Assessing C reactive protein/albumin ratio as a new biomarker for polycystic ovary syndrome: a case-control study of women from Bahraini medical clinics

评估 C 反应蛋白/白蛋白比率作为多囊卵巢综合征的新生物标志物:针对巴林医疗诊所女性的病例对照研究

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作者:Shirin Kalyan, Azita Goshtesabi, Sameh Sarray, Angela Joannou, Wassim Y Almawi

Conclusion

CRP/albumin ratio, a marker for inflammation related to metabolic dysfunction, was found to have a stronger association with PCOS than either androgen excess or insulin resistance. Inflammation is known to be influenced by adiposity, but relative to controls, women with PCOS have higher levels of CRP/albumin irrespective of BMI. These findings support the view that inflammation plays a central role in the pathophysiology of PCOS.

Objective

Polycystic ovary syndrome (PCOS) is an endocrine disorder affecting approximately one in seven women who experience androgen excess, menstrual cycle irregularities, frequent anovulation and a tendency for central obesity and insulin resistance. Chronic subclinical inflammation is now recognised as being common in the context of PCOS, which led to the postulation that PCOS may fundamentally be an inflammatory process. This study aimed to: (1) evaluate serum C reactive protein (CRP)/albumin ratio as a potential predictive biomarker for PCOS; (2) compare the relationship between CRP/albumin and PCOS to variables classically associated with the syndrome. Design: Case-control study. Setting: Adult obstetrics/gynaecology, endocrinology and outpatient clinics; university hospital in Bahrain. Participants: 200 premenopausal women with a diagnosis of PCOS, and 119 ethnically matched eumenorrheic premenopausal women. Main outcome measures: CRP/albumin ratio, anthropometric measures, insulin resistance, androgen excess.

Results

Independent of body mass index (BMI), receiver operating characteristic curve for CRP/albumin ratio as a selective biomarker for PCOS was 0.865 (95% CI 0.824 to 0.905), which was more sensitive than CRP alone. Binary regression analysis showed that CRP/albumin ratio outperformed classical correlates, Free Androgen Index and insulin resistance, in predicting PCOS for every BMI category.

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