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Evaluation of Comprehensive Hormonal and Growth Factor Biomarker Panel in Female Pattern Hair Loss

Aug 2026 · Acta Medica Iranica · 0 citations

TL;DR

FAI serves as a robust diagnostic marker, and the panel of TGF-β1, DHEA, SHBG, and E2 has potential diagnostic and prognostic value in clinical settings to guide personalized management.

Abstract

Female pattern hair loss (FPHL) is a common, multifactorial condition with a complex pathophysiology that remains not entirely understood. This study aimed to evaluate the diagnostic and prognostic values of several biomarkers (TGF-β1, DHEA, testosterone, SHBG, and the Free Androgen Index) in patients with FPHL. A case-control study was conducted in Iraq, involving 60 Iraqi women with FPHL and 60 healthy controls. Serum levels of the biomarkers were determined using ELISA. The Ludwig scale was employed to measure disease severity and its correlation with polycystic ovary syndrome (PCOS) or family history. Women diagnosed with FPHL exhibited significantly elevated levels of total testosterone, DHEA, TGF-β1, and FAI, alongside reduced SHBG and estradiol levels (P<0.0001 for all, except estradiol where P=0.0145). Following cross-validation and adjustment for multiple comparisons, FAI demonstrated excellent diagnostic accuracy (Adjusted AUC=0.96), while DHEA, total testosterone, and SHBG also displayed remarkable diagnostic efficacy (Adjusted AUCs> 0.90). TGF-β1, DHEA, total testosterone, and estradiol levels were positively correlated with disease severity. A significant correlation was observed between a positive family history and elevated Ludwig grades (P=0.0074). FPHL is associated with multiple hormonal imbalances that are not limited to increased androgen levels. FAI serves as a robust diagnostic marker, and the panel of TGF-β1, DHEA, SHBG, and E2 has potential diagnostic and prognostic value in clinical settings to guide personalized management. These findings support a multifactorial theory of FPHL and underline the importance of a comprehensive hormonal evaluation as part of the diagnostic algorithm for FPHL.

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