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Record W4391392140 · doi:10.1002/nau.25399

Safety and efficacy of an α<sub>1</sub>‐blocker plus mirabegron compared with an α<sub>1</sub>‐blocker plus antimuscarinic in men with lower urinary tract symptoms secondary to benign prostatic hyperplasia and overactive bladder: A systematic review and network meta‐analysis

2024· review· en· W4391392140 on OpenAlexaff
Sender Herschorn, Tufan Tarcan, Yuan‐Hong Jiang, Eric Chung, Farid Abdul Hadi, Achim Steup, Budiwan Sumarsono

Bibliographic record

VenueNeurourology and Urodynamics · 2024
Typereview
Languageen
FieldMedicine
TopicUrinary Bladder and Prostate Research
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
FundersAstellas Foundation for Research on Metabolic DisordersAstellas Pharma
KeywordsMedicineOveractive bladderMirabegronLower urinary tract symptomsInternational Prostate Symptom ScoreUrologyPlaceboBenign prostatic hyperplasia (BPH)Adverse effectUrinary retentionInternal medicineProstate

Abstract

fetched live from OpenAlex

Abstract Aim Antimuscarinics and the β3‐adrenoreceptor agonist, mirabegron, are commonly used for treating patients with overactive bladder (OAB) and α1‐adrenoreceptor antagonists (α1‐blockers) are the main pharmacological agents used for treating lower urinary tract symptoms (LUTS) secondary to benign prostatic hyperplasia (BPH). As these conditions commonly occur together, the aim of this systematic review was to identify publications that compared the use of an α1‐blocker plus mirabegron with an α1‐blocker plus antimuscarinic in men with LUTS secondary to BPH and OAB. A meta‐analysis was subsequently conducted to explore the safety and efficacy of these combinations. Methods Included records had to be from a parallel‐group, randomized clinical trial that was ≥8 weeks in duration. Participants were male with LUTS secondary to BPH and OAB. The indirect analyses that were identified compared an α1‐blocker plus OAB agent with an α1‐blocker plus placebo. The PubMed/Medical Literature Analysis and Retrieval System Online, the Excerpta Medica Database, the Cochrane Central Register of Controlled Trials, and the ClinicalTrials.gov registry were searched for relevant records up until March 5, 2020. Safety outcomes included incidences of overall treatment‐emergent adverse events (TEAEs) and urinary retention, postvoid residual volume, and maximum urinary flow (Qmax). Primary efficacy outcomes were micturitions/day, incontinence episodes/day, and urgency episodes/day, and secondary outcomes were Overactive Bladder Symptom Score and International Prostate Symptom Score. A Bayesian network meta‐analysis approach was used for the meta‐analysis. Results Out of a total of 1039 records identified, 24 were eligible for inclusion in the meta‐analysis. There were no statistically significant differences between the α1‐blocker plus mirabegron and α1‐blocker plus antimuscarinic groups in terms of the comparisons identified for all the safety and efficacy analyses conducted. Numerically superior results were frequently observed for the α1‐blocker plus mirabegron group compared with the α1‐blocker plus antimuscarinic group for the safety parameters, including TEAEs, urinary retention, and Qmax. For some of the efficacy parameters, most notably micturitions/day, numerically superior results were noted for the α1‐blocker plus antimuscarinic group. Inconsistency in reporting and study variability were noted in the included records, which hindered data interpretation. Conclusion This systematic review and meta‐analysis showed that an α1‐blocker plus mirabegron and an α1‐blocker plus antimuscarinic have similar safety and efficacy profiles in male patients with LUTS secondary to BPH and OAB. Patients may, therefore, benefit from the use of either combination within the clinical setting.

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)0.007
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.019
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0140.026
Bibliometrics0.0030.004
Science and technology studies0.0000.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.022
GPT teacher head0.308
Teacher spread0.287 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations8
Published2024
Admission routes1
Has abstractyes

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