Who’s at Risk for Cushing’s?

by Kristen Monaco
Contributing Writer, MedPage Today

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, toldMedPage 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).

A logistic regression analysis of LNSC values also showed significant correlation between Cushing’s syndrome and the following top three characteristics:

  • Muscular atrophy (9.04, CI 95% 2.36-34.65);
  • Osteoporosis (3.62, CI 95% 1.16-11.35); and
  • Dorsocervical fat pad (3.3, CI 95% 1.52-7.17).

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.”

The study was funded by a grant from Novartis Oncology, Spain.

León-Justel and Leal Cerro disclosed financial relationships with Novartis Oncology, Spain.

  • Reviewed by F. Perry Wilson, MD, MSCEAssistant Professor, Section of Nephrology, Yale School of Medicine and Dorothy Caputo, MA, BSN, RN, Nurse Planner

LAST UPDATED 08.15.2016

Screening tool accurately predicts Cushing’s syndrome in most at-risk patients

León-Justel A, et al. J Clin Endocrinol Metab. 2016;doi:10.1210/jc.2016-1673.

A scoring system based on clinical signs and a late-night salivary cortisol test accurately predicted Cushing’s syndrome in at-risk patients, with only one missed case, according to recent findings.

In a prospective, multicenter study, Antonio León-Justel, PhD, of the biochemistry department at the Hospital Universitario Virgen del Rocío in Seville, Spain, and colleagues analyzed data from 353 patients treated in endocrinology units in 13 university hospitals in Spain between 2012 and July 2013. All participants had at least two of five features compatible with Cushing’s syndrome, including obesity, hypertension, poorly controlled diabetes,hirsutism with menstrual disorders and osteoporosis; none of the included patients was referred to clinic with the suspicion of Cushing’s syndrome. All patients underwent late-night salivary cortisol and serum cortisol measurements after a low-dose (1 mg) dexamethasone test; those with discordant results were followed until December 2014 (mean follow-up time, 22.2 months).

Within the cohort, 26 (7.4%) patients were diagnosed with Cushing’s syndrome (20 adrenocorticotropic hormone-dependent; six of adrenal origin). In univariate logistic regression analysis, researchers found that muscular atrophy (OR = 15.2), followed by osteoporosis (OR = 4.6), dorsocervical fat pad (OR = 3.32), absence of obesity (OR = 0.21) and absence of type 2 diabetes (OR = 0.26), were associated with Cushing’s syndrome; late-night salivary cortisol values were also related (OR = 1.26). However, after multivariable adjustment, researchers found that muscular atrophy (OR = 9.04; 95% CI, 2.36-34.65), osteoporosis (OR = 3.62; 95% CI, 1.16-11.35) and dorsocervical fat (OR = 3.3; 95% CI, 1.52-7.17) remained as independent variables with Cushing’s syndrome.

“Obesity and type 2 diabetes displayed a negative association with [Cushing’s syndrome],” the researchers wrote. “These results might seem paradoxical a priori, but we want to stress that in our analyzed cohort, the prevalence of obesity and diabetes was exceedingly high (likely reflecting the reasons for referral to endocrinology units).”

In receiver operating characteristic (ROC) analysis, researchers determined that a cutoff value of 9.17 nmol/L for late-night salivary cortisol provided the best results, with an area under the curve of 0.893 (P < .001), a sensitivity of 88.5% and specificity of 83.2%.

Researchers developed a risk-scoring system, determining cutoff values from a ROC curve. The estimated area under the ROC curve was 0.93 (P < .001), with a sensitivity of 96.2% and specificity of 82.9%.

“Selecting this cutoff value of four, 271 of 327 subjects (83%) without [Cushing’s syndrome] were correctly identified, while only 1 of 26 [Cushing’s syndrome] cases was missed,” the researchers wrote. “Our model yielded 56 false positives.

“Although all the assessments were performed by specialists (endocrinologists) in our study, this scoring system could be easily tested in independent cohorts and different settings such as primary care or hypertension clinics,” the researchers wrote. “At the very least, our diagnostic prediction model could be used as a framework for future studies and potential improvements in diagnostic performance.” – by Regina Schaffer

Disclosure: Leon-Justel and another researcher report receiving a research grant from Novartis Oncology, Spain.

From http://www.healio.com/endocrinology/adrenal/news/in-the-journals/%7B50d3d398-c8fe-41e9-b815-87626bfe8a4b%7D/screening-tool-accurately-predicts-cushings-syndrome-in-most-at-risk-patients

GH therapy increases fracture risk in patients previously treated for acromegaly

van Varsseveld NC, et al. Pituitary. 2016;doi:10.1007/s11102-016-0716-3.

Adult patients with severe growth hormone deficiency previously treated for acromegaly saw an increased fracture risk after 6 years of growth hormone replacement therapy, whereas those previously treated for Cushing’s disease did not experience the same risk, according to a recent observational study.

Nadege C. van Varsseveld, MD, of the department of internal medicine at VU University Medical Center in Amsterdam, and colleagues analyzed data from 1,028 patients with previous nonfunctioning pituitary adenoma (NFPA; n = 783), acromegaly (n = 65) and Cushing’s disease (n = 180), identified through the Dutch National Registry of Growth Hormone Treatment in Adults, a nationwide, long-term surveillance study in patients with severe GH deficiency. Data were collected biannually from medical records through 2009. Baseline DXA measurements were available for 414 patients; 71 (17.1%) had osteoporosis at one or more of the measured sites; 147 (35.5%) had osteopenia.

During a mean follow-up of 5.2 years, researchers found that 166 of patients with previous NFPA were prescribed osteoporosis medications (21.3%), as were 69 patients with previous Cushing’s disease (38.5%) and 22 patients with previous acromegaly (33.4%). During follow-up, 39 patients experienced fractures (3.8%; 32 experiencing one fracture), including 26 patients in the previous NFPA group, eight patients in the previous Cushing’s disease group and five patients in the previous acromegaly group. The median time between baseline and first fracture was 2.4 years (mean age, 59 years).

Researchers found that fracture risk did not differ between groups before 6 years’ follow-up. Fracture risk increased in patients with previous acromegaly after 6 years’ follow-up, but not for those with previous Cushing’s disease vs. patients with NFPA. Results persisted after adjustment for multiple factors, including sex, age, fracture history and the extent of pituitary insufficiency.

The researchers noted that patients with previous Cushing’s disease were younger and more often women and had a greater history of osteopenia or osteoporosis, whereas patients with acromegaly had a longer duration between tumor treatment and the start of GH therapy and were treated more often with radiotherapy.

“During active acromegaly, increased bone turnover has been observed, but reported effects on [bone mineral density] are heterogeneous,” the researchers wrote. “It is postulated that cortical BMD increases, whereas trabecular BMD decreases or remains unaffected.

“The increased fracture risk in the present study may be a long-term effect of impaired skeletal health due to previous GH excess, even though this was not reflected by an increased occurrence of osteopenia or osteoporosis in the medical history,” the researchers wrote. – by Regina Schaffer

Disclosure: One researcher reports receiving consultancy fees from Novartis and Pfizer.

From http://www.healio.com/endocrinology/hormone-therapy/news/online/%7B92a67ad7-3bd5-46f0-b999-0a8e3486edab%7D/gh-therapy-increases-fracture-risk-in-patients-previously-treated-for-acromegaly

Six controversial issues on subclinical Cushing’s syndrome

Abstract

Subclinical Cushing’s syndrome is a condition of hypercortisolism in the absence of signs specific of overt cortisol excess, and it is associated with an increased risk of diabetes, hypertension, fragility fractures, cardiovascular events and mortality.

The subclinical Cushing’s syndrome is not rare, being estimated to be between 0.2–2 % in the adult population. Despite the huge number of studies that have been published in the recent years, several issues remain controversial for the subclinical Cushing’s syndrome screening, diagnosis and treatment.

The Altogether to Beat Cushing’s syndrome Group was founded in 2012 for bringing together the leading Italian experts in the hypercortisolism-related diseases. This document represents the Altogether to Beat Cushing’s syndrome viewpoint regarding the following controversial issues on Subclinical Cushing’s syndrome (SCS):

(1) Who has to be screened for subclinical Cushing’s syndrome?
(2) How to screen the populations at risk?
(3) How to diagnose subclinical Cushing’s syndrome in patients with an adrenal incidentaloma?
(4) Which consequence of subclinical Cushing’s syndrome has to be searched for?
(5) How to address the therapy of choice in AI patients with subclinical Cushing’s syndrome?
(6) How to follow-up adrenal incidentaloma patients with subclinical Cushing’s syndrome surgically or conservatively treated?

Notwithstanding the fact that most studies that faced these points may have several biases (e.g., retrospective design, small sample size, different criteria for the subclinical Cushing’s syndrome diagnosis), we believe that the literature evidence is sufficient to affirm that the subclinical Cushing’s syndrome condition is not harmless and that the currently available diagnostic tools are reliable for identifying the majority of individuals with subclinical Cushing’s syndrome.

Keywords

Subclinical hypercortisolism, Adrenal incidentalomas, Hypertension, Diabetes, Osteoporosis

Identification Of Potential Markers For Cushing’s Disease

Endocr Pract. 2016 Jan 20. [Epub ahead of print]

Abstract

OBJECTIVE:

Cushing’s disease (CD) causes a wide variety of nonspecific symptoms, which may result in delayed diagnosis. It may be possible to uncover unusual combinations of otherwise common symptoms using ICD-9-CM codes. Our aim was to identify and evaluate dyads of clinical symptoms or conditions associated with CD.

METHODS:

We conducted a matched case-control study using a commercial healthcare insurance claims database, designed to compare the relative risk (RR) of individual conditions and dyad combinations of conditions among patients with CD versus matched non-CD controls.

RESULTS:

With expert endocrinologist input, we isolated 10 key conditions (localized adiposity, hirsutism, facial plethora, polycystic ovary syndrome, abnormal weight gain, hypokalemia, deep venous thrombosis, muscle weakness, female balding, osteoporosis) with RR varying from 5.1 for osteoporosis to 27.8 for hirsutism. The RR of dyads of these conditions ranged from 4.1 for psychiatric disorders/serious infections to 128.0 for hirsutism/fatigue in patients with vs. without CD. Construction of uncommon dyads resulted in further increases in RR beyond single condition analyses, such as osteoporosis alone had RR of 5.3, which increased to 8.3 with serious infections and to 52.0 with obesity.

CONCLUSION:

This study demonstrated that RR of any one of 10 key conditions selected by expert opinion was ≥5 times greater in CD compared to non-CD, and nearly all dyads had RR≥5. An uncommon dyad of osteoporosis and obesity had an RR of 52.0. If clinicians consider the diagnosis of CD when the highest-risk conditions are seen, identification of this rare disease may improve.

KEYWORDS:

Cushing’s disease; delay in diagnosis; disease markers; insurance claims; relative risk

PMID:
26789346
[PubMed – as supplied by publisher]

From http://www.ncbi.nlm.nih.gov/pubmed/26789346

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