A review of phase III clinical trials of US FDA-approved biologic therapies for chronic rhinosinusitis with nasal polyposis

ChatGPT for Automated Cross-Checking of Authors' Conflicts of Interest Against Industry Payments

OBJECTIVE

The Centers for Medicare & Medicaid Services "OpenPayments" database tracks industry payments to US physicians to improve research conflicts of interest (COIs) transparency, but manual cross-checking of articles' authors against this database is labor-intensive. This study aims to assess the potential of large language models (LLMs) like ChatGPT to automate COI data analysis in medical publications.

STUDY DESIGN

An observational study analyzing the accuracy of ChatGPT in automating the cross-checking of COI disclosures in medical research articles against the OpenPayments database.

SETTING

Publications regarding Food and Drug Administration-approved biologics for chronic rhinosinusitis with nasal polyposis: omalizumab, mepolizumab, and dupilumab.

METHODS

First, ChatGPT evaluated author affiliations from PubMed to identify those based in the United States. Second, for author names matching 1 or multiple payment recipients in OpenPayments, ChatGPT undertook a comparative analysis between author affiliation and OpenPayments recipient metadata. Third, ChatGPT scrutinized full article COI statements, producing an intricate matrix of disclosures for each author against each relevant company (Sanofi, Regeneron, Genentech, Novartis, and GlaxoSmithKline). A random subset of responses was manually checked for accuracy.

RESULTS

In total, 78 relevant articles and 294 unique US authors were included, leading to 980 LLM queries. Manual verification showed accuracies of 100% (200/200; 95% confidence interval [CI]: 98.1%-100%) for country analysis, 97.4% (113/116; 95% CI: 92.7%-99.1%) for matching author affiliations with OpenPayments metadata, and 99.2% (1091/1100; 95% CI: 98.5%-99.6%) for COI statement data extraction.

CONCLUSION

LLMs have robust potential to automate author-company-specific COI cross-checking against the OpenPayments database. Our findings pave the way for streamlined, efficient, and accurate COI assessment that could be widely employed across medical research.

Mast Cells in Aspirin-Exacerbated Respiratory Disease

PURPOSE OF REVIEW

Aspirin-exacerbated respiratory disease (AERD) is a syndrome of high type 2 inflammation and is known to critically involve mast cell activation. The mast cell is an important cell in the baseline inflammatory processes in the upper and lower airway by maintaining and amplifying type 2 inflammation. But it also is prominent in the hypersensitivity reaction to COX-1 inhibition which defines this condition.

RECENT FINDINGS

Recent work highlights the mast cell as a focal point in AERD pathogenesis. Using AERD as a specific model of both high type 2 asthma and chronic sinusitis, the role of mast cell activity can be better understood in other aspects of airway inflammation. Further dissecting out the mechanism of COX-1-mediated mast cell activation in AERD will be an important next phase in our understanding of NSAID-induced hypersensitivity as well as AERD pathophysiology.

IgE glycans promote anti-IgE IgG autoantibodies that facilitate IgE serum clearance via Fc Receptors

Background

Recent studies have shown that IgE glycosylation significantly impacts the ability of IgE to bind to its high-affinity receptor FcεRI and exert effector functions. We have recently demonstrated that immunizing mice with IgE in a complex with an allergen leads to a protective, glycan-dependent anti-IgE response. However, to what extent the glycans on IgE determine the induction of those antibodies and how they facilitate serum clearance is unclear.Therefore, we investigated the role of glycan-specific anti-IgE IgG autoantibodies in regulating serum IgE levels and preventing systemic anaphylaxis by passive immunization.

Methods

Mice were immunized using glycosylated or deglycosylated IgE-allergen-immune complexes (ICs) to induce anti-IgE IgG antibodies. The anti-IgE IgG antibodies were purified and used for passive immunization.

Results

Glycosylated IgE-ICs induced a significantly higher anti-IgE IgG response and more IgG-secreting plasma cells than deglycosylated IgE-ICs. Passive immunization of IgE-sensitized mice with purified anti-IgE IgG increased the clearance of IgE and prevented systemic anaphylaxis upon allergen challenge. Anti-IgE IgG purified from the serum of mice immunized with deglycosylated IgE-ICs, led to a significantly reduced elimination and protection, confirming that the IgE glycans themselves are the primary drivers of the protectivity induced by the IgE-immune complexes.

Conclusion

IgE glycosylation is essential for a robust anti-IgE IgG response and might be an important regulator of serum IgE levels.