Triptorelin therapy for lower urinary tract symptoms (LUTS) in prostate cancer patients: A systematic meta‐analysis
Bibliographic record
Abstract
Objective: This systematic meta-analysis aimed to assess the effectiveness of triptorelin therapy in reducing lower urinary tract symptoms (LUTS) in men with prostate cancer (PCa). Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. PubMed, Web of Science and EMBASE databases were searched for studies conducted between 2013 and 2023. Eligible studies included PCa patients undergoing androgen deprivation therapy (ADT) with triptorelin, with reported baseline and follow-up International Prostate Symptom Scores (IPSS) and quality of life (QoL) data. The Newcastle-Ottawa Scale (NOS) was used to assess the risk of bias, and a random-effects model was applied for the meta-analysis. Results: A total of 29 articles were identified, and three studies met the inclusion criteria. Triptorelin therapy showed a clinically significant reduction in IPSS over 48 weeks in PCa patients with moderate to severe LUTS. The meta-analysis revealed a pooled effect size of 1.05 (95% CI: 0.65; 1.45), indicating a statistically significant improvement in LUTS. QoL also improved in patients receiving triptorelin therapy, although heterogeneity among the studies and a moderate to high risk of bias were noted. Conclusion: Triptorelin therapy demonstrated a positive impact on LUTS in PCa patients. The meta-analysis showed significant reductions in IPSS scores and improved QoL after 48 weeks of triptorelin treatment. However, the results should be interpreted cautiously due to study heterogeneity and potential biases. Further well-designed studies are needed to confirm these findings and determine the optimal use of triptorelin for managing LUTS in men with PCa. Implications for Practice: Triptorelin therapy may offer an effective treatment option for men with PCa experiencing moderate to severe LUTS. Its positive impact on QoL can lead to improved patient well-being and treatment adherence. Clinicians should consider triptorelin as a potential treatment choice, especially in patients who may be reluctant to undergo surgical interventions for their LUTS. However, careful patient selection and close monitoring are essential due to the observed study heterogeneity and risk of bias. Future research should focus on evaluating triptorelin's cost-effectiveness and comparing its efficacy with other LH-RH agonists in managing LUTS in PCa patients.Video Abstract: URL (Reviewers/Editors to select from) Link 1: https://brighton.cloud.panopto.eu/Panopto/Pages/Viewer.aspx?id=071419c8-1ad5-4502-a222-b04300c2ca5e Link 2: https://brighton.cloud.panopto.eu/Panopto/Pages/Viewer.aspx?id=b6305a8a-b977-4fcd-a69e-b04300bed728.
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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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.055 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| 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".