CC BY 4.0 · Journal of Health and Allied Sciences NU 2023; 13(03): 380-388
DOI: 10.1055/s-0042-1757445
Original Article

Free-androgen Index in Women with Polycystic Ovarian Syndrome: A Meta-Analysis

Prakash Patil
1   Central Research Laboratory, KS Hegde Medical Academy, Nitte (Deemed to be University), Mangaluru, Karnataka, India
Neevan D'Souza
2   Center for Bioinformatics and Biostatistics, Nitte (Deemed to be University), Mangaluru, Karnataka, India
Sudeep D. Ghate
2   Center for Bioinformatics and Biostatistics, Nitte (Deemed to be University), Mangaluru, Karnataka, India
3   Department of Endocrinology, Justice KS Hegde Charitable Hospital, K S Hegde Medical Academy, Nitte (Deemed to be University), Mangaluru, Karnataka, India
Harish B. Girijashankar
4   Department of Anesthesiology, Justice KS Hegde Charitable Hospital, K S Hegde Medical Academy, Nitte (Deemed to be University), Mangaluru, Karnataka, India
› Author Affiliations
Funding None.


Objectives Hyperandrogenism, a key feature of polycystic ovarian syndrome (PCOS), is caused by excess androgen secretion, most commonly of ovarian origin. Although the serum total testosterone (TT) levels have long been used as a traditional measure of hyperandrogenemia in women with PCOS, it is associated with many fallacies due to the fact that a component of TT is linked to sex hormone-binding globulin (SHBG). Recent research has discovered that measuring free testosterone levels and computing the free androgen index (FAI), which is a ratio of TT and SHBG, are better predictors of androgen excess in PCOS. The aim of this meta-analysis is to determine the association of FAI in diagnosing hyperandrogenism and its ability to discriminate PCOS from controls.

Materials and Methods The publicly available databases PubMed, Scopus and Web of Science were searched using MeSH terms, ‘Polycystic Ovarian Syndrome’ OR ‘PCOS’ OR ‘PCOD’ AND ‘Testosterone’ AND ‘Sex Hormone Binding Globulin’ OR ‘SHBG’ to collect the full-text articles for the retrieval of related data of case–control and cross-sectional studies. The studies quality was assessed using the Newcastle–Ottawa scale, and a sub-group analysis and publication bias between the studies was evaluated by funnel plot.

Statistical Analysis The R program (v4.0.3) and R packages ‘metafor’ and ‘dmetar’ were used for statistical analyses of quantitative data and the plots were generated using ‘ggplot2’ package through a comparison of pooled SMD by Egger's linear regression and Beggs-Mazumdar tests.

Results Twenty-four studies involving 7,847 participants including 3,290 controls and 4,557 PCOS were included in the meta-analysis. The pooled data analysis of the included studies showed that the PCOS women had higher FAI than controls, with SMD of 1.56 (95%CI 1.08–2.04; p < 0.01). The publication bias was tested using a funnel plot and Egger's regression asymmetry test, which revealed no risk of publishing bias (p = 0.1727). Additionally, the sub-group meta-analysis of geographic region revealed that FAI levels were more significant in PCOS subjects of Asia and Europe, compared with the American region.

Conclusion Overall, this meta-analysis indicates that FAI could be a reliable marker to differentiate PCOS patients from controls in Asian and European ethnicities.

Supplementary Material

Publication History

Article published online:
18 November 2022

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