RT Journal Article
T1 A Probabilistic Model for Cushing’s Syndrome Screening in At-Risk Populations: A Prospective Multicenter Study
A1 Leon-Justel, Antonio
A1 Madrazo-Atutxa, Ainara
A1 Alvarez-Rios, Ana I.
A1 Infantes-Fontan, Rocio
A1 Garcia-Arnes, Juan A.
A1 Lillo-Muñoz, Juan A.
A1 Aulinas, Anna
A1 Urgell-Rull, Eulalia
A1 Boronat, Mauro
A1 Sanchez-de-Abajo, Ana
A1 Fajardo-Montañana, Carmen
A1 Ortuño-Alonso, Mario
A1 Salinas-Vert, Isabel
A1 Granada, Maria L.
A1 Cano, David A.
A1 Leal-Cerro, Alfonso
A1 Mena-Vázquez, Natalia
K1 Cushing's syndrome
K1 ROC curve
K1 Muscular atrophy
K1 Atrofia muscular
K1 Curva ROC
AB Context: Cushing’s syndrome (CS) is challenging to diagnose. Increased prevalence of CS in specific patient populations has been reported, but routine screening for CS remains questionable. To decrease the diagnostic delay and improve disease outcomes, simple new screening methods for CS in at-risk populations are needed.Objective: To develop and validate a simple scoring system to predict CS based on clinical signs and an easy-to-use biochemical test.Design: Observational, prospective, multicenter.Setting: Referral hospital.Patients: A cohort of 353 patients attending endocrinology units for outpatient visits.Interventions: All patients were evaluated with late-night salivary cortisol (LNSC) and a low-dose dexamethasone suppression test for CS.Main Outcome Measures: Diagnosis or exclusion of CS.Results: Twenty-six cases of CS were diagnosed in the cohort. A risk scoring system was developed by logistic regression analysis, and cutoff values were derived from a receiver operating characteristic curve. This risk score included clinical signs and symptoms (muscular atrophy, osteoporosis, and dorsocervical fat pad) and LNSC levels. The estimated area under the receiver operating characteristic curve was 0.93, with a sensitivity of 96.2% and specificity of 82.9%.Conclusions: We developed a risk score to predict CS in an at-risk population. This score may help to identify at-risk patients in non-endocrinological settings such as primary care, but external validation is warranted.
PB Oxford University Press
SN 0021-972X
YR 2016
FD 2016-08-14
LK https://hdl.handle.net/10668/23222
UL https://hdl.handle.net/10668/23222
LA en
NO Leon-Justel A, Madrazo-Atutxa A, Alvarez-Rios AI, Infantes-Fontan R, Garcia-Arnes JA, Lillo-Muñoz JA, et al. A Probabilistic Model for Cushing's Syndrome Screening in At-Risk Populations: A Prospective Multicenter Study. J Clin Endocrinol Metab. 2016 Oct;101(10):3747-3754
DS RISalud
RD Apr 19, 2025