTS: We used three datasets with different participant characteristics: community dwellers who could walk by themselves, outpatients of orthopaedics owing to pain, and patients who required surgery for total knee replacement or lumbar spinal canal stenosis. OUTCOME MEASURES: The missing items of the datasets were artificially created, and four statistical methods, complete case analysis, multiple imputation, single imputation using individual mean, and single imputation using individual domain average, were compared in terms of bias and mean squared error. Simulation studies were conducted to compare them under varying numbers of participants with missing values (5%-40%) and under varying numbers of missing items of GLFS-25 (4-16). RESULTS: Multiple imputation had the lowest root mean squared error. Complete case analysis showed the largest bias, and the performances of the single imputation were between those methods. The relative performances were similar across the three datasets. The absolute bias of the single imputation was<0.1. The bias and mean squared error of multiple imputation and single imputation were comparable when the number of missing items was less than or equal to eight. CONCLUSIONS: Multiple imputation is preferable, although single imputation using subject average/subject domain average can be used with practically negligible bias as long as the number of missing items is up to 8 out of 25 items in each individual of the population.