Statistical methods for exploring spontaneous adverse event reporting databases for drug-host factor interactions

Reversible bilateral central scotoma under scotopic conditions associated with oral semaglutide

Introduction

Semaglutide is a glucagon-like peptide-1 receptor agonist that treats type 2 diabetes mellitus and can be used as an adjunct for weight loss when combined with exercise and diet. Here we report a case of a bilateral, incongruent central visual scotoma under scotopic conditions in a board-certified ophthalmologist associated with semaglutide use that resolved quickly following medication discontinuation.

Case report

A 72-year-old male ophthalmologist (JAD) started 3.0 mg daily oral semaglutide (Rybelsus) to help with weight loss and seventeen days after treatment initiation developed a small, round central scotoma in his right eye that enlarged over several days. After two days a similar but smaller scotoma developed in his left eye. These symptoms were present only under scotopic conditions and were not visible in daylight or artificially lit conditions. When symptoms developed in the left eye, the medication was discontinued, and all symptoms completely resolved two days later. A subsequent clinical evaluation revealed no abnormalities on macular optical coherence tomography, fundus photography, fundus autofluorescence or Humphrey visual field.

Conclusions

This case of a bilateral central scotoma under scotopic conditions that resolved after medication discontinuation expands the knowledge of potential side effects from this increasingly popular diabetic and weight loss medication.

Subgroup disproportionality analysis of dementia-related adverse events with sacubitril/valsartan across geographical regions

This study aimed to evaluate the association between sacubitril/valsartan and dementia-related adverse events (AEs) in geographical subpopulations using subgroup disproportionality analysis. Cases from the FDA adverse event reporting system involving patients aged 60 or older with sacubitril/valsartan or angiotensin receptor blockers (ARBs) were analyzed. The adjusted reporting odds ratios (RORs) for dementia-related AEs were calculated for each continent. A total of 61,518 AEs associated with sacubitril/valsartan or ARBs were identified. Among these, 1441 were dementia-related AEs. In Asia, Europe, and Africa, the reporting risk of dementia-related AEs associated with sacubitril/valsartan was lower compared to ARBs (adjusted ROR, 0.57 [95% CI 0.31-1.01]; adjusted ROR, 0.89 [95% CI 0.69-1.14]; adjusted ROR, 0.40 [95% CI 0.27-0.61], respectively). In Latin America and Oceania, the reporting risk of dementia-related AEs associated with sacubitril/valsartan was similar to that associated with ARBs (adjusted ROR, 1.04 [95% CI 0.75-1.44]; adjusted ROR, 1.02 [95% CI 0.31-3.37], respectively). On the contrary, in North America, the reporting risk associated with sacubitril/valsartan was higher compared to ARBs (adjusted ROR, 1.29 [95% CI 1.10-1.53]). Although the ROR value did not meet the criteria for signal detection, the significantly greater than 1 ROR observed in North America suggests that caution may be warranted regarding potential dementia-related adverse events associated with sacubitril/valsartan.

Model driven method for exploring individual and confounding effects in spontaneous adverse event reporting databases

BACKGROUND

Spontaneous Adverse Event Reporting (SAER) databases play a crucial role in post-marketing drug surveillance. However, the traditional model-free disproportionality analysis has been challenged by the insufficiency in investigating subgroup and confounders. These issues result in significant low-precision and biases in data mining for SAER.

METHODS

The Model-Driven Reporting Odds Ratio (MD-ROR) was proposed to bridge the gap between SAER database and explainable models for exploring individual and confounding effects. MD-ROR is grounded in a well-designed model, rather than a 2 × 2 cross table, for estimating AE-drug signals. Consequently, individual and confounding effects can be parameterized based on these models. We employed simulation data and the FDA Adverse Event Reporting System (FAERS) database.

RESULT

The simulated data indicated the subgroup effects estimated by MD-ROR were unbiased and efficient. Moreover, the adjusted-MD-ROR demonstrated greater robustness against confounding biases than the crude ROR. Applying our method to the FAERS database suggested higher occurrences of drug interactions and cardiac adverse events induced by Midazolam in females compared to males.

CONCLUSION

The study underscored that MD-ROR holds promise as a method for investigating individual and confounding effects in SAER databases.

Post-marketing safety of finerenone: a disproportionality analysis of the FDA adverse event reporting system

BACKGROUND

Finerenone was approved for the treatment of type 2 diabetes patients with chronic kidney disease. However, the post-marketing safety of finerenone in the real world is unknown.

METHODS

The quarterly reported data related to finerenone from the third quarter of 2021 to the second quarter of 2023 were collected by using the FAERS database. Two disproportionality analysis methods were estimated by using Reporting odds ratio (ROR) and Bayesian confidence propagation neural network (BCPNN).

RESULTS

A total of 1067 adverse events (AEs) were included. Twenty-four kinds of system organ classes (SOCs) were classified for the organs and systems involved and 39 AEs with significant safety signals were identified using ROR and BCPNN at the preferred terms (PTs) level. Most AEs originated from the United States, and the median time to onset of AEs was 13 days. Three hundred and fifty-one (55.5%) reported serious outcome. The proportion of medication combinations was 29.0%. The most commonly reported AEs were the glomerular filtration rate decreased. Safety signals have also been observed in new and unexpected AEs.

CONCLUSION

The analysis of the AE signals may contribute to minimizing the risks associated with its use.

Detection Algorithms for Simple Two-Group Comparisons Using Spontaneous Reporting Systems

Medical science has often used adult males as the standard to establish pathological conditions, their transitions, diagnostic methods, and treatment methods. However, it has recently become clear that sex differences exist in how risk factors contribute to the same disease, and these differences also exist in the efficacy of the same drug. Furthermore, the elderly and children have lower metabolic functions than adult males, and the results of clinical trials on adult males cannot be directly applied to these patients. Spontaneous reporting systems have become an important source of information for safety assessment, thereby reflecting drugs' actual use in specific populations and clinical settings. However, spontaneous reporting systems only register drug-related adverse events (AEs); thus, they cannot accurately capture the total number of patients using these drugs. Therefore, although various algorithms have been developed to exploit disproportionality and search for AE signals, there is no systematic literature on how to detect AE signals specific to the elderly and children or sex-specific signals. This review describes signal detection using data mining, considering traditional methods and the latest knowledge, and their limitations.

Adverse events with pemigatinib in the real world: a pharmacovigilance study based on the FDA Adverse Event Reporting System

BACKGROUND

To data, there is insufficient large-scale data on the adverse events (AEs) of pemigatinib. Consequently, we conducted a pharmacovigilance study utilizing the Food and Drug Administration Adverse Event Reporting System (FAERS) database to investigate these AEs.

RESEARCH DESIGN AND METHODS

The OpenVigil 2.1 was used to extract AE data from the FAERS database. Proportional reporting ratio (PRR), reporting odds ratios (ROR), and bayesian analysis confidence propagation neural network (BCPNN) were used to assess the association between pemigatinib and AEs. The clinical importance of AE signals were prioritized using a rating scale.

RESULTS

A total of 848 AE reports were retrieved from the FAERS database, and 421 AE reports were identified after the data cleaning process. After accounting for indication bias and removal of medication errors, 59 positive signals were finally included. The 59 positive signals emerged in 11 system organ classes (SOCs). Besides, 19 positive AEs were classified as moderate clinical priority, while 40 were deemed weak in terms of priority. 9 positive AEs were not included in the drug label.

CONCLUSIONS

This study provided valuable evidence for clinicians to mitigate the risk of pemigatinib-related toxicities in the real world.

Pharmacovigilance Study of Infigratinib: A Safety Analysis of the FDA Adverse Event Reporting System

BACKGROUND

Infigratinib is a fibroblast growth factor receptor (FGFR)-specifc tyrosine kinase inhibitor indicated for the treatment of patients with previously treated, unresectable, locally advanced or metastatic cholangiocarcinoma. However, few studies have been conducted to evaluated the safety of infigratinib in the real world. In this study, we conducted a pharmacovigilance study to evaluate the adverse events (AEs) of infigratinib by using the Food and Drug Administration Adverse Event Reporting System (FAERS) database.

METHODS

OpenVigil 2.1 was employed to extract the FAERS database. Descriptive analysis was used to describe the characteristics of infigratinib-associated AE reports. Disproportionality analysis was performed by calculating the proportional reporting ratio (PRR), reporting odds ratios (ROR), and Bayesian analysis confidence propagation neural network (BCPNN) to detect positive signals.

RESULTS

Our findings revealed 149 AE reports, among which 36 significant signals were identified. These significant AE signals were mainly observed in gastrointestinal disorders (N = 26, ROR = 26.03, PRR = 8.44, information component [IC] = 3.08) and skin and subcutaneous tissue disorders (N = 21, ROR = 92.13, PRR = 40.41, IC = 5.34). Notably, dehydration and skin exfoliation were unexpected AEs, but had relatively high signal intensities (ROR = 29.75, PRR = 26.64, IC = 4.74; ROR = 50.61, PRR = 45.24, IC = 5.50, respectively) despite not being listed on the drug label. Furthermore, our analysis showed that infigratinib dose differed statistically between severe and non-severe reports (113.82 ± 16.13 mg vs 125 ± 0.00 mg, t = - 4.28; p < 0.001). However, there were no significant differences in sex, age, and types of AEs between the two groups (p  = 0.06, p  = 0.86, and p = 0.93, respectively).

CONCLUSIONS

These findings suggest that gastrointestinal and skin toxicities are the most common adverse reactions for infigratinib. It is important to recognize skin exfoliation and dehydration in clinical practice, as they are unexpected AEs. Additionally, our study indicates that infigratinib dose may correlate with an increased risk of AE severity, highlighting the need for dose adjustment of infigratinib when exposure to the drug is increased due to internal or external factors.