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Modelling of oscillatory cortisol response in horses using a Bayesian population approach for evaluation of dexamethasone suppression test protocols

Artikel i vetenskaplig tidskrift
Författare Felix Held
C. Ekstrand
Marija Cvijovic
J. Gabrielsson
M. Jirstrand
Publicerad i Journal of Pharmacokinetics and Pharmacodynamics
Volym 46
Nummer/häfte 1
Sidor 75-87
ISSN 1567-567X
Publiceringsår 2019
Publicerad vid Institutionen för matematiska vetenskaper
Sidor 75-87
Språk en
Länkar dx.doi.org/10.1007/s10928-018-09617...
Ämnesord Cortisol, Dexamethasone suppression test, Bayesian inference, Oscillating baseline, Turnover model, Inter-individual variability, NLME, pars-intermedia dysfunction, endogenous hydrocortisone, risk-factors, pharmacokinetics, disease, prednisolone, sensitivity, prevalence, secretion, Pharmacology & Pharmacy, th dn, 1982, endocrinology, v110, p1430
Ämneskategorier Farmakologi och toxikologi

Sammanfattning

Cortisol is a steroid hormone relevant to immune function in horses and other species and shows a circadian rhythm. The glucocorticoid dexamethasone suppresses cortisol in horses. Pituitary pars intermedia dysfunction (PPID) is a disease in which the cortisol suppression mechanism through dexamethasone is challenged. Overnight dexamethasone suppression test (DST) protocols are used to test the functioning of this mechanism and to establish a diagnosis for PPID. However, existing DST protocols have been recognized to perform poorly in previous experimental studies, often indicating presence of PPID in healthy horses. This study uses a pharmacokinetic/pharmacodynamic (PK/PD) modelling approach to analyse the oscillatory cortisol response and its interaction with dexamethasone. Two existing DST protocols were then scrutinized using model simulations with particular focus on their ability to avoid false positive outcomes. Using a Bayesian population approach allowed for quantification of uncertainty and enabled predictions for a broader population of horses than the underlying sample. Dose selection and sampling time point were both determined to have large influence on the number of false positives. Advice on pitfalls in test protocols and directions for possible improvement of DST protocols were given. The presented methodology is also easily extended to other clinical test protocols.

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