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Record W4412732739 · doi:10.3389/fphar.2025.1630843

Recombinant human growth hormone and brain neoplasm association: a pharmacovigilance and Mendelian randomization analysis based on US FAERS, Japanese JADER, and Canadian CVARD

2025· article· en· W4412732739 on OpenAlexaboutno aff
Li Huang, Mei Zhang, Fang Li, Yinpeng Xu

Bibliographic record

VenueFrontiers in Pharmacology · 2025
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacovigilance and Adverse Drug Reactions
Canadian institutionsnot available
Fundersnot available
KeywordsPharmacovigilanceMendelian randomizationMedicinePharmacologyOncologyInternal medicineAdverse effectBiologyGeneGeneticsGenotype

Abstract

fetched live from OpenAlex

Objective This study aimed to analyze the statistical association between recombinant human growth hormone (rhGH) and brain neoplasm adverse events (AEs) by mining data from the US Food and Drug Administration Adverse Event Reporting System (FAERS) database, the Japanese Adverse Drug Event Report (JADER) database, and the Canada Vigilance Adverse Reaction Online Database (CVARD). Furthermore, Mendelian randomization (MR) was utilized to evaluate the potential causal link between rhGH and brain neoplasm, thereby providing a reference for safe clinical medication use. Methods Reports of brain neoplasm associated with rhGH originated from the FAERS database (Q1 2004 - Q4 2024), the JADER database (April 2004 - December 2024), and the CVARD database (January 1991 - December 2024). Disproportionality analysis methods, including the Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), and Information Component (IC), were used to detect pharmacovigilance signals. Subsequently, a two-sample Mendelian randomization analysis was conducted, treating rhGH as the exposure and brain neoplasm as the outcome, to evaluate the causal relationship. Results A total of 323 reports of rhGH-associated brain neoplasms AEs were identified (FAERS: n = 282; JADER: n = 14; CVARD: n = 27). Brain neoplasm was detected as a positive signal in all three databases by all three signal detection methods, consistently classified as medium clinical priority. Multivariable logistic regression analysis demonstrated an independent association between age and the increased risk of rhGH-induced brain tumors. Specifically, age groups 18–45 years and 46–65 years showed significantly elevated risks [OR (95% CI): 3.71 (1.09–13.34), P = 0.048; and 3.78 (1.02–14.62), P = 0.049, respectively]. The two-sample MR analysis, using the Inverse Variance Weighted (IVW) method, yielded an OR of 1.415 (95% CI: 1.005, 1.991, P = 0.046), suggestive of causal relationship between rhGH and brain neoplasms. Conclusion Pharmacovigilance analysis revealed a significant statistical association between rhGH and brain neoplasms. Mendelian randomization analysis further suggested a causal relationship between them. These findings highlight the need to consider the potential risk of brain neoplasm adverse events during treatment with rhGH.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.022
metaresearch head score (Gemma)0.050
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.901
Threshold uncertainty score0.197

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.050
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.005
Bibliometrics0.0050.004
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.356
Teacher spread0.337 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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