Comparison of the efficacy of febuxostat vs. benzbromarone in the treatment of gout: a meta-analysis in Chinese gout patients.
Bibliographic record
Abstract
OBJECTIVE: Febuxostat and benzbromarone are two common drugs for the treatment of gout, but the clinical efficacy of these two drugs is controversial. This meta-analysis aimed to compare the efficacy of febuxostat and benzbromarone in the treatment of gout. MATERIALS AND METHODS: PubMed, Embase, and the Cochrane Library were searched for articles related to febuxostat and benzbromarone in the treatment of gout from inception to January 7, 2023. Titles and abstracts were reviewed in accordance with predesigned inclusion and exclusion criteria, and data were extracted independently. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the studies, and the continuous variables were expressed as the standard mean square error (SMD) by STATA 16 (Stata Corp., College Station, TX, USA). The sensitivity analysis was conducted by randomly removing a study, and the heterogeneity was analyzed by funnel plots and Egger's test. RESULTS: According to the search strategy, a total of 1,043 publications were retrieved from the three aforementioned databases, of which 45 publications were excluded due to duplication. Fourteen studies remained after screening titles and abstracts, and a total of 7 studies met the inclusion criteria after a comprehensive evaluation of the 14 studies. Meta-analysis showed that the uric acid (UA)-reducing effect of febuxostat is better than that of benzbromarone, while febuxostat showed a better ability to improve the estimated glomerular filtration rate (eGFR) and reduce Cr and blood urea nitrogen (BUN). In terms of hepatotoxicity, benzbromarone was not as potent as febuxostat in increasing alanine transaminase (ALT) and aspartate transaminase (AST), suggesting that benzbromarone has less hepatotoxicity. Moreover, there was no significant difference in the effect on blood lipid levels between the two drugs. CONCLUSIONS: The beneficial effect of febuxostat on renal function-related indexes such as the eGFR, Cr and BUN is significant, while benzbromarone is more effective in reducing UA and has relatively less hepatotoxicity. The specific efficacy of the two drugs needs to be confirmed by further research.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.017 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.058 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".