Using natural language processing to characterize and predict homeopathic product-associated adverse events in consumer reviews: comparison to reports to FDA Adverse Event Reporting System (FAERS).

OBJECTIVE: Apply natural language processing (NLP) to Amazon consumer reviews to identify adverse events (AEs) associated with unapproved over the counter (OTC) homeopathic drugs and compare findings with reports to the US Food and Drug Administration Adverse Event Reporting System (FAERS). MATERIALS AND METHODS: Data were extracted from publicly available Amazon reviews and analyzed using JMP 16 Pro Text Explorer. Topic modeling identified themes. Sentiment analysis (SA) explored consumer perceptions. A machine learning model optimized prediction of AEs in reviews. Reports for the same time interval and product class were obtained from the FAERS public dashboard and analyzed. RESULTS: Homeopathic cough/cold products were the largest category common to both data sources (Amazon = 616, FAERS = 445) and were analyzed further. Oral symptoms and unpleasant taste were described in both datasets. Amazon reviews describing an AE had lower Amazon ratings (X2 = 224.28, P < .0001). The optimal model for predicting AEs was Neural Boosted 5-fold combining topic modeling and Amazon ratings as predictors (mean AUC = 0.927). DISCUSSION: Topic modeling and SA of Amazon reviews provided information about consumers' perceptions and opinions of homeopathic OTC cough and cold products. Amazon ratings appear to be a good indicator of the presence or absence of AEs, and identified events were similar to FAERS. CONCLUSION: Amazon reviews may complement traditional data sources to identify AEs associated with unapproved OTC homeopathic products. This study is the first to use NLP in this context and lays the groundwork for future larger scale efforts.

Serious Skin Injuries Following Exposure to Unapproved Mole and Skin Tag Removers.

Objective: We sought to describe skin injuries associated with unapproved topical mole and skin tag removers containing concentrated salicylic acid, Sanguinaria canadensis, or other caustic agents. Methods: We identified skin injuries associated with unapproved non-device topical mole and skin tag removers reported to the US Food and Drug Administration (FDA) through October 30, 2021 or described in Amazon consumer product reviews between 2019 and 2021. Results: We identified 38 cases, including 30 from Amazon consumer product reviews and eight reported to the FDA. Twenty-eight were from 2021. The most common reason for use was for mole and/or skin tag removal. Listed ingredients included salicylic acid, Sanguinaria canadensis, botanicals (includes homeopathic products), and calcium oxide. Seven cases involved products without ingredients listed. Adverse events included burns, pain, and ulceration, some resulting in permanent scarring and disfigurement. There were 14 facial injuries, including four adjacent to the eye. Reported treatments included antibiotics, hospital care, wound care, and dermatology advice to have a skin graft. Limitations: Limitations include underreporting of adverse events to the FDA, limited clinical details and potential bias in consumer reviews, and poor replicability of review searches due to the dynamic nature of the Amazon website. Conclusion: Unapproved, non-device topical mole and skin tag removers are associated with serious skin injuries. We found Amazon consumer reviews to be a novel and useful data source for safety surveillance of these types of skin products. When dermatologists are consulted about skin injuries, exposure to these products should be considered in the differential diagnosis.

Pentosan associated retinal pigmentary changes: FDA's perspective on an emerging postmarketing safety finding.

INTRODUCTION AND HYPOTHESIS: Recent publications describe pigmentary changes in the retina associated with the use of pentosan polysulfate sodium, the only FDA-approved oral agent for relief of bladder pain or discomfort associated with interstitial cystitis. METHODS: To evaluate this association, we reviewed data from the FDA Adverse Event Reporting System and published case reports and observational studies. RESULTS: The totality of clinical and epidemiology evidence does not resolve the question of causation between pentosan use and retinal pigmentary changes; however, several elements support a potential association. CONCLUSION: Here, we provide our perspective on the available evidence the agency weighed when retinal pigmentary changes were added to pentosan labeling. It is important for urogynecologists prescribing pentosan to be aware of this potential association and be vigilant about assessing eye health in pentosan users.

Comparison of Nicotine and Toxicant Exposure in Users of Electronic Cigarettes and Combustible Cigarettes.

Importance: Use of electronic cigarettes (e-cigarettes) is increasing. Measures of exposure to known tobacco-related toxicants among e-cigarette users will inform potential health risks to individual product users. Objectives: To estimate concentrations of tobacco-related toxicants among e-cigarette users and compare these biomarker concentrations with those observed in combustible cigarette users, dual users, and never tobacco users. Design, Setting, and Participants: A population-based, longitudinal cohort study was conducted in the United States in 2013-2014. Cross-sectional analysis was performed between November 4, 2016, and October 5, 2017, of biomarkers of exposure to tobacco-related toxicants collected by the Population Assessment of Tobacco and Health Study. Participants included adults who provided a urine sample and data on tobacco use (N = 5105). Exposures: The primary exposure was tobacco use, including current exclusive e-cigarette users (n = 247), current exclusive cigarette smokers (n = 2411), and users of both products (dual users) (n = 792) compared with never tobacco users (n = 1655). Main Outcomes and Measures: Geometric mean concentrations of 50 individual biomarkers from 5 major classes of tobacco product constituents were measured: nicotine, tobacco-specific nitrosamines (TSNAs), metals, polycyclic aromatic hydrocarbons (PAHs), and volatile organic compounds (VOCs). Results: Of the 5105 participants, most were aged 35 to 54 years (weighted percentage, 38%; 95% CI, 35%-40%), women (60%; 95% CI, 59%-62%), and non-Hispanic white (61%; 95% CI, 58%-64%). Compared with exclusive e-cigarette users, never users had 19% to 81% significantly lower concentrations of biomarkers of exposure to nicotine, TSNAs, some metals (eg, cadmium and lead), and some VOCs (including acrylonitrile). Exclusive e-cigarette users showed 10% to 98% significantly lower concentrations of biomarkers of exposure, including TSNAs, PAHs, most VOCs, and nicotine, compared with exclusive cigarette smokers; concentrations were comparable for metals and 3 VOCs. Exclusive cigarette users showed 10% to 36% lower concentrations of several biomarkers than dual users. Frequency of cigarette use among dual users was positively correlated with nicotine and toxicant exposure. Conclusions and Relevance: Exclusive use of e-cigarettes appears to result in measurable exposure to known tobacco-related toxicants, generally at lower levels than cigarette smoking. Toxicant exposure is greatest among dual users, and frequency of combustible cigarette use is positively correlated with tobacco toxicant concentration. These findings provide evidence that using combusted tobacco cigarettes alone or in combination with e-cigarettes is associated with higher concentrations of potentially harmful tobacco constituents in comparison with using e-cigarettes alone.