This cross-sectional study assessed hair cortisol concentration (HCC) as a marker of glucocorticoid replacement adequacy in 64 adults with adrenal insufficiency (AI) and 64 matched healthy controls. Participants received hydrocortisone treatment, and HCC was measured alongside clinical parameters including fatigue, pain, blood pressure, and anthropometric data.
HCC levels were markedly higher in AI patients (4.3 ng/g) compared to controls (1.75 ng/g; p < 0.01). Primary AI patients exhibited higher HCC (6.5 ng/g) than those with secondary AI (3.8 ng/g; p = 0.037). This difference remained significant even after excluding patients with congenital adrenal hyperplasia (13.8 vs. 3.8 ng/g; p < 0.01).
HCC demonstrated positive correlations with BMI, waist circumference, blood pressure, and hydrocortisone dose, while showing inverse correlations with fatigue, pain, and therapy duration (all p < 0.05). Multivariable analysis identified AI subtype as an independent predictor of HCC; excluding subtype, hydrocortisone dose emerged as the independent predictor. HCC showed excellent discrimination for severe fatigue (AUC 0.906) and pain (AUC 0.898), and good performance for systolic hypertension (AUC 0.837). Undertreated patients had significantly lower HCC (2.1 ng/g) than overtreated patients (14.1 ng/g; p < 0.001).
No safety data regarding adverse events or discontinuations were reported. The primary limitation is the cross-sectional design, which precludes causal inference. Prospective studies are required to determine the utility of HCC in optimizing glucocorticoid dosing. Consequently, HCC should be interpreted as a potential adjunctive tool rather than a standalone diagnostic metric for replacement adequacy.
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BackgroundAchieving physiologic glucocorticoid replacement in adrenal insufficiency (AI) remains challenging, as both under- and over-replacement contribute to morbidity. Hair cortisol concentration (HCC) reflects cumulative cortisol exposure and may provide clinically relevant information beyond single-time-point assessments.MethodsIn this cross-sectional study, 64 adults with hydrocortisone-treated AI and 64 matched healthy controls were evaluated. HCC was measured from the proximal 3-cm hair segment. Clinical, anthropometric, metabolic, and dosing parameters were analyzed. Patients were categorized as undertreated (VAS-fatigue or VAS-pain ≥7) or overtreated (hypertension, hyperglycemia, or ≥5% weight gain). Correlation, ROC, and multivariable regression analyses were performed.ResultsHCC was higher in AI patients than controls (4.3 vs. 1.75 ng/g, p < 0.01). In AI, HCC was higher in primary than in secondary disease (6.5 vs. 3.8 ng/g; p = 0.037); this difference remained significant after excluding patients with congenital adrenal hyperplasia (13.8 vs. 3.8 ng/g; p < 0.01). HCC was positively correlated with BMI, waist circumference, blood pressure, and hydrocortisone dose, and inversely correlated with fatigue, pain, and therapy duration (all p < 0.05). In multivariable analysis, AI subtype remained independently associated with HCC. When the AI subtype was excluded from the model, hydrocortisone dose emerged as an independent predictor. HCC demonstrated excellent discrimination for severe fatigue (AUC 0.906) and pain (AUC 0.898), and good performance for systolic hypertension (AUC 0.837). Undertreated patients had markedly lower HCC than overtreated patients (2.1 vs. 14.1 ng/g, p < 0.001).ConclusionsHCC reflects long-term glucocorticoid exposure in AI and differentiates patterns consistent with both underreplacement and overtreatment. These findings support HCC as a potential adjunctive tool for evaluating replacement adequacy. Prospective studies are needed to determine its role in dose optimization.