Researchers say they have developed a new, internally validated tool to distinguish between a low- and high-pretest probability of Cushing syndrome (CS) in patients. Details on the proposed “Cushing score” were published in Frontiers in Endocrinology.

To develop the score, a team of investigators performed a retrospective, multicenter case-control study that included 150 people with confirmed CS and 300 patients in which hypercortisolism was excluded. Patients were enrolled from 5 endocrinology centers in Italy. All patients were evaluated for suspected hypercortisolism according to current guidelines.

The researchers collected baseline characteristics often associated with CS, including certain personal data as well as hypercortisolism-related clinical signs, symptoms, or comorbidities. These included skin changes (easy bruisability, facial plethora, hirsutism, purple striae, and/or seborrhea), muscle wasting (proximal muscle atrophy, proximal muscle weakness), atypical fat distribution (central adiposity, dorsocervical fat pad, facial fullness), cardiometabolic alterations (diabetes, dyslipidemia, hypertension, obesity), bone mineral loss (osteopenia or osteoporosis), and psychiatric symptoms.


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A multivariable logistic regression was used to build a clinical prediction model for CS. The model considered all primary features associated with a clinical suspicion of hypercortisolism as potential predictive variables.

Predictors obtained after stepwise backward selection included age (odds ratio [OR], 3.15, 95% CI, 1.34-7.42, P =.009 for age 40-59 years; OR, 7.35, 95% CI, 2.79-19.37, P <.001 for age < 40 years), facial fullness (OR, 2.13; 95% CI, 1.16-3.93; P=.015), facial plethora (OR, 1.98; 95% CI, 1.04-3.77; P =.038), proximal muscle atrophy (OR, 2.46; 95% CI, 1.24-4.88; P =.010), hirsutism and/or seborrhea (OR, 1.91; 95% CI, 1.06-3.41; P =.030), absence of obesity (OR, 5.93; 95% CI, 3.27-10.73; P<.001), hypertension (OR, 3.36; 95% CI, 1.81-6.21; P <.001), diabetes (OR, 1.87; 95% CI, 0.98-3.57; P =.059), and bone mineral density (OR, 2.35, 95% CI, 1.14-4.86, P =.021 for osteopenia; OR, 5.13, 95% CI, 2.39-11.02, P <.001 for osteoporosis).

Predictive performance of the model, assessed by the area under the curve (AUC), was 0.873, which researchers said did not affect the predictive power of the model. Additionally, an internal validation was conducted through 10-fold cross-validation. According to the researchers, the final estimation of the model performance over 10 iterations showed an average AUC of 0.841, “thus reassuring about a small overfitting effect.”

Retrieved ‘Cushing score’ for the prediction model was structured on a 17.5-point scale. Scores classified patients in a low-risk class (score value, ≤5.5; probability of disease, 0.8%), an intermediate-low-risk class (score value, 6-8.5; probability of disease, 2.7%), an intermediate-high-risk class (score value, 9-11.5; probability of disease, 18.5%), and a high-risk class (score value, 12.0-17.5; probability of disease, 72.5%).

Limitations of the study, according to the researchers, included its retrospective design as well as the potential selection bias due to the tertiary nature of the endocrinology referral centers.

“The derived Cushing score is a simple tool that could be extensively adopted in clinical practice and might be of significant help in reducing the length and the potential pitfalls in CS diagnostic work-up, with reflections in the improvement of patient health and in the reduction of health care costs, particularly during the COVID-19 pandemic”, the researchers concluded.

Disclosure: At least one author declared affiliations with a pharmaceutical company. Please see the original reference for a full list of authors’ disclosures.

Reference

Parasiliti-Caprino M, Bioletto F, Frigerio T, et al. A new clinical model to estimate the pre-test probability of Cushing’s syndrome: The Cushing score. Front Endocrinol (Lausanne) Published Online October 5, 2021. doi:10.3389/fendo.2021.747549

This article originally appeared on Endocrinology Advisor