Safety of tildrakizumab: a disproportionality analysis based on the FDA adverse event reporting system (FAERS) database from 2018-2023.

Background: Tildrakizumab, the IL-23 inhibitor, is used to treat plaque psoriasis and psoriatic arthritis. Many studies have reported adverse drug reactions (ADRs) associated with Tildrakizumab. Objective: The aim of this study was to describe ADRs associated with Tildrakizumab monotherapy by mining data from the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS). Methods: The signals of Tildrakizumab-associated ADRs were quantified using disproportionality analyses such as the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the Bayesian confidence propagation neural network (BCPNN), and the multiitem gamma Poisson shrinker (MGPS) algorithms. Results: A total of 10,530,937 reports of ADRs were collected from the FAERS database, of which 1,177 reports were identified with tildrakizumab as the "primary suspect (PS)". Tildrakizumab-induced ADRs occurred against 27 system organ classes (SOCs). A total of 32 significant disproportionality Preferred Terms (PTs) conformed to the algorithms. Unexpected significant ADRs such as coronavirus infection, herpes simplex, diverticulitis, atrial fibrillation and aortic valve incompetence were also possible. The median time to onset of Tildrakizumab-associated ADRs was 194 days (interquartile range [IQR] 84-329 days), with the majority occurring, within the first 1 and 3 months after initiation of Tildrakizumab. Conclusion: This study identified a potential signal for new ADRs with Tildrakizumab, which might provide important support for clinical monitoring and risk prediction.

The top 100 most cited articles in the treatment of basal cell carcinoma over the last decade: A bibliometric analysis and review.

Basal cell carcinoma (BCC) represents the most prevalent cancer globally. The past decade has witnessed significant advancements in BCC treatment, primarily through bibliometric studies. Aiming to perform a comprehensive bibliometric analysis of BCC treatments to comprehend the research landscape and identify trends within this domain, a dataset comprising 100 scientific publications from the Web of Science Core Collection was analyzed. Country co-operation, journal co-citation, theme bursts, keyword co-occurrence, author co-operation, literature co-citation, and field-specific references were examined using VOSviewer and CiteSpace visualization tools. These articles, published between 2013 and 2020, originated predominantly from 30 countries/regions and 159 institutions, with the USA and Germany at the forefront, involving a total of 1118 authors. The keyword analysis revealed significant emphasis on the hedgehog pathway, Mohs micrographic surgery, and photodynamic therapy. The research shows developed nations are at the forefront in advancing BCC therapies, with significant focus on drugs targeting the hedgehog pathway. This treatment avenue has emerged as a crucial area, meriting considerable attention in BCC therapeutic strategies.

A Retrospective Analysis of Risk Factors for Atopic Dermatitis Severity.

Background: Atopic dermatitis (AD) has the highest burden of any skin disease; however, the severity-associated factors remain unclear. Objective: To evaluate potential severity-associated factors of AD and to design and validate a severity prediction model to inform the management of AD patients. Methods: A cross-sectional study of 900 AD patients was conducted from December 2021 to October 2022 at our hospital. The primary outcome was disease severity, categorized as mild, moderate, or severe using the scoring atopic dermatitis index. Ordinal logistic regression and bootstrapped validation were used to derive and internally validate the model. Results: Increasing age, elevated eosinophil level, higher economic status, and urban residence were associated with severe AD. Breastfeeding, disinfectants and topical emollients use, and short duration of bathing were associated with mild AD. In the prediction model, predictors included age, eosinophil and economic status, residence, feeding, disinfectants and emollients use, and duration of bathing. Prediction models demonstrated good discrimination (bias-corrected concordance index [c-index] = 0.72) and good calibration. Conclusion: Risk factors for the severity of AD were identified that could aid the early prediction of AD progression. The predictive model included variables that are easily evaluated and could inform personalized prevention and therapy.