A Systematic Review of Inflammatory Markers in Polycystic Ovary Syndrome (PCOS) and Meta-Analysis of Interleukin-6 (IL-6) in Case-Control Studies
Bibliographic record
Abstract
Chronic low-grade inflammation plays a crucial role in the pathophysiology of polycystic ovary syndrome (PCOS). This systematic review aims to synthesize the recent evidence on key inflammatory markers in PCOS and the role of IL-6. A comprehensive literature search was conducted using the PubMed, Web of Science, Cochrane Library, and Google Scholar databases. Studies published between 2014 and 2024 were screened based on predefined eligibility criteria. Both observational and interventional studies that reported levels of inflammatory markers in patients with polycystic ovary syndrome (PCOS) were included. Data were systematically extracted, and the quality of the studies was assessed using the Newcastle-Ottawa Scale (NOS) for observational studies, the Cochrane Risk of Bias tool for randomized controlled trials (RCTs), and the ROBINS-1 tool for non-randomized controlled trials. A statistical synthesis of IL-6 levels was performed for the meta-analysis using a random-effects model in R. A total of 44 studies met the inclusion criteria for qualitative analysis and identified 94 biomarkers. The most commonly used biomarkers across the majority of studies, listed in descending order, are as follows: high-sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), CRP, adiponectin, IL-18, vascular endothelial growth factor (VEGF), IL-8, IL-1β, sex hormone binding globulin (SHBG), leptin, and vascular cell adhesion protein 1 (VCAM-1). Additionally, four case-control studies conducted in four countries (Taiwan, Russia, Spain, and Turkey) were included in the quantitative analysis, which involved 689 participants (PCOS group: n = 365; Control group: n = 324). The pooled mean difference (MD), calculated using the random-effects model, was 0.72 (0.47; 0.98) (p < 0.0001), indicating a significant increase in IL-6 levels among PCOS patients compared to the control group. The funnel plot exhibited slight asymmetry, suggesting publication bias, where smaller studies with negative or neutral results may be absent. The adjusted effect size after trim and fill analysis remained significant, indicating that publication bias is unlikely to affect the conclusions substantially. Chronic low-grade inflammation plays a crucial role in PCOS, and IL-6 levels in women with PCOS were elevated. Potential markers that can be investigated to assess inflammatory status in PCOS include hs-CRP, TNFα, CRP, adiponectin, IL-18, VEGF, IL-8, iIL-1β, SHBG, leptin, and VCAM-1.
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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 | 0.017 | 0.058 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.023 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".