ArticleCureus2024
Social Interest Data as a Proxy for Off-Label Performance-Enhancing Drug Use: Implications and Clinical Considerations.
Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Rising Public Interest in Weight Loss Medications and Growing Awareness of Their Aesthetic Sequelae: An Infodemiologic Google Trends Analysis and Clinical Diagnostic Patterning.Journal of cosmetic dermatology · 2026Article
- Leader-Inspired Nutrition: Promoting Safe Dietary Supplement Use for Service Members.Nutrients · 2025Article
- Illegal and falsified medicines self-administrated in not approved post-cycle therapy after the cessation of anabolic-androgenic steroids - qualitative analysis.Frontiers in chemistry · 2025Article
- Safety Implications of Off-Label Medication Use in Athletes: A Narrative Review.Medicines (Basel, Switzerland) · 2024Review
- Illegal products containing selective androgen receptor modulators purchased online from Italy: health risks for consumers.Sexual medicine · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Performance-enhancing drugs (PEDs) can be categorized into various classes based on the physiological mechanism of the compound, with the most popular being anabolic steroids, selective androgen receptor modulators, and growth hormones. Ancillary compounds, such as selective estrogen receptor modulators (SERMs) and selective estrogen receptor degraders, are commonly utilized alongside a PED to counterbalance any potential undesired side effects. With little clinically relevant data to support the use of these ancillary compounds, medical education and evidence-based approaches aimed at monitoring the potential adverse effects of PED use are sparse.This study aims to identify emerging trends in the interest of PEDs and related ancillary compounds, hypothesize the physiological effects of the continued respective behavior, and propose a proxy for use by clinicians to approximate off-label drug use and subsequently modify their practices accordingly. Several significant trends were identified for non-FDA-regulated compounds (i.e., selective androgen receptor modulators such as RAD-140) and off-label indications for FDA-regulated drugs (i.e., SERMs such as tamoxifen). A significant increase in interest regarding selective androgen receptor modulators, mirrored by anecdotal reports in clinical settings and online forums, is coupled with stagnant or decreasing interest in both post-cycle therapies and anabolic steroids. Ultimately, we propose a call to action for utilizing social data and/or prescription data as a proxy for clinicians to better understand trends in these compounds and thus refine their treatment protocols in a concordant manner.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.