What is it about?
Polycystic Ovary Syndrome (PCOS) is a complex endocrine and metabolic disorder affecting women of reproductive age and is characterized by hormonal imbalance, insulin resistance and chronic low-grade inflammation. Recent evidence highlights the clinical utility of integrating hematological, inflammatory and hormonal biomarkers for early diagnosis, risk stratification and management of PCOS. Hematological indices derived from complete blood count (CBC), such as neutrophilto- lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and red cell distribution width (RDW), have emerged as costeffective indicators of subclinical inflammation and oxidative stress. Inflammatory markers, particularly C-reactive protein (CRP) and high-sensitivity CRP (hs-CRP), reflect systemic inflammation closely associated with insulin resistance and metabolic dysfunction. Hormonal biomarkers, including anti-Müllerian hormone (AMH), luteinizing hormone (LH), follicle-stimulating hormone (FSH), and insulin, remain central to PCOS diagnosis and phenotyping. This review synthesizes literature published between 2020 and 2025 to evaluate the integrative role of these biomarkers in understanding PCOS pathophysiology and improving diagnostic and therapeutic approaches.
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Why is it important?
Polycystic Ovary Syndrome (PCOS) is a complex endocrine and metabolic disorder affecting women of reproductive age and is characterized by hormonal imbalance, insulin resistance and chronic low-grade inflammation. Recent evidence highlights the clinical utility of integrating hematological, inflammatory and hormonal biomarkers for early diagnosis, risk stratification and management of PCOS. Hematological indices derived from complete blood count (CBC), such as neutrophilto- lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and red cell distribution width (RDW), have emerged as costeffective indicators of subclinical inflammation and oxidative stress. Inflammatory markers, particularly C-reactive protein (CRP) and high-sensitivity CRP (hs-CRP), reflect systemic inflammation closely associated with insulin resistance and metabolic dysfunction. Hormonal biomarkers, including anti-Müllerian hormone (AMH), luteinizing hormone (LH), follicle-stimulating hormone (FSH), and insulin, remain central to PCOS diagnosis and phenotyping. This review synthesizes literature published between 2020 and 2025 to evaluate the integrative role of these biomarkers in understanding PCOS pathophysiology and improving diagnostic and therapeutic approaches.
Perspectives
Polycystic Ovary Syndrome (PCOS) is a complex endocrine and metabolic disorder affecting women of reproductive age and is characterized by hormonal imbalance, insulin resistance and chronic low-grade inflammation. Recent evidence highlights the clinical utility of integrating hematological, inflammatory and hormonal biomarkers for early diagnosis, risk stratification and management of PCOS. Hematological indices derived from complete blood count (CBC), such as neutrophilto- lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and red cell distribution width (RDW), have emerged as costeffective indicators of subclinical inflammation and oxidative stress. Inflammatory markers, particularly C-reactive protein (CRP) and high-sensitivity CRP (hs-CRP), reflect systemic inflammation closely associated with insulin resistance and metabolic dysfunction. Hormonal biomarkers, including anti-Müllerian hormone (AMH), luteinizing hormone (LH), follicle-stimulating hormone (FSH), and insulin, remain central to PCOS diagnosis and phenotyping. This review synthesizes literature published between 2020 and 2025 to evaluate the integrative role of these biomarkers in understanding PCOS pathophysiology and improving diagnostic and therapeutic approaches.
Dr Ajit Pal Singh
Sharda University
Read the Original
This page is a summary of: Integrated assessment of haematological, inflammatory and hormonal biomarkers in women with Polycystic Ovary Syndrome aged 15–40 years, Biochemical and Cellular Archives, March 2026, Research Floor,
DOI: 10.51470/bca.2026.26.1.951.
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