Researchers have developed a new method to assess specific populations for Cushing's syndrome, based on results from a multicenter study.

The prospective cohort study evaluated at-risk patients for Cushing's syndrome to create a novel type of scoring system in order to better predict the development of disease, stated lead author Antonio León-Justel, PhD, of the Seville Institute of Biomedicine in Spain, and colleagues.

Cushing's syndrome is identified by an excess of cortisol and/or glucocorticoids in the blood, which can result in myriad negative health outcomes, including an increased risk of death and morbidity, according to the study in The Journal of Clinical Endocrinology & Metabolism.

Because Cushing's syndrome (CS) is complex and difficult to diagnose, there is a necessity for new methods to assess at-risk populations in order to mitigate the rising prevalence of the disorder, the authors noted.

"The diagnosis of CS might pose a considerable challenge even for experienced endocrinologists since there are no pathognomonic symptoms or signs of CS and most of the symptoms and signs of CS are common in the general population including obesity, hypertension, bone loss, and diabetes," the senior author, Alfonso Leal Cerro, MD, told MedPage Today via email. "Routine screening for CS remains impractical due to the estimated low prevalence of the disease. However this prevalence might be higher in at-risk populations."



The authors screened a total of 353 at-risk patients from 13 different hospitals across Spain between January 2012 and July 2013 to measure cortisol variability from saliva samples.

At-risk populations, which the authors note have a higher prevalence of Cushing's syndrome, included individuals with type 2 diabetes, hypertension, and osteoporosis.

The patients screened in the study were each identified as having at least two of the risk factors for Cushing's syndrome: high blood pressure (defined as taking two or more drugs and having a systolic blood pressure over 140 mmHg and/or a diastolic blood pressure over 90 mmHg), obesity (body mass index >30), uncontrolled diabetes (HbA1c>7.0%), osteoporosis (T-score ≥ -2.5 SD), and virilization syndrome (hirsutism) with menstrual disorders.

The researchers used clinical and biochemical methods of assessment. Clinical methods included inspection of physical characteristics, such as muscle atrophy, purple striae, and/or facial plethora. Biochemical methods included collecting saliva and blood samples from participants to test cortisol levels using a chemiluminescence method. Each individual was identified as either negative for hypercortisolism (late-night salivary cortisol [LNSC] ≤ 7.5 nmol/L and dexamethasone suppression test [DST] ≤ 50 nmol/L) or positive for hypercortisolism (LNSC > 7.5 nmol/L and DST > 50 nmol/L).

Univariate testing indicated the following significant characteristics to be positively correlated with the development of Cushing's syndrome:
Muscular atrophy (15.2, CI 95% 4.48-51.25);
Osteoporosis (4.60, 1.66-12.75); and
Dorsocervical fat pad (3.32, 1.48-7.5).

Roberto Salvatori, MD, professor and medical director of the Johns Hopkins Pituitary Center, who was not involved with the study, commented to MedPage Today in an email: "Any endocrinologist would proceed with careful Cushing biochemical evaluation in the presence of the clinical features (muscular atrophy, osteoporosis, and dorsocervical fat pad) that are well known to be associated with hypercortisolism. Of notice, the odds ratio is further increased by an abnormal late-night salivary cortisol, which is already a screening test for hypercortisolism."

The researchers used their results to develop an equation to determine the level of risk a patient has for developing Cushing's syndrome, taking into account factors for osteoporosis, dorsocervical fat pads, muscular atrophy, and LNSC levels.

Although the study was able to develop a comprehensive risk model for the syndrome, when tested against the prevalence for Cushing's syndrome in the subject group, the equation generated a total of 56 false-positive and 25 true-positive results. Overall, the researchers wrote, 83% of patients were accurately classified as belonging to the at-risk population when using the equation.

Because the newly developed equation for identifying at-risk individuals involved factors that are relatively easy to test for, the authors noted that clinical application is broad and cost-effective in a primary care setting.

"We would like to test the scoring system in different clinical settings such as primary care or hypertension clinics," Leal Cerro said. "Primary care would be a particularly interesting setting since it might significantly decrease the time to diagnosis, something critical to avoid an excessive exposure to glucocorticoid excess and consequent deleterious effects."

Salvatori said that while the study was a good start at shedding light on some of the unknowns about Cushing's syndrome, more research is required. "The real question in my mind is when does a non-endocrinologist need to suspect Cushing in a general medicine, orthopedic, or other clinic? When the internal medicine residents ask me about guidelines for 'who to screen for hypercortisolism in my clinic,' I am unable to provide an evidence-based answer."