Abstract

Abstract Background Salivary cortisol is considered a reliable alternative to serum-free cortisol for evaluating hypothalamic-pituitary-adrenal axis rhythmicity. Its advantages include free hormone measurement, non-invasiveness, precision, and cost-effectiveness. Several cortisol indicators in serially collected saliva have been used in research studies to evaluate the circadian rhythm. We aimed to find if the distribution of those indicators is affected by the specific assay platform used. Methods Four-time points of saliva specimens were obtained immediately after awakening, 30 min and 60 min post-awakening, and in the nighttime from 49 subjects (aged between 19 and 25, mean ± SD: 28.9 ± 8.4 years). Salivary cortisol was analyzed by ELISA method using the Cortisol Saliva ELISA kit (IBL, Hamburg, Germany). Liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay was performed on the API 4000 triple quadrupole mass spectrometer coupled with an Agilent 1200 liquid chromatography system. Four cortisol indicators (DCS (diurnal cortisol slope), CARi (cortisol awakening response by an absolute increase within 30 min of awakening), AUCg (area under the curve with respect to ground), and AUCi (AUC with respect to increasing)) were calculated from each patient by the method. Correlation between the two methods was evaluated for overall cortisol concentrations, DCS, CARi, AUCg, and AUCi. Results The cortisol concentrations between the two methods strongly correlated (r = 0.973) but with a mean bias of 3.4 nmol/L (95% CI −3.8 to −2.9). Four cortisol indicators strongly correlated between the two methods, but showed significant differences. DCS data generated from LC-MS/MS measurement was more broadly distributed than those from ELISA. On the contrary, CARi data generated from ELISA measurement dispersed more than those from LC-MS/MS. Conclusion The concentrations of salivary cortisol strongly correlated between ELISA and LC-MS/MS, though considerable proportional bias between the two methods. The cortisol indicators generated from different methods can affect its distribution, therefore possibly affecting its discrimination power.

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