Exploring the Mechanisms Underlying Drug-Induced Fractures Using the Japanese Adverse Drug Event Reporting Database

Fractures occur when bones become fragile and are subjected to external forces as occurring during falls. The use of drugs that increase bone fragility or fall risk increases the risk of fracture. This study investigates drug-induced fractures reported in the Japanese Adverse Drug Event Report (JADER) database in patients using 4892 drugs. Atypical femur fracture was the most frequently reported fracture, and 58 other fractures were also reported. Using Volcano plots and multiple logistic regression analysis, we identified the risk factors for drug-induced fractures as being female, of older age, higher body mass index, and using one of 90 drugs. The drug groups significantly associated with drug-induced fractures included bone resorption inhibitors, antiviral drugs, dopaminergic drugs, corticosteroids, and sleep sedatives. Principal component analysis was used to examine the relationship between the use of specific drugs and the site of drug-induced fracture. Bone resorption inhibitors and corticosteroids were associated with atypical femur fractures, jaw fractures, and ulna fractures through an osteoclast-mediated process. Other drugs were found to increase fracture risk via non-osteoclast-mediated mechanisms. These findings suggest that many drugs can result in drug-induced fractures through a variety of mechanisms.

Analysis of anticholinergic adverse effects using two large databases: The US Food and Drug Administration Adverse Event Reporting System database and the Japanese Adverse Drug Event Report database

Introduction Anticholinergic adverse effects (AEs) are a problem for elderly people. This study aimed to answer the following questions. First, is an analysis of anticholinergic AEs using spontaneous adverse drug event databases possible? Second, what is the main drug suspected of inducing anticholinergic AEs in the databases? Third, do database differences yield different results? Methods We used two databases: the US Food and Drug Administration Adverse Event Reporting System database (FAERS) and the Japanese Adverse Drug Event Report database (JADER) recorded from 2004 to 2020. We defined three types of anticholinergic AEs: central nervous system (CNS) AEs, peripheral nervous system (PNS) AEs, and a combination of these AEs. We counted the number of cases and evaluated the ratio of drug–anticholinergic AE pairs between FAERS and JADER. We computed reporting odds ratios (RORs) and assessed the drugs using Beers Criteria®. Results Constipation was the most reported AE in FAERS. The ratio of drug–anticholinergic AE pairs was statistically significantly larger in FAERS than JADER. Overactive bladder agents were suspected drugs common to both databases. Other drugs differed between the two databases. CNS AEs were associated with antidementia drugs in FAERS and opioids in JADER. In the assessment using Beers Criteria®, signals were detected for almost all drugs. Between the two databases, a significantly higher positive correlation was observed for PNS AEs (correlation coefficient 0.85, P = 0.0001). The ROR was significantly greater in JADER. Conclusions There are many methods to investigate AEs. This study shows that the analysis of anticholinergic AEs using spontaneous adverse drug event databases is possible. From this analysis, various suspected drugs were detected. In particular, FAERS had many cases. The differences in the results between the two databases may reflect differences in the reporting countries. Further study of the relationship between drugs and CNS AEs should be conducted.

Evaluation of the Expression Profile of Antibiotic-Induced Thrombocytopenia Using the Japanese Adverse Drug Event Report Database

Drug-induced thrombocytopenia (DITP) can be triggered by antibiotics; however, the details remain unclear. Here, we evaluated the expression profiles of DITP using the Japanese Adverse Drug Event Report (JADER) database. We analyzed reports of DITP between April 2004 and January 2021 from the JADER database. The reporting odds ratio (ROR) and 95% confidence interval (CI) were used to detect DITP signals. Factors thought to affect DITP, such as male sex and an age of at least 60 years, were added as covariates. We evaluated the time-to-onset profile and hazard type using the Weibull shape parameter. The JADER database contained 1,048,576 reports. Twelve of 60 antibiotics showed signals for DITP; the RORs (95% CIs) for ampicillin/sulbactam, ceftazidime, cefozopran, ciprofloxacin, fluconazole, fos-fluconazole, linezolid, pazufloxacin, piperacillin/tazobactam, teicoplanin, trimethoprim/sulfamethoxazole, and voriconazole were 1.75 (1.41-2.16), 1.77 (1.42-2.18), 1.35 (1.06-1.72), 2.56 (2.19-2.98), 1.93 (1.67-2.23), 2.08 (1.76-2.46), 5.29 (2.73-9.60), 1.92 (1.51-2.41), 1.54 (1.05-2.19), 1.47 (1.16-1.84), 1.92 (1.73-2.14), and 2.32 (1.59-3.30), respectively. In multiple logistic regression analysis, 7 and 6 antibiotics were detected for the factors age and male sex, respectively. The median times-to-onset of DITP for ciprofloxacin (oral treatment), fluconazole, linezolid, piperacillin/tazobactam, and trimethoprim/sulfamethoxazole were 91, 91, 11.5, 10, and 9 days, respectively. Furthermore, the 95% CI of the Weibull shape parameter β for these antibiotics was above and excluded 1, indicating that the antibiotics were the wear out failure type. We revealed the expression profiles of DITP following treatment with 12 antibiotics.

Lack of Major Involvement of Common CYP2C Gene Polymorphisms in the Risk of Developing Cross-Hypersensitivity to NSAIDs

Cross-hypersensitivity to non-steroidal anti-inflammatory drugs (NSAIDs) is a relatively common, non-allergic, adverse drug event triggered by two or more chemically unrelated NSAIDs. Current evidence point to COX-1 inhibition as one of the main factors in its etiopathogenesis. Evidence also suggests that the risk is dose-dependent. Therefore it could be speculated that individuals with impaired NSAID biodisposition might be at increased risk of developing cross-hypersensitivity to NSAIDs. We analyzed common functional gene variants for CYP2C8, CYP2C9, and CYP2C19 in a large cohort composed of 499 patients with cross-hypersensitivity to NSAIDs and 624 healthy individuals who tolerated NSAIDs. Patients were analyzed as a whole group and subdivided in three groups according to the main enzymes involved in the metabolism of the culprit drugs as follows: CYP2C9, aceclofenac, indomethacin, naproxen, piroxicam, meloxicam, lornoxicam, and celecoxib; CYP2C8 plus CYP2C9, ibuprofen and diclofenac; CYP2C19 plus CYP2C9, metamizole. Genotype calls ranged from 94 to 99%. No statistically significant differences between patients and controls were identified in this study, either for allele frequencies, diplotypes, or inferred phenotypes. After patient stratification according to the enzymes involved in the metabolism of the culprit drugs, or according to the clinical presentation of the hypersensitivity reaction, we identified weak significant associations of a lower frequency (as compared to that of control subjects) of CYP2C8*3/*3 genotypes in patients receiving NSAIDs that are predominantly CYP2C9 substrates, and in patients with NSAIDs-exacerbated cutaneous disease. However, these associations lost significance after False Discovery Rate correction for multiple comparisons. Taking together these findings and the statistical power of this cohort, we conclude that there is no evidence of a major implication of the major functional CYP2C polymorphisms analyzed in this study and the risk of developing cross-hypersensitivity to NSAIDs. This argues against the hypothesis of a dose-dependent COX-1 inhibition as the main underlying mechanism for this adverse drug event and suggests that pre-emptive genotyping aiming at drug selection should have a low practical utility for cross-hypersensitivity to NSAIDs.