scholarly journals Epidemiology and in-Depth Clinical and Biochemical Assessment of Cushing’s Syndrome – A Population-Based Study

Author(s):  
Jessica Mangion ◽  
Miriam Giordano Imbroll ◽  
Sarah Craus ◽  
Josanne Vassallo ◽  
Mark Gruppetta

Abstract Purpose: To provide complete epidemiological data on Cushing’s Syndrome (CS) with analysis and differentiation of biochemical parameters including blood count indices and serum inflammation-based scores.Methods: Clinical records of 35 patients diagnosed with CS between 2008 and 2020 at the only central national health service hospital in Malta, were retrospectively analysed. Detailed clinical and biochemical data were obtained for each patient. Correlation and receiver operator characteristics (ROC) curve analyses were used to establish a threshold value for different variables to predict malignant CS.Results: Standardized incidence rate (SIR) (/million/year) of CS was 4.5, SIR of Cushing’s disease (CD) was 2.3, 0.5 for ectopic CS, 1.5 for cortisol secreting adrenal adenoma and 0.3 cases for cortisol-producing ACC. Malignant cause of CS had a statistically significant higher cortisol, size of tumour and lower potassium at diagnosis (P<0.001). Additionally, malignant causes had a higher neutrophil-to-lymphocyte ratio (NLR) (P=0.001), systemic immune inflammation index (P=0.005) and a lower lymphocyte-to-monocyte ratio (P<0.001). Using ROC curve analysis to predict malignant cause of CS, a potassium level of < 3.05 was 75% sensitive and 100% specific (ROC-AUC 0.907, P = 0.001), a post-ODST cortisol level of > 841nmol/L was 100% sensitive and 91% specific (ROC-AUC 0.981, P <0.001), while a NLR ratio > 3.9 was 100% sensitive and 57.7% specific (ROC-AUC 0.885, P = 0.001).Conclusion: Biochemical and blood count indices and serum inflammatory-based scores remarkably differ between benign and malignant causes of endogenous CS and such indices can help in predicting severity of disease and thus prognosis.

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Imogen Schofield ◽  
David C. Brodbelt ◽  
Noel Kennedy ◽  
Stijn J. M. Niessen ◽  
David B. Church ◽  
...  

AbstractCushing’s syndrome is an endocrine disease in dogs that negatively impacts upon the quality-of-life of affected animals. Cushing’s syndrome can be a challenging diagnosis to confirm, therefore new methods to aid diagnosis are warranted. Four machine-learning algorithms were applied to predict a future diagnosis of Cushing's syndrome, using structured clinical data from the VetCompass programme in the UK. Dogs suspected of having Cushing's syndrome were included in the analysis and classified based on their final reported diagnosis within their clinical records. Demographic and clinical features available at the point of first suspicion by the attending veterinarian were included within the models. The machine-learning methods were able to classify the recorded Cushing’s syndrome diagnoses, with good predictive performance. The LASSO penalised regression model indicated the best overall performance when applied to the test set with an AUROC = 0.85 (95% CI 0.80–0.89), sensitivity = 0.71, specificity = 0.82, PPV = 0.75 and NPV = 0.78. The findings of our study indicate that machine-learning methods could predict the future diagnosis of a practicing veterinarian. New approaches using these methods could support clinical decision-making and contribute to improved diagnosis of Cushing’s syndrome in dogs.


2015 ◽  
Vol 62 (9) ◽  
pp. 466-469
Author(s):  
Run Yu ◽  
Meng Wei ◽  
Xuemo Fan ◽  
Richard R. Ellis ◽  
Glenn D. Braunstein

2021 ◽  
Vol 12 ◽  
Author(s):  
Ariadne Bosman ◽  
Annewieke W. van den Beld ◽  
Richard A. Feelders ◽  
M. Carola Zillikens

ObjectivesThe influence of hypercortisolism on phosphate homeostasis is relatively unknown. A few previous studies have reported on patients with Cushing’s syndrome (CS) with hypophosphatemia in whom serum phosphate normalized after initiation of treatment for CS. We aimed to investigate the prevalence of hypophosphatemia in CS, the association between the degree of hypercortisolism and serum phosphate and the change in serum phosphate after remission of CS. We compared the prevalence of hypophosphatemia in CS with the prevalence in the population-based Rotterdam Study (RS).MethodsPatients diagnosed with CS and treated at the Department of Endocrinology of Erasmus MC in the period of 2002-2020 were included and data was collected on age at diagnosis, sex, serum phosphate, calcium and potassium levels, kidney function and BMI. Using multivariate linear regression, we analyzed the association between 24h urinary free cortisol excretion (UFC) and serum phosphate. Changes in serum phosphate and covariates were tested with a repeated measurement ANOVA, using mean levels of laboratory values for the periods before remission, and 0-14 days and 15-180 days after remission.ResultsHypophosphatemia before treatment was present in 16% of the 99 CS patients with data on serum phosphate, 24h UFC and covariates. In comparison, the prevalence of hypophosphatemia in RS was 2.0-4.2%. Linear regression showed a negative association between the level of UFC and serum phosphate at diagnosis, which remained significant after adjusting for covariates [β -0.002 (95%CI -0.004; -0.0004), p=0.021]. A subset of 24 patients had additional phosphate measurements at 0-14 days and 15-180 days after remission. In this subgroup, serum phosphate significantly increased from 1.03 ± 0.17 mmol/L prior to remission to 1.22 ± 0.25 mmol/L 15-180 days after remission (p = 0.008). BMI decreased after remission [-1.1 kg/m2, (95%CI -2.09 to -0.07), p=0.037]. Other covariates did not show an equivalent change over time.ConclusionIn this retrospective study, we found that 16% of patients with CS had hypophosphatemia. Moreover, serum phosphate was related to the level of cortisoluria and increased after remission of CS. Potential underlying mechanisms related to urinary phosphate excretion and possibly involving FGF23, BMI and parathyroid hormone levels should be further explored.


2019 ◽  
Vol 109 (2) ◽  
pp. 171-178 ◽  
Author(s):  
Mesut Savas ◽  
Vincent L. Wester ◽  
Yolanda B. de Rijke ◽  
German Rubinstein ◽  
Stephanie Zopp ◽  
...  

Background/Aims: The current diagnostic workup of Cushing’s syndrome (CS) requires various tests which only capture short-term cortisol exposure, whereas patients with endogenous CS generally have elevated cortisol levels over longer periods of time. Scalp hair assessment has emerged as a convenient test in capturing glucocorticoid concentrations over long periods of time. The aim of this multicenter, multinational, prospective, case-control study was to evaluate the diagnostic efficacy of scalp hair glucocorticoids in screening of endogenous CS. Methods: We assessed the diagnostic performances of hair cortisol (HairF), hair cortisone (HairE), and the sum of both (sumHairF+E), as measured by a state-of-the-art LC-MS/MS technique, in untreated patients with confirmed endogenous CS (n = 89) as well as in community controls (n = 295) from the population-based Lifelines cohort study. Results: Both glucocorticoids were significantly elevated in CS patients when compared to controls. A high diagnostic efficacy was found for HairF (area under the curve 0.87 [95% CI: 0.83–0.92]), HairE (0.93 [0.89–0.96]), and sumHairF+E (0.92 [0.88–0.96]) (all p < 0.001). The participants were accurately classified at the optimal cutoff threshold in 86% of the cases (81% sensitivity, 88% specificity, and 94% negative predictive value [NPV]) by HairF, in 90% of the cases (87% sensitivity, 90% specificity, and 96% NPV) by HairE, and in 87% of the cases (86% sensitivity, 88% specificity, and 95% NPV) by the sumHairF+E. HairE was shown to be the most accurate in differentiating CS patients from controls. Conclusion: Scalp hair glucocorticoids, especially hair cortisone, can be seen as a promising biomarker in screening for CS. Its convenience in collection and workup additionally makes it feasible for first-line screening.


2020 ◽  
Vol 4 (1) ◽  
pp. 56-58
Author(s):  
Shoko Uketa ◽  
Yousuke Shimizu ◽  
Kosuke Ogawa ◽  
Noriaki Utsunomiya ◽  
Satsuki Asai ◽  
...  

2001 ◽  
Vol 24 (6) ◽  
pp. 723-726 ◽  
Author(s):  
Tadaaki HONDA ◽  
Tetsuya NAKAMURA ◽  
Yuichiro SAITO ◽  
Yoshio OHYAMA ◽  
Hiroyuki SUMINO ◽  
...  

2015 ◽  
Vol 173 (4) ◽  
pp. M99-M106 ◽  
Author(s):  
Davide Calebiro ◽  
Guido Di Dalmazi ◽  
Kerstin Bathon ◽  
Cristina L Ronchi ◽  
Felix Beuschlein

The cAMP signaling pathway is one of the major players in the regulation of growth and hormonal secretion in adrenocortical cells. Although its role in the pathogenesis of adrenocortical hyperplasia associated with Cushing's syndrome has been clarified, a clear involvement of the cAMP signaling pathway and of one of its major downstream effectors, the protein kinase A (PKA), in sporadic adrenocortical adenomas remained elusive until recently. During the last year, a report by our group and three additional independent groups showed that somatic mutations of PRKACA, the gene coding for the catalytic subunit α of PKA, are a common genetic alteration in patients with Cushing's syndrome due to adrenal adenomas, occurring in 35–65% of the patients. In vitro studies revealed that those mutations are able to disrupt the association between catalytic and regulatory subunits of PKA, leading to a cAMP-independent activity of the enzyme. Despite somatic PRKACA mutations being a common finding in patients with clinically manifest Cushing's syndrome, the pathogenesis of adrenocortical adenomas associated with subclinical hypercortisolism seems to rely on a different molecular background. In this review, the role of cAMP/PKA signaling in the regulation of adrenocortical cell function and its alterations in cortisol-producing adrenocortical adenomas will be summarized, with particular focus on recent developments.


2003 ◽  
Vol 29 (1) ◽  
pp. 67-71 ◽  
Author(s):  
Ilias Vrezas ◽  
Paul Wentworth ◽  
Stefan R. Bornstein

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