Exploring the Association Between Low Serum Vitamin D Levels and Benign Prostatic Hyperplasia: A Systematic Review
Bibliographic record
Abstract
Introduction: Benign prostatic hyperplasia (BPH) is a prevalent urologic concern that affects aging men. In addition to hormonal influences, inflammation serves as one of the common pathways for the proliferative growth of BPH. The objective of this article is to bridge the knowledge gap on the association between Vitamin D, renowned for its anti-inflammatory effect, and BPH. Materials and methods: A systematic search was conducted using PubMed and Cochrane library databases, covering the period from 2013 to 2024, following PRISMA 2020 guidelines. Keyword combinations of "Vitamin D" and "BPH" were used. Articles were filtered using inclusion and exclusion criteria and underwent bias assessment using the Newcastle-Ottawa Quality Assessment Scale (NOS). Results: This systematic review consists of 6 observational studies, involving more than 1500 male patients with and without BPH across six countries. All 6 studies suggest Lower serum vitamin D consistently correlates with larger prostate volumes. Vitamin D deficiency is linked to reduced urinary flow, with higher International Prostate Symptom Score (IPSS) but varying results regarding relationships Prostate-Specific Antigen (PSA). These findings suggest vitamin D has potential for BPH management, but larger and more standardized studies are needed. Conclusion: This review indicates a significant association between low serum vitamin D and larger prostate volumes in BPH. While findings for other BPH parameters vary, the potential role of vitamin D in modulating prostate size is evident.
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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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".