Osilodrostat for Cyclic Cushing’s Disease

Posted on October 24, 2025 by MaryO

Highlights

  • •
    Cyclic Cushing’s syndrome (CCS) is a rare entity with significant comorbidities
  • •
    It is defined by at least 3 peaks of hypercortisolism, 2 troughs of eucortisolism
  • •
    Surgical cure is preferred, and medications are second-line
  • •
    Our case is the first showing successful treatment of native CCS with osilodrostat
  • •
    Osilodrostat showed rapid onset/offset and reversible inhibition of steroidogenesis

Abstract

Background/Objective

Cyclic Cushing’s syndrome is a rare subtype of Cushing’s syndrome with episodes of hypercortisolism, followed by spontaneous remission.

Case Report

Our patient was a 68-year-old male who presented with his third cycle of cyclic Cushing’s disease with facial swelling, buffalo hump, fatigue, proximal muscle weakness, and lower extremity edema. Laboratory tests showed the following: 24-hour urine free cortisol 12030.3 mcg/d (normal <= 60.0 mcg/d), morning adrenocorticotropic hormone (ACTH) 464 pg/mL (normal 6-59 pg/mL), morning serum cortisol 91 mcg/dL (normal 8-25 mcg/dL), and potassium 3.3 mmol/L (normal 3.6-5.3 mmol/L). MRI pituitary without/with contrast showed a partially empty sella. Prior inferior petrosal sinus sampling during the second cycle indicated a potential pituitary source of increased ACTH production, localized or draining to the right side. The patient was treated with osilodrostat with improvement in laboratory values and clinical symptoms by 2-3 weeks. After development of adrenal insufficiency (AI), osilodrostat was rapidly titrated off by 2 months of treatment. Subsequently, labs after 8 days off osilodrostat confirmed clinical remission and reversibility of medication-induced AI.

Discussion

Since hypercortisolism is associated with mortality risk and comorbidities, timely management is a priority. If a surgical cure is not possible, a medication that treats hypercortisolism with rapid onset, reversible inhibition, and minimal side effects would be ideal to address the cyclicity.

Conclusion

Our case is the first to our knowledge demonstrating osilodrostat’s use for native cyclic Cushing’s syndrome treatment and highlighted its reversibility and ability to preserve normal adrenal function.

Keywords

Osilodrostat
cyclic Cushing’s disease
cyclic Cushing’s syndrome

Introduction

Cyclic Cushing’s syndrome is a rare entity that represents a clinical challenge. It is defined by at least 3 peaks of biochemical hypercortisolism, which is clinically symptomatic in the majority though rarely asymptomatic, and 2 troughs with normalized cortisol production that can last from days to years.1 The phenomenon can arise from any potential source of Cushing’s syndrome, including pituitary (54%), ectopic (26%), adrenal (11%), and unclassified (9%) sources.1 Intermittent hypercortisolism can also occur after pituitary surgery for Cushing’s disease.2
The cyclicity interferes with a straightforward diagnosis. It can lead to paradoxical results from biochemical testing and inferior petrosal sinus sampling (IPSS),3 making determination of therapeutic outcomes more complicated.3 The goal of cyclic Cushing’s syndrome management, as in all types of Cushing’s syndrome, is early diagnosis and intervention to reduce the length of hypercortisolism.4 A surgical cure is preferred, as Cushing’s syndrome is associated with a five-fold increased standardized mortality risk.4 Cardiovascular, metabolic, bone, and cognitive comorbidities may persist despite remission and must be aggressively managed.4,5 For patients in whom surgical management is not possible or has not led to remission, medical therapy has a crucial role. We describe the first case to our knowledge of native cyclic Cushing’s syndrome treated successfully with osilodrostat. A case of exogenous cyclic ACTH-independent Cushing’s syndrome from pembrolizumab, with cyclicity attributed to the infusions, also demonstrated successful treatment with osilodrostat.6

Case Report

The patient was a 68-year-old male with hypertension, hyperlipidemia, and rheumatoid arthritis with a history of cyclical episodes of weight gain and facial swelling, occurring spontaneously without steroid treatments. The initial episode occurred at age 62 for 5 months, and returned at age 64 with facial swelling, buffalo hump, fatigue, proximal muscle weakness, sleep disturbances, and lower extremity edema. Laboratory tests showed the following (Table 1): 24-hour urine free cortisol >245 mcg/d (normal 11-84 mcg/d), morning adrenocorticotropic hormone (ACTH) 528.0 pg/mL (normal 7.2-63.3 pg/mL) and morning serum cortisol 91.7 mcg/dL (confirmed on dilution; normal 6.2-19.4 mcg/dL). Laboratory tests were also notable for a mildly low potassium level, low prolactin, low testosterone, and normal thyroid hormone, insulin-like growth factor-1 (IGF-1), and dehydroepiandrosterone sulfate (DHEA-S) levels. MRI pituitary without/with contrast showed no sellar and suprasellar masses. A prior CT abdomen/pelvis with contrast at age 62 noted unremarkable adrenal glands. The patient was referred for inferior petrosal sinus sampling (IPSS) (Table 2), which indicated a potential pituitary source of increased ACTH production, localized or draining to the right side. The central to peripheral gradient was >2 in the first pre-stimulation sample and >3 in all samples after providing 10mcg of desmopressin (DDAVP). There was a >1.4/1 gradient between the right and left sides, suggesting a potential pituitary source draining to the right side (Table 2). The inferior petrosal sinuses were normal and of similar size. Cushing’s symptoms receded spontaneously in 5 months, and the patient did not follow up until recurrence at age 67.

Table 1. Labs at time of onset of cyclical episodes

Empty Cell Labs at age 64 y/o (2nd episode) Labs at age 67 y/o (3rd episode)
24hr urine free cortisol level >245 mcg/24hr (normal 11-85 mcg/24hr) 12030.3 mcg/d (normal <= 60.0 mcg/d)
24hr urine creatinine 1495 mg/24hr (normal 1000-2000mg/24hr) 1868 mg/day (normal 800-2100 mg/day)
Morning ACTH 528.0 pg/mL (normal 7.2-63.3 pg/mL) 464 pg/mL (normal 6-59 pg/mL),
Morning cortisol 91.7 mcg/dL (normal 6.2-19.4 mcg/dL) 91 mcg/dL (normal 8-25 mcg/dL)
Thyroid-stimulating hormone level (TSH) 0.452 mcIU/mL (normal 0.450-4.500 mcIU/mL) 0.08 mcIU/mL (normal 0.3-4.7 mcIU/mL)
Free thyroxine (free T4) 1.34 ng/dL (normal 0.82-1.77 ng/dL) 1.30 ng/dL (normal 0.8-1.7 ng/dL)
Prolactin <1.0 ng/mL (normal 3.0-15.2 ng/mL) 8.05 ng/mL (normal 3.5-19.4 ng/mL)
Insulin-like growth factor-1 (IGF-1) 148 ng/mL (normal 64-240 ng/mL) 128 ng/mL (normal 41-279 ng/mL)_
Testosterone panel Total 66 ng/dL(11AM)
(normal 264-916 ng/dL)
Free 9.6 pg/mL (11AM)
(normal 6.6-18.1 pg/mL)		 Total 107 ng/dL (8:30AM)
(normal 300-720 ng/dL)
Bioavailable 61 ng/mL (8:30AM)
(normal 131-682 ng/mL)
Follicle-Stimulation Hormone (FSH) 3.6 mIU/mL (normal 1.6-9 mIU/mL)
Luteinizing Hormone (LH) 1.6 mIU/mL (normal 2-12 mIU/mL)
Dehydroepiandrosterone sulfate (DHEA-S) 153 mcg/dL (normal 48.9-344.2 mcg/dL)
Potassium level 3.2 mmol/L (normal 3.4-4.8 mmol/L) 3.3 mmol/L (normal 3.6-5.3 mmol/L)
Creatinine level 0.92 mg/dL (normal 0.7-1.2 mg/dL) 0.89 mg/dL (normal 0.6-1.3 mg/dL)

Table 2. Inferior Petrosal Sinus Sampling (IPSS)

Empty Cell Time Right IPS
ACTH level (normal 6-59 pg/mL)		 Left IPS
ACTH level (normal 6-59 pg/mL)		 Inferior Vena Cava ACTH level (normal 6-59 pg/mL) Serum Cortisol (normal 8-25 mcg/dL)
Baseline 1 08:25 AM 32 23 14 7
Baseline 2 08:27 AM 19 16 13 7
Desmopressin (DDAVP) 08:30 AM
Post 2 min 08:32 AM 150 34 15
Post 5 min 08:35 AM 123 32 18
Post 10 min 08:40 AM 49 26 17
Post 15 min 08:45 AM 124 31 17
Post 30 min 09:00 AM 107 28 13
*These results may indicate a pituitary source for increased ACTH production, localized or draining to the right side. There is a Central:Peripheral gradient of >2 (right IPS) in the first pre-stimulation samples and >3 in all post-desmopressin (DDAVP) 10mcg samples. If due to an adenoma, it might drain into the right given the presence of a significant (greater than 1.4/1) gradient between right and left. The inferior petrosal sinuses were of similar size and normal. These results must take into account the patient’s clinical scenario, and there are false positives and possible overlap with normal results.
*Abbreviation: min = minutes
During the third and most recent cycle of Cushing’s syndrome, laboratory tests after 1 month of symptom development showed the following (Table 1): 24-hour urine free cortisol 12030.3 mcg/d (normal <= 60.0 mcg/d), morning ACTH 464 pg/mL (normal 6-59 pg/mL), morning serum cortisol 91 mcg/dL (normal 8-25 mcg/dL), potassium level 3.3 mmol/L (normal 3.6-5.3 mmol/L), and mild leukocytosis and erythrocytosis. Repeat MRI pituitary without/with contrast showed a partially empty sella and no pituitary mass (Figure 1).

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Figure 1. MRI pituitary without/with contrast at the time of the third cyclical episode of Cushing’s disease. The MRI showed a partially empty sella with no evidence of a pituitary mass. Left) Coronal view. Right) Sagittal view.

The patient was started on osilodrostat 2mg twice daily. By week 2 of treatment, the morning cortisol level improved to 9.5 mcg/dL (8-25 mcg/dL) and potassium level normalized, though facial and body swelling persisted. Significant improvement in symptoms and fatigue were noted by week 3 of treatment with the following labs: morning ACTH 145 pg/mL (normal 6-59 pg/mL), morning serum cortisol 5.4 mcg/dL (8-25 mcg/dL), and 24-hour urine free cortisol 7 mcg/d (normal 5-64 mcg/d). The osilodrostat dose was decreased to 1mg twice daily, then 1mg daily, and stopped by 2 months of treatment after development of adrenal insufficiency (AI), which was confirmed on laboratory results (Table 3), along with corresponding symptoms of nausea, abdominal pain, low appetite, and fatigue. By that time, the facial and body swelling had also resolved. Potassium levels remained normal throughout treatment. After eight days off osilodrostat, laboratory tests showed the following: Noon ACTH 67 pg/mL (normal 6-59 pg/mL), noon serum cortisol 7.24 mcg/dL (normal 8-25 mcg/dL), and 24-hour urine free cortisol 26.2 mcg/d (normal <=60.0 mcg/d). Nearly 3 months off osilodrostat, the patient had an 11 AM ACTH of 68.9 pg/mL (normal 7.2-63.3 pg/mL) and 11AM serum cortisol level of 11.0 ug/dL (6.2-19.4 ug/dL). The clinical course is summarized in Table 3 and Figure 2. A DOTATATE-PET scan was discussed, though the patient wished to reconsider in the future given clinical response.

Table 3. Labs during treatment (Tx) with osilodrostat

Empty Cell 1 month before Tx Week 2 on Tx Week 3 on Tx Week 7 on Tx Week 9 on Tx – Tx stopped Week 1 off Tx Month 3 off Tx
Treatment with osilodrostat None On 2mg BID since Week 0 of Tx Advised to decrease to 1mg BID but patient did not decrease dose. Decreased to 1mg BID Decreased to 1mg daily after serum lab resulted. Then discontinued Tx after 24hr UFC resulted in several days. None None
ACTH level (pg/mL) 464 145 126 135 67 68.9
Cortisol level (mcg/dL) 91
8:32AM		 9.5
7:04AM		 5.4
7:11AM		 3.04
11:56AM		 4.9
11:26AM		 7.24
12:14PM		 11
11:08AM
24hr urine free cortisol (UFC) level (mcg/day) 12030.3 7 14 26.2
*Normal reference ranges depending on assays:
ACTH: 6-59 pg/mL or 7.2-63.3 pg/mL
Serum morning cortisol: 8-25 mcg/dL or 6.2-19.4 mcg/dL
24hr urine free cortisol: <=60.0 mcg/day or 5-64 mcg/day
*Acronyms: Tx = treatment; BID = twice daily; UFC = urine free cortisol, ACTH = adrenocorticotropic hormone

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Figure 2. Trends of 24hr urine cortisol levels and serum cortisol levels with osilodrostat treatment (Tx)

Discussion

Cyclic Cushing’s syndrome is a rare subtype of Cushing’s and occurs in both ACTH-dependent and ACTH-independent cases.3,7 Cyclicity has been attributed to hypothalamic dysfunction exaggerating a normal variant of hormonal cyclicity, a dysregulated positive feedback mechanism followed by negative feedback, intra-tumoral bleeding, and ACTH-secretion from neuroendocrine tumors (ex carcinoid tumors, pheochromocytomas).7,8,9,10
Potentially curative pituitary surgery or unilateral adrenalectomy are the treatments of choice.4 For example, cases of cyclic Cushing’s in primary pigmented nodular adrenocortical disease have demonstrated cure in some patients with unilateral adrenalectomy.11 In florid Cushing’s syndrome that is not amenable or responsive to other treatments, bilateral adrenalectomy could be lifesaving, though risks significant comorbidities including Nelson’s syndrome.4,12 Pituitary radiotherapy/radiosurgery are treatment options, though risks progressive anterior pituitary dysfunction.4 Medical therapy can play an important role as a bridge to surgery or radiation, with recurrence, for poor surgical candidates, or when there is no identifiable source as in our patient.13 Cyclic Cushing’s syndrome, moreover, has a higher recurrence rate (63%) and lower remission rate (25%), compared to classic Cushing’s syndrome.8
Medical treatments of cyclic Cushing’s syndrome include steroidogenesis inhibitors (ketoconazole, levoketoconazole, metyrapone, and osilodrostat), adrenolytic agents (mitotane), glucocorticoid receptor blockers (mifepristone), and pituitary tumor-directed agents (pasireotide, cabergoline, and temozolomide).8,14,15 Treatment goal is normalization of 24-hour urine cortisol levels and morning serum cortisol levels, though block-and-replace regimens occasionally are used.13,14 A block-and-replace regimen with osilodrostat and dexamethasone was used in the case of exogenous cyclic Cushing’s from pembrolizumab, given need for the immunotherapy;6 however, this regimen would hinder assessment of remission in native cyclic Cushing’s.
As our patient had cyclic Cushing’s disease, pituitary tumor-directed medications could be used for treatment. Pasireotide and cabergoline, however, are limited by a significant percentage of non-responders, along with risk of hyperglycemia for pasireotide.15 We considered mifepristone, which is a competitive antagonist at the glucocorticoid receptor and progesterone receptor; however, mifepristone is limited by the inability to directly monitor cortisol response on labs, in addition to the risk of AI and mineralocorticoid side effects with overtreatment.16
Steroidogenesis inhibitors block one or more enzymes in the production of cortisol, with potential risk of AI. The new steroidogenesis inhibitor osilodrostat, like metyrapone, selectively inhibits CYP11B1 and CYP11B2, which are involved in the final steps of cortisol and aldosterone synthesis, respectively.13,14 Ketoconazole and levoketoconazole, on the other hand, block most enzymes in the adrenal steroidogenesis pathway, including CYP11B1 and CYP11B2, and are limited by their inhibition of CYP7A (with associated hepatotoxicity) and strong inhibition of cytochrome p450 CYP3A4 (leading to many drug-drug interactions, decreased testosterone production, and QTc prolongation).14
Osilodrostat and metyrapone do not affect CYP7A and less potently inhibit CYP3A4.13 However, they can lead to increased deoxycorticosterone levels, with associated risks of hypokalemia, hypertension, and edema, and increased androgen production (with metyrapone thus being considered second-line in women).13,14,17
Osilodrostat, compared to metyrapone and ketoconazole, has a higher potency in CYP11B1 and CYP11B2 inhibition and a longer half-life, with stronger effects in lowering cortisol levels, allowance of less frequent (twice daily) dosing, and possibly less side effects.13,14,17,18 Compared to metyrapone, studies have suggested osilodrostat leads to a lesser rise in 11-deoxycortisol levels and less hyperandrogenic effects.13,14 Osilodrostat is also rapidly absorbed with sustained efficacy up to 6.7 years.17,18 Though rare cases of prolonged AI following discontinuation exist, osilodrostat (like other steroidogenesis inhibitors) is generally considered a reversible inhibitor.19 Reversible inhibition of cortisol synthesis is particularly appealing to treatment of cyclic Cushing’s syndrome as patients will not suffer from prolonged AI after episodes subside.
We thus considered osilodrostat an attractive treatment of cyclic Cushing’s syndrome. In our patient, osilodrostat was efficacious and well-tolerated, consistent with the literature,17 with clinical effects within 2-3 weeks without significant mineralocorticoid side effects. Differentiation of AI as a side effect of osilodrostat or from remission of the cyclical episode is crucial. Our patient was carefully tapered off osilodrostat after developing AI, and reversal of AI and osilodrostat inhibition were clearly demonstrated after 8 days off osilodrostat. Off treatment, the patient demonstrated neither prolonged AI nor clinical hypercortisolism, confirming remission of cyclic Cushing’s.

Conclusion

We present the first case to our knowledge demonstrating successful treatment of cyclic Cushing’s syndrome with osilodrostat. Osilodrostat showed rapid and safe control of hypercortisolism and importantly exhibited quick reversible inhibition of steroidogenesis upon discontinuation, a virtue in cyclic Cushing’s syndrome management.

References

Cited by (0)

The authors declare the following:
This paper did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
All authors do not have any conflicts of interests regarding the manuscript.
Run Yu, MD, PhD runyu@mednet.ucla.edu
Clinical Relevance
Osilodrostat is a new steroidogenesis inhibitor. Our case demonstrates the first successful treatment of native cyclic Cushing’s syndrome with osilodrostat, which showed rapid onset/offset, clinical safety, and reversible inhibition of steroidogenesis and medication-induced adrenal insufficiency. Osilodrostat’s preservation of underlying adrenal function is key when the cyclic Cushing’s episode spontaneously remits.

Filed under: Cushing's, pituitary, Rare Diseases, Treatments | Tagged: , , , , | Leave a comment »

Osilodrostat-associated Adrenal Gland Shrinkage: a Case Series of Patients with ACTH-Dependent Cushing’s Syndrome

Posted on October 18, 2025 by MaryO

The Journal of Clinical Endocrinology & Metabolism, dgaf552, https://doi.org/10.1210/clinem/dgaf552

Abstract

Context

Medical therapy for Cushing’s syndrome (CS) is increasingly used. A potent adrenal steroidogenesis inhibitor, osilodrostat, has been rarely linked to prolonged adrenal insufficiency (AI).

Objective

We hypothesized that osilodrostat-induced adrenal insufficiency could be associated with adrenal gland shrinkage.

Design

Non-interventional, retrospective, longitudinal, IRB-approved study of patients with CS treated at Oregon Health and Science University between January 1, 2000 and July 1, 2025.

Setting

Ambulatory and inpatient, academic, quaternary medical center.

Patients or Other Participants

Patients with ACTH-dependent CS, treated with osilodrostat for >3 months, and CT imaging before and after osilodrostat available for adrenal volume (AV) measurement.

Intervention(s)

Age, sex, osilodrostat doses and duration, laboratory data and AI were recorded. AV was calculated using manual segmentation on CT images by a board-certified radiologist.

Main Outcome Measure(s)

AV before and after initiation of osilodrostat was expressed as percent reduction.

Results

10 patients (5 ectopic CS, 4 unknown ACTH source, 1 Cushing’s disease) were included. Osilodrostat mean starting, maximum and final doses: 7.7, 13.8 and 5.9 mg/day, respectively, over 23 months. Four patients received block-and-replace regimen, AI developed in 5. Adrenal gland volume decreased by 46.7±22.2% from 25.5±9.9 ml to 12.7±6.4 ml, p<0.001 over a median of 19 months. AV reduction positively correlated with maximum osilodrostat dose, r=0.626, p=0.027.

Conclusions

We found that in selected patients with ACTH-dependent CS, osilodrostat can induce significant adrenal shrinkage, with or without AI. Further confirmation by larger studies of different CS types and monitoring for AI is required for all patients.

Filed under: adrenal, Cushing's, Treatments | Tagged: , , | Leave a comment »

A Preliminary Model to Tailor Osilodrostat In Patients With Adrenocorticotropic Hormone (ACTH)-Dependent Cushing’s syndrome

Posted on October 10, 2025 by MaryO

Abstract

Over the past 10 years, osilodrostat has become one of the most commonly used steroidogenesis inhibitors in patients with Cushing’s syndrome. The starting dose is usually determined based on the product characteristics, the prescriber’s experience, and cortisol levels. However, no study has attempted to determine whether there was a dose–response relationship between osilodrostat and cortisol reduction. In this study, we developed a preliminary kinetic–pharmacodynamic model to tailor osilodrostat in patients with Adrenocorticotropin hormone (ACTH)-dependent Cushing’s syndrome. We first analyzed the decrease in cortisol 48 hours after initiation or dose change of osilodrostat in 18 patients. Simulations were then performed for different doses of osilodrostat to evaluate the variation in cortisol concentrations. Our results report the first dose–response relationship between osilodrostat dose and cortisol levels, which should be helpful in identifying the optimal dosing regimen in patients with Cushing’s syndrome and in individualizing treatment to approximate a nychthemeral rhythm.

osilodrostat, Cushing’s syndrome, Cushing’s disease, cortisol, adrenal insufficiency
Issue Section:

Brief Report

Significance

The current preliminary study is a first step in trying to better understand the effect of osilodrostat on cortisol, which should help determine the optimal dose for each patient.

Introduction

Cushing’s syndrome is a rare condition in which increased cortisol levels lead to a wide range of comorbidities and increased mortality. Surgery is usually regarded as the first-line and most effective treatment.1 In some cases, cortisol-lowering drugs are necessary, mainly after failed surgery.2,3 Among several steroidogenesis inhibitors such as ketoconazole and metyrapone,4,5 osilodrostat, which acts through inhibition of 11β-hydroxylase, is now being considered an effective drug in controlling cortisol hypersecretion. Initially designed as a CYP11B2 inhibitor, the study by Ménard et al.6 involving both animal models and healthy human subjects showed that osilodrostat reduced cortisol levels from a dose of 1 mg/day, while lower doses exerted an anti-aldosterone effect. Since then, several clinical trials and retrospective studies emphasized its efficacy in all etiologies of Cushing’s syndrome.7-9 While the usual recommended starting dose is 2 mg twice a day, precise studies on the short-term effect of osilodrostat on plasma cortisol are lacking. These data could, however, be of interest to tailor the treatment. Moreover, baseline urinary free cortisol (UFC) level is not able to predict response to osilodrostat.10 Taking advantage of serial cortisol measurements performed in inpatient clinics in our center at the time osilodrostat became available, we developed a pharmacokinetic (PK)/pharmacodynamic model of plasma cortisol variation as a function of osilodrostat dose in patients with Adrenocorticotropin-hormone (ACTH)-dependent Cushing’s syndrome.

Patients and methods

Clinical data and hormonal measurements

We retrospectively included patients with ACTH-dependent Cushing’s syndrome, who had serial measurements of plasma cortisol (every 4 hours for 24 hours) before and after the first osilodrostat dose between 2019 and 2024. These measurements were part of our standard of care approach when osilodrostat became available in our tertiary expert center as a thorough evaluation of the efficacy and tolerance of a new drug. The initial dose ranged from 2 to 15 mg/day, depending on the severity of hypercortisolism. Subsequently, osilodrostat dose was gradually adjusted based on the successive cortisol measurements described above. Sex, age at diagnosis, and etiologies were recorded, as well as plasma cortisol measurements 48 hours after the initiation or any change in the osilodrostat dose and time elapsed since change of dose and last administration were recorded. All plasma cortisol measurements were performed with the same Elecsys II Cortisol, Cobas (Roche Diagnostics) assay in the hormonal laboratory of our center; cross-reactivity with 11-deoxycortisol is 4.9%. According to our institutional policy, this retrospective study did not require specific signed informed consent from patients as the data collected were anonymized. It was thus approved by the Ethics Committee of Assistance Publique—Hopitaux de Marseille (RGPD PADS reference RUXXX2). The current study complies with the Declaration of Helsinki.

Pharmacokinetics and statistical analysis

The pharmacodynamic parameters of osilodrostat on cortisol concentrations were analyzed using a kinetic–pharmacodynamic (PD) model in the software Nonlinear Mixed Effects Modeling version 7.4 (NONMEM Icon Development Solutions, Ellicott City, MD, United States). PK analysis from a previously published study6 was used to predict plasma concentration in our patients. The PK parameters were described in the article, and mean concentration values were obtained by digitizing the graph of osilodrostat vs time using the software WebPlotDigitizer version 4.2.11 With these data, a one-compartment population PK model was used to predict osilodrostat concentrations for different dosing regimens. Direct and indirect relationship between osilodrostat-predicted concentration and variation of cortisol concentrations were evaluated to consider a delay. The variation of cortisol concentrations was calculated with reference to a session without treatment. Several functions were tested to describe the relationship such as linear and sigmoidal. Model selection and evaluation were done by the likelihood ratio test (objective function), goodness-of-fit plots (observed vs predicted variation of cortisol concentrations, observed vs individual predictions, normalized prediction distribution errors vs time and variation of cortisol predictions), bootstrap, and visual predictive checks. Graphical analysis was performed with the R software version 4.4.012 using the ggplot2 package.13 Simulations were performed for different doses of osilodrostat to evaluate the variation on cortisol concentrations using the package rxode2.14

Results

Of the patients who were prescribed osilodrostat at least once between 2019 and 2024, 18 were presenting ACTH-dependent Cushing’s syndrome, 12 women (66.6%) and 6 men (33.3%). Mean age was 53.2 ± 15 years. The cause of Cushing’s syndrome was Cushing’s disease in 16 patients (88.9%), ectopic ACTH secretion in 1 patient (5.6%), and ACTH-dependent hypercortisolism of uncertain diagnosis in 1 patient (5.6%). Clinical characteristics are presented in Table 1. It should be noted that none of the patients included were Asian.

 

 

Table 1.

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Clinical characteristics of patients with all included patients and differentiated according to gender.

All patientsa Women Men
Age at diagnosis 53.2 ± 15 54 ± 17.2 51.5 ± 10.5
Weight 81.7 ± 13.7 79.5 ± 12.7 86.2 ± 15.6
% of CD 88.9 83.3 100
ULN of 24 hour UFC 4.4 ± 8.3 5.5 ± 10.3 2.5 ± 1.8
Osilodrostat starting dose 3.3 ± 2.2 3.7 ± 2.4 2.5 ± 1.4
Cortisol before osilodrostat intake 422.9 ± 159.2 414.7 ± 176.6 439.4 ± 130.7
Cortisol 4 hour after osilodrostat 404 ± 165.6 408.2 ± 200.1 395.5 ± 70.8

 

Abbreviations: CD, Cushing’s disease; ULN, upper limit range; UFC, urinary free cortisol.

aOf note, none of the included patients were Asian.

In their article, Ménard et al.6 showed that the dose–exposure relationship was not strictly proportional. A one-compartment model was enhanced by increasing the relative bioavailability with the dose and was estimated that the dose resulting in a 50% increase in bioavailability was 1.06 mg. The PK parameters derived from Ménard et al.6 were fixed and used to predict osilodrostat concentration in our patients. A direct relationship between the predicted osilodrostat concentrations and variation of cortisol concentrations (%) gave a better fit than an indirect model. The drug effect was modeled with the following sigmoidal function (Eq. 1);

(1)

where Imax is the maximal inhibition and IC50 is the apparent half-maximal inhibitory concentration.

The estimated PD parameters were IC50 and Imax. Their values as well as the relative standard errors (RSE%) and the corresponding bootstrap IC50 are shown in Table 2. Final parameters were used to simulate n = 500 profiles following a single dose of osilodrostat.

 

 

 

Table 2.

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Pharmacodynamic parameters of osilodrostat’s effects on the variation of cortisol concentrations.

Parameters Unit Estimation RSE% Bootstrap
0.025 0.975
KA (fixed)a 1/hour 4.03 — — —
CL/F (fixed)a L/hour 18.3 — — —
V/F (fixed)a L 125 — —
Imax % 44.5 18.7 12.51 90.9
IC50 mg/L 0.011 37.4 0.0001 0.10
Interindividual variability (ω)
 Imax 0.40 30.9 0.003 1.86
 IC50 3.78 41.0 0.003 9.22
Residual unexplained variability (σ)
 Additive % 23.8 12.2 18.2 29.9

 

Abbreviations: CL/F, apparent clearance; IC50, osilodrostat concentration associated with half the maximal inhibition of the cortisol variation; Imax, maximum inhibitory effect of osilodrostat on the variation of cortisol; KA, first-order absorption rate constant; RSE, relative standard error; V/F, apparent volume of distribution.

 

aAdapted from Ménard et al.6

The effects on plasma cortisol variation are depicted in Figure 1. Cortisol concentration declines during the first hour after taking osilodrostat, from 24% for a 1 mg dose to over 42% for a 20 mg dose. Thereafter, from the first hour onward, cortisol increases progressively, with loss of treatment efficacy occurring around the 10th-15th hour for 1 and 2 mg, while for doses above 5 mg, a moderate effect persists over the following hours. Figure 2 shows the variation in cortisol concentration for a 2 mg dose, with median decrease in cortisol variation of 31%, ranging from 0% to 67.5%, with, as mentioned above, a maximum effect 1 hour after osilodrostat intake, and a progressive increase in cortisol levels, mainly during the 12 hours following treatment. The same analysis for 10 mg revealed a median reduction in cortisol of 38%, ranging from 5% to 80%. Figure 3 describes the relationship between osilodrostat concentration and cortisol variation, showing that the maximum effect corresponds to the maximum concentration and that a decrease in osilodrostat concentration results in an increase in cortisol level.

Relationship between time since last administration of osilodrostat and cortisol concentrations.

Figure 1.

Relationship between time since last administration of osilodrostat and cortisol concentrations.

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Visual predictive variation on cortisol concentrations following 2 or 10 mg osilodrostat administration.

Figure 2.

Visual predictive variation on cortisol concentrations following 2 or 10 mg osilodrostat administration.

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Relation between osilodrostat concentration and cortisol variation.

Figure 3.

Relation between osilodrostat concentration and cortisol variation.

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Discussion

To the best of our knowledge, this is the first study that attempts to define a dose/efficacy relationship between osilodrostat dose and the variation of plasma cortisol. First, our results suggest that the effect of osilodrostat appears immediately after the peak of concentration, 1 hour after treatment intake, which highlights the parallel evolution of osilodrostat and cortisol concentrations. This is unusual, as typically effect peak takes few hours, following concentration peak.15 The relationship between osilodrostat concentration and the effect on cortisol is not linear but sigmoidal with a rapid increase in concentrations producing a rapid significant effect, leading to a maximal effect. Because elimination is a slower process than absorption, the effect’s decline will also be slower: this means that efficiency remains stable during the first 5 hours, with a further progressive increase of cortisol and a loss of efficiency around 10-15 hours after intake. This confirms the need for two intakes per day, with one early in the morning and the other 12 hours later in the evening. In addition, even if our simulation suggests a wide interindividual variability, we were able to determine the impact of different doses of osilodrostat on the percent decrease in plasma cortisol levels. For instance, 20 mg osilodrostat leads to an estimated 42% decrease in cortisol concentration. Interestingly, Ferrari et al.16 recently showed that patients controlled with two doses of osilodrostat for at least 1 month had the same efficacy with a single intake (combing both doses) at 4 or 7 Pm. This is quite surprising and will need to be evaluated in future studies: our preliminary model could give more precise information on this point.

Cushing’s syndrome is also characterized by a loss of circadian rhythm leading to increased comorbidities such as diabetes, hypertension, and cardiovascular disease.17,18 This is why 24 hour UFC can only be considered an imperfect marker of glucocorticoid overexposure even though it is an easy-to-use marker, as exemplified by its use in all the clinical trials performed on cortisol-lowering drugs.7,8,10,19 Predicting the efficacy of osilodrostat on plasma cortisol might be helpful to tailor the treatment as a titrating approach. Of note, some studies suggested that there might be an inpatient variability of cortisol secretion in Cushing’s syndrome,20 and this might account for a bias in our results. However, none of our patients had cyclical Cushing’s syndrome. Moreover, 12 patients in our cohort had at least two cortisol cycles (every 4 hours during the day) before starting treatment. A comparison of these two cycles using Student’s t-test showed no significant difference (P = .7), indicating no obvious spontaneous variability. Our preliminary report gives interesting insights into the maximal efficacy expected for a single dose of osilodrostat, thus defining the initial dosage needed to rapidly control hypercortisolism, as opposed to the dose currently recommended by the manufacturer (2 mg twice daily). Thus, our results could help define an optimal dose in the morning, but also in the evening, with the aim of re-establishing a circadian profile. This will, however, have to be confirmed on an interventional study focusing on comorbidities, quality of life and their potential improvements while using this PK model.

The main limitation of this proof-of-concept study is the large CI. This may be due to the relatively low number of patients and the fact that cortisol was measured every 4 hours instead of every hour, but also to the large variability in efficacy between subjects. Due to the number of patients included in the analysis, it was not possible to investigate further if a covariate, such as the gender, may explain these differences between individuals. It is important to highlight that although our model predicts cortisol levels 1 hour post intake as the most reliable predictor of future efficacy, cortisol measurements were taken every 4 hours. Thus, this finding should be confirmed in prospective studies with more frequent cortisol measurements, particularly 1 hour after osilodrostat administration. While the kinetic–pharmacodynamic approach used in this study can present with some inherent limitations, this type of approach is regularly used to define the modalities of use for a medication in a new indication. A nonlinear mixed-effects modeling allows the use of data from the routine clinical follow-up of patients. This method is thus effective and particularly well-suited for sparse data. Finally, a larger study could include closer measurements of cortisol. Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is the best method for avoiding cross-reactivity with steroid precursors and could be used for these measurements. However, we used the Elecsys Cortisol II Immunoassay, which shows <5% cross-reactivity with 11-deoxycortisol; thus, our results are credible.

In conclusion, we designed a kinetic–pharmacodynamic model to adapt osilodrostat in patients with ACTH-dependent Cushing’s syndrome. Our model shows that cortisol level 1 hour after treatment is the best indicator of future efficacy. Moreover, depending on the initial cortisol level and the goal to be achieved, different doses should be prescribed. Despite wide inter-patient variability, we believe our model provides insight into the minimal dose necessary to decrease cortisol levels and the maximal efficacy expected for a given dose. Thus, it should help physicians tailor the treatment to reach maximal efficacy in the shortest possible time. The next step will be to analyze whether this percent decrease remains stable on a long-term basis or becomes more important with time, as suggested by some clinical cases showing delayed adrenal insufficiency on stable doses of osilodrostat.21

Authors’ contributions

Cecilia Piazzola (Conceptualization [equal], Formal analysis [equal], Writing—original draft [equal]), Frederic Castinetti (Conceptualization [equal], Formal analysis [equal], Writing—review & editing [equal]), Katharina von Fabeck (Conceptualization [equal], Writing—review & editing [equal]), and Nicolas Simon (Conceptualization [equal], Methodology [equal], Supervision [equal], Validation [equal], Writing—original draft [equal], Writing—review & editing [equal])

Funding

This work received an unrestricted educational grant from Recordati Rare Diseases.

To see the references and the original article, please go here: https://academic.oup.com/ejendo/article/193/4/K11/8255719?login=false

 

Filed under: adrenal crisis, Clinical trials, Cushing's, pituitary, Treatments | Tagged: , , , | Leave a comment »

Liver impairment and medical management of Cushing Syndrome and MACS Provisionally

Posted on October 4, 2025 by MaryO

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Cushing syndrome (CS) and Mild Autonomous Cortisol Secretion syndrome (MACS) are states of endogenous hypercortisolemia, associated with multiple metabolic complications. The data on the impact of cortisol on the liver are at times inconsistent.

From one perspective, some studies proved hepatotoxic cortisol action. Elevated liver enzymes and liver steatosis are common findings in patients with newly diagnosed CS and MACS (liver steatosis prevalence: 20-66% and 25-57% respectively). As well as normocortisolemic subjects with liver steatosis/metabolic associated steatohepatitis seem to have higher cortisol concentration than the healthy population. In contrast, other studies suggest that the liver impairment prevalence in hypercortisolemic patients with so many metabolic comorbidities, would be expected to be much higher than it is reported. They postulate anti-inflammatory cortisol action as a preventive factor for liver diseases progression in subjects with CS and MACS. The data on the hepatic safety profile of hypercortisolemia pharmacotherapy at times seems to be conflicting.

Antihypercortisolemic medical therapy potentially can cause liver impairment; therefore, implementing the treatment of hypercortisolemia is often challenging in patients with liver dysfunction.

We present two CS cases with baseline liver impairment, which improved on the treatment with steroidogenesis inhibitors. The case reports are followed by literature review regarding liver dysfunction in endogenous hypercortisolemia, impact of hypothalamic-pituitary- adrenal axis on the liver, and liver safety profile of medical treatment used in endogenous hypercortisolemia.

Keywords: cushing, MACs, Liver steatosis, liver fibrosis, Steroidogenesis inhibitors, Osilodrostat, Metyrapone, hypercortisolemia

From https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2025.1660316/abstract

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Predictors of Cancer in Patients With Endogenous Cushing’s Syndrome

Posted on July 21, 2025 by MaryO

We previously reported an increase in overall cancer risk in patients with endogenous Cushing’s syndrome (CS), mainly during the 10-year period following CS diagnosis.

To identify predictors of cancer in patients with CS, we conducted this retrospective nationwide cohort study of patients with CS, diagnosed between 2000 and 2023 in Israel. The cohort comprised 609 patients with CS (age at diagnosis, 48.1 ± 17.2 years; 65.0% women) and 3,018 age-, sex-, socioeconomic status-, and body mass index-matched controls (1:5 ratio).

Patients were grouped according to the occurrence of any malignancy within 10-years after the diagnosis of CS. Cox proportional hazards models, with death as a competing event, were used to identify predictors of cancer development. Independent predictors of cancer development in patients with CS included age ≥60 years (HR 1.75, 95% CI 1.01–2.68), male gender (HR 1.67, 95% CI 1.04–3.05), and adrenal-origin CS (HR 1.66, 95% CI 1.01–2.73). Baseline urinary-free cortisol levels were not associated with cancer development. Patients with ≥4 CS-associated comorbidities had a higher cancer risk (HR 1.76, 95% CI 1.03–3.02; age- and sex-adjusted). The overall 10-year risk of malignancy was twice as high in patients with CS compared to matched controls, with cancer developing, on average, 5 years earlier in patients with CS (62.3 ± 15.0 vs 67.2 ± 12.3 years). Cancer-related mortality at 10-years was twice as high in deceased patients with CS, compared to deceased controls. In conclusion, age ≥60 years at CS diagnosis, male gender, and adrenal-origin CS are independent predictors of cancer diagnosis within 10-years of initial confirmation of CS.

 

Introduction

Prolonged cortisol exposure may promote cancer development and growth (Mayayo-Peralta et al. 2021, Khadka et al. 2023). Epidemiological research showed that extended glucocorticoids use is associated with elevated overall cancer risk (Oh & Song 2020). Recently, several studies suggested that cortisol levels increase cancer risk in patients with endogenous Cushing’s syndrome (CS). A Danish study found higher rates of cancer at the time of CS diagnosis compared to controls (Dekkers et al. 2013). A Swedish study examined comorbidity rates in patients with CS and identified a nonsignificant trend of increased cancer rates in CS compared to the general population, but was probably underpowered for this relatively rare outcome (Papakokkinou et al. 2020). Our nationwide retrospective matched-cohort study, using the Clalit Health Services (CHS) database in Israel (including 609 patients with CS and 3,018 age-, sex-, socioeconomic status- and body mass index (BMI)-matched controls), observed higher rates of all cancer types in patients with CS, with a hazard ratio (HR) of 1.78 (95% CI 1.44–2.20) (Rudman et al. 2024). Elevated cancer incidence was evident in patients with Cushing’s disease (CD) and in patients with adrenal CS. The overall cancer risk remained elevated during the first 10 years that followed CS diagnosis (Rudman et al. 2024). Similarly, a nationwide cohort study from Taiwan investigated the association between endogenous CS and cancer incidence, and reported a standardized incidence ration of 2.08 (95% CI 1.54–2.75) for cancer in patients with endogenous CS (Wu et al. 2025).
Hypercortisolemia and CS-associated comorbidities could drive malignancy development in patients with CS (Rudman et al. 2024, Wu et al. 2025). While it is known that the incidence of diabetes, obesity and insulin resistance is higher in patients with CS than that of the general population (Pivonello et al. 2016, Fleseriu et al. 2021, Reincke & Fleseriu 2023) – all of which are linked to cancer development (Renehan et al. 2008, Ling et al. 2020) – it remains unclear whether these comorbidities specifically contribute to the risk of malignancy within the CS population.
Thus, the aims of the present study were to identify the baseline predictors of cancer development in CS and to test the hypothesis that cumulative cortisol exposure, measured by urinary-free cortisol (UFC), predicts cancer risk in patients with CS.

Methods

Study design and data collection

We conducted a retrospective matched-cohort study using the electronic health record database of Clalit Health Services (CHS), the largest health maintenance organization (HMO) in Israel with over 4.8 million members. The CHS database includes demographic and clinical data, hospital and outpatient clinic diagnoses, medication dispensation, and all laboratory test results conducted at the HMO’s laboratories. All diagnoses and respective dates were identified using the International Classification of Diseases, tenth revision (ICD-10) codes (Supplementary Table S1 (see section on Supplementary materials given at the end of the article)). Weight and height data, and smoking status, were recorded regularly during visits to primary care clinics and in some specialized clinics. 24 h UFC results were collected and the normal reference range for each kit used. As these tests were performed by several different laboratories and devices (in all cases the bioanalytical method used was an immunoassay test), the results were reported as multiples of the upper limit of normal (×ULN). Data were extracted using the CHS research data-sharing platform, powered by MDClone. Importantly, the diagnoses of chronic medical conditions, recorded at the time of CS diagnosis, were validated: any member of CHS who required chronic treatment for a medical condition (e.g., medication for hypertension or diabetes) could only receive his prescriptions if the primary physician has registered the diagnosis, coded according to the ICD-10, in the computerized system. Mortality data were collected from the hospital’s mortality database, which is updated from the Ministry of Interior’s population registry. Data on cancer-specific mortality were obtained from hospital discharge certificates at the time of the hospitalization that ultimately resulted in the patient’s death. The study protocol, including detailed data collection methods, has been previously published (Rudman et al. 2024).

Ethical approval

The study was approved by the institutional ethics review board of Rabin Medical Center. As data were collected anonymously and in a retrospective manner, a waiver of informed consent was granted.

Patients and outcome measures

The methods we used for patient selection and matched controls selection have been previously published (Rudman et al. 2024), as the current study is based on the same group of patients with CS and controls. After the initial screening, potential cases with ICD-10 diagnosis of CS had to fulfill at least one of the following criteria: i) 24 h UFC ≥4 ×ULN, ii) 24 h UFC ≥3 ×ULN and surgical intervention to remove a pituitary or adrenal adenoma, and iii) 24 h UFC ≥2 ×ULN and metyrapone, ketoconazole, osilodrostat, cabergoline, or pasireotide treatment. All patients with CS and non-suppressed adrenocorticotropic hormone (ACTH) levels who did not receive pituitary-directed therapy and were diagnosed with a malignancy possibly causative of ectopic CS, including small-cell lung carcinoma, bronchial and thymic carcinoids, medullary thyroid carcinoma, neuroendocrine tumors or pheochromocytoma, were suspected of ectopic CS and were excluded from this study (Rudman et al. 2024). Patients diagnosed with adrenocortical carcinoma before or within 5 years of CS diagnosis were excluded.
All identified cases were individually matched in a 1:5 ratio with age-, sex-, socioeconomic status-, and BMI-matched controls from the general population (CHS members who have never been tested for suspected hypercortisolism). The age of the individually matched controls matched the age of cases ±12 months.
The follow-up period began at the time of CS diagnosis for all cases (newly diagnosed patients with CS) and at the exact same day for each individually matched control. It continued until death, termination of CHS membership, or until the date of data collection (June 30, 2023).
The main outcome measure was the first diagnosis of any malignancy following CS diagnosis, excluding non-melanoma skin cancer. Recurrences of known malignancies were also excluded.

Statistical analysis

The statistical analysis was generated using the SAS Software, Version 9.4, SAS Institute Inc., Cary, NC, USA. Continuous variables were presented by the mean ± standard deviation or median (interquartile range (IQR)). Categorical variables were presented by (n, %). Normality of continuous variables was assessed using the Kolmogorov–Smirnov test. The t-test, Mann–Whitney test, and chi-square test were used for comparison of normally distributed, non-normal, and categorical variables, respectively. The Cox proportional hazard model, with death without malignancy treated as a competing risk, was used to calculate both univariate and multivariate HR; the Fine and Gray methodology for dealing with competing risks was used, both in the cumulative incidence plots and in HR calculations. Baseline variables found to be associated with malignancy in the univariate analysis (with a between-group P-value below 0.05) were incorporated into the multivariate model. The appropriateness of the proportional hazard assumption was assessed visually. Two-sided P-values less than 0.05 were considered statistically significant.

Results

Patient characteristics

From January 1, 2000, to June 30, 2023, a total of 609 patients with CS met the study inclusion criteria (65.0% women, mean age at CS diagnosis of 48.1 ± 17.2 years). All cases of CS were matched with up to five controls based on age, sex, socioeconomic status, and BMI, and amounted to a total of 3,018 controls. Baseline characteristics of all 609 patients and 3,018 controls, with subdivisions according to disease source, are shown in Table 1.

Table 1. Baseline characteristics (at diagnosis/time 0) of patients with Cushing’s syndrome (CS) and matched control of all patients with CS, Cushing’s disease (CD), and adrenal CS.

Baseline characteristics, all patients with CS CS (n = 609) Matched controls (n = 3,018) P value CD (n = 251) Matched controls (n = 1,246) P value Adrenal CS (n = 200) Matched controls (n = 991) P value
Age, years, mean (SD) 48.1 (17.2) 47.9 (17.2) 45.7 (17.8) 45.7 (17.8) 51.1 (16.6) 51.0 (16.6)
Sex, no. (%)
 Females 396 (65.0) 1,975 (65.4) 164 (65.3) 818 (65.6) 137 (68.5) 684 (69.0)
 Males 213 (35.0) 1,043 (34.6) 87 (34.7) 428 (34.4) 63 (31.5) 307 (31.0)
Socioeconomic status, no. (%)a
 Low 74 (12.8) 371 (13.0) 34 (14.2) 172 (14.5) 20 (10.5) 99 (10.4)
 Middle 349 (60.6) 1,719 (60.3) 145 (60.7) 713 (60.2) 119 (62.6) 594 (62.9)
 High 153 (26.6) 760 (26.7) 60 (25.1) 300 (25.3) 51 (26.9) 252 (26.7)
Body mass index, Kg/m2, mean (SD)b 30.9 (7.6) 30.0 (6.9) 30.2 (7.4) 29.6 (6.8) 30.8 (7.1) 30.3 (6.3)
Source of hypercortisolism, no. (%)
 Cushing’s disease 251 (41.2)
 Adrenal Cushing’s syndrome 200 (32.8)
 Indeterminatec 158 (25.9)
Smoking status, no. (%)d 0.35 0.77 0.18
 Non-smoker 198 (59.8) 910 (62.6) 87 (64.0) 387 (65.3) 61 (53.0) 327 (60.1)
 Smoker/former smoker 133 (40.2) 544 (37.4) 49 (36.0) 206 (34.7) 54 (47.0) 217 (39.9)
Comorbidities, no. (%)
 Diabetes mellitus 140 (23.0) 396 (13.1) <0.01 55 (21.9) 148 (11.9) <0.01 51 (25.5) 158 (15.9) <0.01
 Hypertension 343 (56.3) 957 (31.7) <0.01 129 (51.4) 338 (27.1) <0.01 129 (64.5) 387 (39.0) <0.01
 Dyslipidemia 258 (42.4) 874 (29.0) <0.01 97 (38.6) 305 (24.5) <0.01 97 (48.5) 339 (34.2) <0.01
 Ischemic heart disease 70 (11.5) 191 (6.3) <0.01 23 (9.2) 67 (5.4) 0.03 25 (12.5) 77 (7.8) 0.04
 Cerebrovascular disease 27 (4.4) 82 (2.7) 0.04 12 (4.8) 35 (2.8) 0.11 10 (5.0) 32 (3.2) 0.21
 Osteoporosis 75 (12.3) 187 (6.2) <0.01 26 (10.4) 57 (4.6) <0.01 28 (14.0) 82 (8.3) 0.02
 Malignancy before CS diagnosis 50 (8.2) 117 (3.9) <0.01 15 (6.0) 48 (3.9) 0.12 20 (10.0) 50 (5.0) 0.01
Cases and controls were individually matched for age, sex, socioeconomic status, and body mass index.
a
Cushing’s syndrome n = 576, controls n = 2,850; Cushing’s disease n = 239, controls n = 1,185; adrenal Cushing’s syndrome n = 190, controls n = 945.
b
Cushing’s syndrome n = 363, controls n = 1,549; Cushing’s disease n = 152, controls n = 644; adrenal Cushing’s syndrome n = 131, controls n = 570.
c
Ectopic ACTH secretion and adrenocortical carcinoma were excluded.
d
Cushing’s syndrome n = 331, controls n = 1,454; Cushing’s disease n = 136, controls n = 593; adrenal Cushing’s syndrome n = 115, controls n = 544.
At baseline, diabetes mellitus, hypertension, dyslipidemia, ischemic heart disease, and osteoporosis were more common among patients with CS (P < 0.01). Smoking rates were similar between the two groups (Table 1). A prior history of malignancy was more prevalent among patients with CS than controls (8.2 vs 3.9%, respectively; P < 0.01) (Table 1).

Predictors of new malignancy in patients with Cushing’s syndrome

Table 2 presents the baseline characteristics of 609 patients with CS, including demographic data, CS etiology, history of malignancy before CS diagnosis, maximal UFC at diagnosis, and CS-associated comorbidities. In a univariate time-to-event analysis of the 10-year cumulative cancer risk, accounting for death as a competing event, we found that age ≥60 years at CS diagnosis, male gender, adrenal-origin CS, hypertension, dyslipidemia, and ischemic heart disease at baseline were all associated with a higher cancer risk. The 10-year cumulative cancer risk, with death as a competing event, stratified by age, sex, and CS etiology is shown in Fig. 1. Prior malignancy, diabetes, and obesity were not associated with an increased risk of malignancy in patients with CS (Table 2). The cohort was divided into three groups based on baseline UFC level (below 5 ×ULN, 5–10 ×ULN, and above 10 ×ULN) with comparison of time to cancer occurrence. Higher UFC levels at the time of CS diagnosis were not associated with cancer development (Table 2 and Fig. 2). In a multivariable Cox regression model (multivariable model 1, Table 2), we found that age ≥60 years at CS diagnosis (HR 1.75, 95% CI 1.01–2.68), male gender (HR 1.67, 95% CI 1.04–3.05), and adrenal-origin CS (HR 1.66, 95% CI 1.01–2.73) were independent predictors of cancer development within 10 years after CS diagnosis. In an additional model (multivariable model 2, Table 2), we observed that patients with ≥4 CS-associated comorbidities at the time of CS diagnosis had a higher risk of cancer (HR 1.76, 95% CI 1.03–3.02), after adjustment for age and sex.

Table 2. Univariate analysis and multivariable regression models for the 10-year cumulative cancer risk in patients with Cushing’s syndrome, accounting for death as a competing event.

Baseline characteristics Patients (n = 609) Incident cases of cancer (n = 81) Deaths without cancer (n = 40) Univariate analysis Multivariable model 1* Multivariable model 2 (total no. of CS-associated comorbidities, with age and sex adjustment)
Age <60 years (ref) 444 44 10 – – –
Age ≥60 years 165 37 30 2.47 (1.60–3.82) 1.75 (1.01–2.68) 3.18 (2.09–4.86)
Female (ref) 396 42 23 – – –
Male 213 39 17 1.75 (1.13–2.70) 1.67 (1.04–3.05) 1.60 (1.11–2.29)
Low SESa 74 13 5 1.29 (0.65–2.56)
Medium SESa 349 42 21 0.87 (0.52–1.45)
High SES (ref)a 153 22 13 –
Cushing’s disease (ref)b 251 27 21 – –
Adrenal CSb 200 39 8 1.87 (1.14–3.05) 1.66 (1.01–2.73)
Non-smoker (ref)c 198 25 12 –
Smoker/former smokerc 133 21 12 1.25 (0.70–2.23)
Prior malignancy 50 6 14 0.91 (0.40–2.08)
No prior malignancy (ref) 559 75 26 –
Maximal urinary free cortisold
 <5 × ULN (ref) 231 38 18 –
 5–10 × ULN 135 18 7 0.86 (0.49–1.48)
 ≥10 × ULN 70 10 4 0.89 (0.45–1.78)
CS-associated comorbidities
 Obesitye 176 28 17 1.22 (0.71–2.11)
 No obesity (ref)e 187 24 12 –
 Diabetes mellitus 140 21 14 1.28 (0.78–2.10)
 No diabetes mellitus (ref) 469 60 26 –
 Hypertension 343 59 34 2.23 (1.36–3.65) 1.52 (0.83–2.81)
 No hypertension (ref) 266 22 6 – –
 Dyslipidemia 258 44 29 1.81 (1.17–2.81) 0.97 (0.55–1.72)
 No dyslipidemia (ref) 351 37 11 – –
 Ischemic heart disease 70 19 11 2.70 (1.62–4.51) 1.48 (0.81–2.71)
 No ischemic heart disease (ref) 539 62 29 –
 Stroke 27 3 2 1.07 (0.33–3.49)
 No stroke (ref) 582 78 38 –
 Osteoporosis 75 9 9 0.92 (0.46–1.84)
 No osteoporosis (ref) 534 72 31 –
Total no. of CS-associated comorbiditiesf
 0–1 (ref) 295 27 9 – –
 2–3 205 33 15 2.09 (1.36–3.22) 1.40 (0.87–2.26)
 ≥4 109 21 16 3.76 (2.37–5.97) 1.76 (1.03–3.02)
CS, Cushing’s syndrome; SES, socioeconomic status; ULN, upper limit of normal. Bold indicates statistical significance.
*
Included variables: age, sex, source of hypercortisolism, hypertension, dyslipidemia, and ischemic heart disease.
a
n = 576.
b
Ectopic ACTH secretion and adrenocortical carcinoma were excluded.
c
n = 331.
d
Maximal value of urinary-free cortisol divided by the upper limit of normal of the specific assay, n = 436.
e
n = 363.
f
CS-associated comorbidities include obesity, diabetes mellitus, hypertension, dyslipidemia, ischemic heart disease, and osteoporosis.
Figure 1

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Figure 1. The 10-year cumulative cancer risk, with death as a competing event, among patients with Cushing’s syndrome, according to age at diagnosis (A), sex (B), and Cushing’s syndrome etiology (C). CD, Cushing’s disease; CS, Cushing’s syndrome. A full colour version of this figure is available at https://doi.org/10.1530/ERC-25-0059.

Figure 2

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Figure 2. The 10-year cumulative cancer risk, with death as a competing event, among patients with Cushing’s syndrome, according to the maximal value of UFC divided by the upper limit of normal (ULN) of the specific assay used: UFC <5 × ULN (reference), 5–10 × ULN, and ≥10 × ULN. A full colour version of this figure is available at https://doi.org/10.1530/ERC-25-0059.

Univariate analysis and multivariable regression models for the 10-year cumulative cancer risk in patients with CD and adrenal CS are presented in Tables 3 and 4. In the univariate time-to-event analysis of 251 patients with CD, age ≥60 years at CS diagnosis and the presence of dyslipidemia and ischemic heart disease at baseline were associated with higher cancer risk. The multivariable Cox regression model did not identify any significant predicting factors in patients with CD. Tables 3 and 4 also present the univariate analysis for the 10-year cumulative cancer risk in 200 patients with adrenal CS, which showed that age ≥60 years, male gender, and ischemic heart disease were associated with cancer development. In the multivariable model, only age ≥60 years at CS diagnosis (HR 2.66, 95% CI 1.36–5.18) was found to be independently associated with cancer development in patients with adrenal CS (Table 4). UFC levels at the time of CS diagnosis were not associated with new cancer diagnosis in either patients with CD or with adrenal CS (Tables 3 and 4).

Table 3. Univariate analysis and multivariable regression models for the 10-year cumulative cancer risk in patients with Cushing’s disease, accounting for death as a competing event.

Cushing’s disease baseline characteristics Patients (n = 251) Incident cases of cancer (n = 27) Deaths without cancer (n = 21) Univariable Multivariable model 1 Multivariable model 2 (total no. of CS-associated comorbidities, with age and sex adjustment)
Age <60 years (ref) 196 16 8 – – –
Age ≥60 years 55 11 13 2.72 (1.27–5.81) 1.83 (0.65–5.18) 3.54 (1.81–6.92)
Female (ref) 164 14 14 – – –
Male 87 13 7 1.79 (0.85–3.80) 1.61 (0.73–3.56) 1.22 (0.68–2.18)
Low SESa 34 5 5 1.29 (0.42–3.99)
Medium SESa 145 13 12 0.81 (0.32–2.00)
High SES (ref)a 60 7 4 –
Non-smoker (ref)b 87 6 6 –
Smoker/former smokerb 49 8 8 2.59 (0.91–7.39)
Prior malignancy 15 26 15 0.66 (0.09–5.13)
No prior malignancy (ref) 236 1 6 –
Maximal urinary-free cortisolc
 <5 × ULN (ref) 133 15 14 –
 5–10 × ULN 70 6 3 0.78 (0.31–2.00)
 ≥10 × ULN 40 6 4 1.48 (0.57–3.79)
CS-associated comorbidities
 Obesityd 69 7 10 0.80 (0.31–2.09)
 No obesity (ref)d 83 10 6 –
 Diabetes mellitus 55 5 6 0.89 (0.34–2.35)
 No diabetes mellitus (ref) 196 22 15 –
 Hypertension 129 17 17 1.67 (0.76–3.64)
 No hypertension (ref) 122 10 4 –
 Dyslipidemia 97 15 13 2.31 (1.08–4.96) 1.64 (0.58–4.61)
 No dyslipidemia (ref) 154 12 8 – –
 Ischemic heart disease 23 5 4 2.71 (1.03–7.08) 1.29 (0.43–3.86)
 No ischemic heart disease (ref) 228 22 17 – –
 Stroke 12 2 1 2.34 (0.53–10.30)
 No stroke (ref) 239 25 20 –
 Osteoporosis 26 24 15 1.14 (0.35–3.66)
 No osteoporosis (ref) 225 3 6 –
Total no. of CS-associated comorbiditiese
 0–1 (ref) 136 11 6 – –
 2–3 74 10 8 2.19 (1.13–4.26) 1.48 (0.72–3.04)
 ≥4 41 6 7 3.69 (1.78–7.66) 1.72 (0.73–4.02)
CS, Cushing’s syndrome; SES, socioeconomic status; ULN, upper limit of normal. Bold indicates statistical significance.
a
n = 239.
b
n = 136.
c
Maximal value of urinary free cortisol divided by the upper limit of normal of the specific assay; n = 243.
d
Cushing’s disease, n = 152.
e
CS-associated comorbidities include obesity, diabetes mellitus, hypertension, dyslipidemia, ischemic heart disease, and osteoporosis.

Table 4. Univariate analysis and multivariable regression models for the 10-year cumulative cancer risk in patients with adrenal Cushing’s syndrome, accounting for death as a competing event.

Adrenal Cushing’s syndrome baseline characteristics Patients with CS at risk (n = 200) Incident cases of cancer (n = 39) Deaths without cancer (n = 8) Univariable Multivariable model 1 Multivariable model 2 (total no. of CS-associated comorbidities, with age and sex adjustment)
Age <60 years (ref) 134 20 1 – – –
Age ≥60 years 66 19 7 2.12 (1.13–3.96) 2.66 (1.36–5.18) 2.70 (1.35–5.42)
Female (ref) 137 17 3 – – –
Male 63 22 5 2.97 (1.58–5.58) 1.81 (0.94–3.51) 3.11 (1.73–5.57)
Low SESa 20 3 0 0.62 (0.17–2.28)
Medium SESa 119 22 3 0.73 (0.36–1.44)
High SES (ref)a 51 13 5 –
Non-smoker (ref)b 61 12 3 –
Smoker/former smokerb 54 10 2 0.86 (0.38–1.99)
Prior malignancy 20 4 2 1.03 (0.38–2.81)
No prior malignancy (ref) 180 35 6 –
Maximal urinary free cortisolc
 <5 × ULN (ref) 98 23 4 –
 5–10 × ULN 65 12 4 0.84 (0.42–1.69)
 ≥10 × ULN 30 4 0 0.53 (0.18–1.52)
CS-associated comorbidities
 Obesityd 64 15 4 1.68 (0.75–3.74)
 No obesity (ref)d 67 10 3 –
 Diabetes mellitus 51 12 3 1.47 (0.75–2.89)
 No diabetes mellitus (ref) 149 27 5 –
 Hypertension 129 29 7 1.73 (0.84–3.58)
 No hypertension (ref) 71 10 1 –
 Dyslipidemia 97 20 7 1.20 (0.65–2.25)
 No dyslipidemia (ref) 103 19 1 –
 Ischemic heart disease 25 10 4 2.65 (1.31–5.34) 1.51 (0.68–3.32)
 No ischemic heart disease (ref) 175 29 4 – –
 Stroke 10 1 1 0.58 (0.08–4.35)
 No stroke (ref) 190 38 7 –
 Osteoporosis 28 2 2 0.32 (0.08–1.33)
 No osteoporosis (ref) 172 37 6 –
Total no. of CS-associated comorbiditiese
 0–1 (ref) 82 14 1 – –
 2–3 76 15 2 1.24 (0.62–2.48) 0.95 (0.44–2.02)
 ≥4 42 10 5 2.46 (1.20–5.05) 1.21 (0.51–2.85)
CS, Cushing’s syndrome; SES, socioeconomic status; ULN, upper limit of normal. Bold indicates statistical significance.
a
n = 190.
b
n = 115.
c
Maximal value of urinary-free cortisol divided by the upper limit of normal of the specific assay; n = 193.
d
n = 131.
e
CS-associated comorbidities include obesity, diabetes mellitus, hypertension, dyslipidemia, ischemic heart disease, and osteoporosis.

The 10-year cancer risk in patients with Cushing’s syndrome vs controls

In the 10 years following CS diagnosis, 81 (13.3%) patients with CS were diagnosed with cancer and 40 (6.6%) died without malignancy, compared with 206 (6.8%) and 152 (5.0%) controls, respectively. Similar to the previously reported risk for the entire follow-up period (Rudman et al. 2024), the overall 10-year risk of malignancy, calculated with death as a competing event, was twice as high in patients with CS than in matched controls (HR 2.01; 95% CI, 1.55–2.60) (Supplementary Fig. S1).
The mean age of cancer development in patients with CS was 62.3 ± 15.0 years, compared with 67.2 ± 12.3 years in controls (P < 0.01). The risk of cancer across different subgroups (patients with CS vs controls) is shown in Fig. 3 and Table 5. The number of cases for each type of cancer in patients with CS and controls is shown in Supplementary Table S2.
Figure 3

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Figure 3. The 10-year cancer risk in subgroups of the entire cohort (cases vs matched controls). Cases and controls were individually matched for age, sex, socioeconomic status, and body mass index.

Table 5. The 10-year cancer risk in subgroups of the entire cohort (cases vs matched controls).

Subgroup Cushing’s syndrome Individually matched controls HR 95% CI
Patients Incident cases of cancer Deaths Patients Incident cases of cancer Deaths
Age
 <60 444 44 10 2,200 84 30 2.67 1.85–3.85
 ≥60 165 37 30 818 122 122 1.55 1.08–2.24
Sex
 Females 396 42 23 1,975 117 89 1.83 1.29–2.61
 Males 213 39 17 1,043 89 63 2.25 1.54–3.28
Socioeconomic status
 Low 74 13 5 371 14 17 5.03 2.37–10.68
 Middle 349 42 21 1,719 116 90 1.83 1.28–2.60
 High 153 22 13 760 73 36 1.52 0.94–2.45
Smoking status
 Smoker/former smoker 133 21 12 544 46 34 1.84 1.09–3.10
 Non-smoker 198 25 12 910 66 48 1.79 1.13–2.83
Comorbidities
 Obesity 176 28 17 698 45 62 2.52 1.57–4.04
 No obesity 187 24 12 851 70 46 1.58 0.99–2.51
 Diabetes mellitus 140 21 14 396 45 75 1.35 0.80–2.25
 No diabetes mellitus 469 60 26 2,622 161 77 2.13 1.58–2.86
 Hypertension 343 59 34 957 106 126 1.59 1.16–2.19
 No hypertension 266 22 6 2,061 100 26 1.71 1.07–2.72
 Dyslipidemia 258 44 29 874 100 100 1.53 1.07–2.17
 No dyslipidemia 351 37 11 2,144 106 52 2.15 1.47–3.13
 Ischemic heart disease 70 19 11 191 30 49 1.89 1.06–3.35
 No ischemic heart disease 539 62 29 2,827 176 103 1.88 1.41–2.52
 Stroke 27 3 2 82 7 17 1.50 0.39–5.74
 No stroke 582 78 38 2,936 199 135 2.02 1.56–2.63
 Osteoporosis 75 9 9 187 23 32 0.98 0.45–2.10
 No osteoporosis 534 72 31 2,831 183 120 2.15 1.64–2.83
Cases and controls were individually matched for age, sex, socioeconomic status, and body mass index.
Among 487 cases and 2,411 controls with an attainable follow-up period of at least 10 years, 52 patients with CS and 184 controls died (from any cause) during the 10 years that followed CS diagnosis. Eight (15.4%) patients with CS died due to malignancy, compared with 12 (6.5%) patients in the control group (P = 0.04).
During the 10-year follow-up after CS diagnosis, 27 out of 251 patients with CD (10.8%) were diagnosed with malignancy, compared to 71 (5.7%) controls. Among 200 patients with adrenal CS, 39 (19.5%) were diagnosed with cancer, compared to 79 (8.0%) controls. The 10-year risk of overall malignancy was higher in patients with CD (HR 1.92, 95% CI 1.23–3.00) and in patients with adrenal CS (HR 2.63, 95% CI 1.79–3.87), compared to controls (Supplementary Fig. S1). The number of cases for each specific cancer type in patients with CD and adrenal CS and their individually matched controls is elaborated in Supplementary Table S2.

Sensitivity analyses

Due to possible bias in individuals with a genetic predisposition to cancer, and in patients at increased risk due to prior cancer treatment, we excluded all patients with prior history of cancer (50 cases and 117 controls). Following this exclusion, patients with CS still exhibited a higher 10-year cancer risk (HR 2.12, 95% CI 1.62–2.77).
Patients with adrenal cancer diagnosed before or within 5 years of CS diagnosis were excluded from the study. However, as it is possible that adrenal cancer was either not recorded properly or unrecognized at the time of CS diagnosis, we performed an analysis of the risk of malignancy excluding all adrenal cancer cases and found no change in the 10-year risk of overall cancer (HR 1.92, 95% CI 1.48–2.50).
The diagnosis of CS patients in the study included an ICD-10 coding of the diagnosis and laboratory evidence of hypercortisolism (and test date) in all cases. However, because in many cases the diagnostic and treatment process are lengthy, there is a possibility of information bias caused by patients included in the database who were diagnosed before the time period included in the study. Therefore, we performed a sensitivity analysis excluding the first year of the study, without any change in the 10-year risk of malignancy among CS patients (HR 1.98, 95% CI 1.51–2.58).

Discussion

Patients with CS have higher morbidity and mortality (Gadelha et al. 2023, Loughrey et al. 2024), and it has been recently established that CS is associated with an increased cancer risk (Rudman et al. 2024, Wu et al. 2025). However, predictors of a new cancer diagnosis have not been studied. In this nationwide retrospective study, the 10-year cancer risk in 609 patients with CS was twice as high as in 3,018 matched controls. Importantly, the 10-year risk was notably higher in patients with CD (HR 1.92, 95% CI 1.23–3.00) and in those with adrenal CS (HR 2.63, 95% CI 1.79–3.87), compared to controls. Furthermore, the risk of cancer was higher in patients with CS, regardless of age and sex. On average, cancer development in patients with CS occurred at an age that was 5 years younger than that of controls who developed cancer (62.3 ± 15.0 vs 67.2 ± 12.3 years, respectively).
Our study is the first to identify predictors of new cancer diagnosis in patients with CS. A multivariate regression model showed that age ≥60 years at CS diagnosis (HR 1.75, 95% CI 1.01–2.68), male gender (HR 1.67, 95% CI 1.04–3.05), and adrenal-origin CS (HR 1.66, 95% CI 1.01–2.73) were identified as independent predictors of cancer development within 10 years. In addition, we found that patients with ≥4 CS-associated comorbidities at the time of CS diagnosis had an increased risk of cancer (HR 1.76, 95% CI 1.03–3.02; adjusted for age and sex). Interestingly, diabetes and obesity were not associated with malignancy development in patients with CS. Importantly, we found no association between UFC levels at the time of CS diagnosis and cancer development rates.
CS most commonly affects young women, a population not inherently at high risk for malignancy, with the exception of breast cancer (National Cancer Institute, Surveillance, Epidemiology, and End Results (SEER) Program, December 2024. https://seer.cancer.gov/statfacts/html/aya.html). Our study demonstrates that young patients and female patients with CS are at an increased risk of cancer, as compared with matched controls from the general population. However, within the group of patients with CS, we found age and sex disparities in malignancy risk: men and elderly patients (over 60 years of age) showed a higher cancer risk (Table 2). Advanced age is a universal risk factor for cancer (Campisi 2013), and patients with CS are no exception. Previous studies found that male patients with CS are more susceptible to metabolic derangements than female patients (Liu et al. 2015, Broersen et al. 2019), a difference that likely results from gender disparity in response to glucocorticoid receptor activation (Bourke et al. 2012).
In addition, our study found that CS of adrenal origin is associated with a higher risk of malignancy, as compared with CD, after adjustment for age, sex, and significant CS-related comorbidities. Notably, patients with a history of adrenal cancer or ectopic CS were excluded. This finding is difficult to explain, since most studies have found that patients with CD present with higher UFC levels (Berr et al. 2015, Rubinstein et al. 2019, Schernthaner-Reiter et al. 2019) and a longer delay in diagnosis (Rubinstein et al. 2019, Schernthaner-Reiter et al. 2019) compared to those with adrenal CS. One potential explanation for this observation is that adrenal adenomas may be linked to a higher incidence of malignancy, as studies have shown that cancer mortality is increased with autonomic cortisol secretion, with malignancy being the most common cause of death in patients with mild autonomous cortisol secretion (Patrova et al. 2017, Deutschbein et al. 2022). Another conceivable explanation stems from previous research that reported higher rates of non-adrenal malignancies in patients with bilateral adrenal tumors and autonomous cortisol secretion (Kawate et al. 2014), suggesting a possible genetic predisposition in patients with adrenal adenoma that may contribute to the development of overall cancer.
Interestingly, in our study, patients with adrenal CS had a history of malignancy at a higher rate than their individually matched controls at the time of CS diagnosis (Table 1). In contrast, no difference in the rate of malignancy was found between patients with CD and controls. Although it is possible that a prior history of malignancy contributed to the higher risk of cancer observed in patients with adrenal CS, we did not find that a prior malignancy predicted subsequent cancer risk in this population when we analyzed our cohort of patients with adrenal CS (Table 4).
In this study, we found no association between the cumulative exposure to excess glucocorticoids (measured as UFC levels) and the development of malignancy (Fig. 2), but we did identify an association between the total number of CS-related comorbidities and cancer risk (adjusted for age and sex) (Table 2). Previous studies have similarly shown no correlation between the degree of hypercortisolism and the presence of CS-related comorbidities in patients with CS (Schernthaner-Reiter et al. 2019), including diabetes and obesity (Giordano et al. 2014, Bavaresco et al. 2024). Those findings support the hypothesis that individual sensitivity to glucocorticoids varies across tissues, such that UFC levels do not always correlate with symptom burden or comorbidities. Patients who are more sensitive to excess cortisol may experience a broader range of CS-associated comorbidities. Several genetic mutations and alterations have already been identified as causes of variation in cortisol sensitivity, including the genes encoding the human glucocorticoid receptor (NR3C1) (Chrousos et al. 1982, Riebold et al. 2015, Laulhé et al. 2024), the chaperone protein that regulates proper folding of the glucocorticoid receptor (HSP90) (Riebold et al. 2015), and the nuclear protein that modulates glucocorticoid receptor actions (NR2C2) (Zhang et al. 2016). In addition, mutations in glucocorticoid response elements (Vandevyver et al. 2013), variations in RNA-binding to the glucocorticoid receptor (Lammer et al. 2023), and epigenetic changes (Paes et al. 2024) may also play a role in inter-individual differences in response to cortisol excess.
In the univariate model we have performed, the total number of CS-related comorbidities was associated with cancer development, and the risk of malignancy increased with the number of comorbidities. However, after adjustment for age and sex, the HR was significantly moderated (mainly due to a strong correlation between age and comorbidity) but remained graded. We find this observation to support the concept that cancer is a CS-associated comorbidity, and suggest that patients with CS (especially older men with adrenal CS) suffering from multiple disease-related comorbidities require closer follow-up and a rigorous age-adjusted cancer screening, in accordance with guidelines for the general population.
We have previously reported an increased risk of genitourinary, thyroid, and gynecological cancers in patients with CS (Rudman et al. 2024). A Taiwanese national cohort study reported that liver (27.7%), kidney (16.7%), and lung (13.0%) cancers were the most common cancers among patients with CS (Wu et al. 2025). Despite the small absolute number of cases in each cancer type in this study, we found that the incidence in patients with CS was higher across all cancer groups, except for malignant melanoma. One might think that patients with CS underwent more imaging and laboratory tests, and therefore more cases of low-risk cancers (e.g., clinically insignificant prostate or thyroid cancer) were diagnosed in patients with CS than in controls. However, as we have shown, the overall 10-year malignancy-associated mortality was twice as high in patients with CS compared to controls, indicating that malignancies in this group were clinically significant.
Surgery for CS, especially for CD, improves some but not all comorbidities (Dekkers et al. 2013, Terzolo et al. 2014, Papakokkinou et al. 2020, Puglisi et al. 2024). Improvement of comorbidities with medical therapy have been noted in several clinical trials (Fleseriu et al. 2012, 2022, Petersenn et al. 2017); however, there are no prospectively collected data on the risk of cancer in these patients treated long-term. A retrospective study examining the course of several CS-related comorbidities showed that the risk of cancer in patients with CS who did not achieve remission was higher compared to the risk of cancer for patients in remission, yet these analyses did not reach statistical significance, partly due to the limited sample size (Papakokkinou et al. 2020).
In order to successfully identify predictors of cancer in patients with CS, this research of an uncommon outcome (malignancy) in patients with a rare disease (CS) required a long-term follow-up of a large, population-representative cohort, paired with well-matched control group. Matching for socioeconomic status is another strength of this study, as its impact on morbidity has recently been demonstrated in several studies (Ebbehoj et al. 2022, Claudel & Verma 2024).
However, this study has limitations. Missing data prevented us from determining the specific CS etiology in some patients. Correct classification of all cases with an indeterminate diagnosis (as either CD or adrenal CS) would have allowed us to improve the power of subgroup analysis of patients with CD and adrenal CS; however, we had very strict criteria for determining the etiology of CS. Not all data regarding socioeconomic status, BMI, and smoking status were available. In addition, the impact of hypopituitarism and overreplacement of glucocorticoids in patients with CD could not be assessed.
Since the control group was drawn from the general population, ascertainment bias cannot be ruled out, as it is likely that patients with CS underwent more physician-initiated imaging and laboratory tests, and therefore more cases of cancer could have been diagnosed in patients with CS than in controls. However, we consider this bias to be unlikely for most cases of aggressive cancer, especially given our long follow-up period.
While this nationwide study includes a relatively large sample size, we acknowledge that it is likely that our current sample size was not sufficiently powered to detect risk predictors that are only modestly associated with malignancy risk. The small sample size of subgroups and the low frequency of the outcome in these subgroups meant we were unable to predict malignancy in patients with CD or adrenal CS, nor could we estimate the risk of specific malignancies. Moreover, we could not account for certain factors that may influence the risk of malignancy, such as family history of malignancy, duration of exposure to elevated cortisol levels, and the presence of genetic syndromes that predispose individuals to both CS and certain malignancies (e.g., multiple endocrine neoplasia type 1) (Hernández-Ramírez & Stratakis 2018). Finally, the lack of systematic prospective assessment of comorbidities is an important limitation and should raise the standards for future clinical care of these patients and collecting data in new registries. While patients receiving treatment for a particular comorbidity were successfully identified, those without treatment were not systemically recorded, which may have led to underreporting. Such is the case with osteoporosis: only patients who received treatment or whose treating physician decided to send them for a bone density scan were diagnosed, while others without such evaluations were assumed to be free of osteoporosis.
In conclusion, this large nationwide retrospective matched-cohort study found that the risk of cancer was consistently higher in patients with CS, regardless of age or sex, and on average, cancer development occurred 5 years earlier in patients with CS than in controls. The multivariate regression model we developed identified age ≥60 years at CS diagnosis, male gender, and CS of adrenal-origin as independent predictors of malignancy during the 10 years following CS diagnosis. Importantly, we found no association between UFC levels at CS diagnosis and cancer development rates. However, patients with ≥4 CS-associated comorbidities at CS diagnosis were more likely to develop cancer, after adjusting for age and sex. Given previous studies that identified overall cancer as a CS-related comorbidity and as one of the leading causes of death in this population, the results of the current study will help identify patients at high risk of malignancy, emphasize the importance of timely screening tests, in accordance with guidelines for the general population, and highlight the need for larger international cohorts to establish specific cancer screening recommendations for patients with CS.

Supplementary materials

This is linked to the online version of the paper at https://doi.org/10.1530/ERC-25-0059.

Declaration of interest

Yaron Rudman, Genady Drozdinsky, Hiba Masr-Iraqi, Tzippy Shochat, and Shiri Kushnir do not have any financial or personal relationships with other people or organizations to disclose. Maria Fleseriu has been a PI with research funding to the university from Crinetics and Sparrow and has received occasional scientific fees for scientific consulting and advisory boards from Crinetics, Recordati, Sparrow and Xeris. Ilan Shimon has been an investigator for Xeris Biopharma and has received occasional scientific fees for scientific consulting and advisory boards from Medison, CTS pharma, and Neopharm. Amit Akirov has received occasional scientific fees for scientific consulting and advisory boards from Medison, CTS pharma, and Neopharm.

Funding

This work did not receive any specific grant from any funding agency in the public, commercial or not-for-profit sector.

Data availability

The data that support the findings of this study are available from Clalit Health Services. Restrictions apply to the availability of these data, which were used under license for this study. Deidentified individual participant-level data sharing will be considered by the corresponding author of this study, with the permission of Clalit Health Services. All applicants will be asked to sign a data access agreement. All requests will be assessed as to whether data sharing is appropriate, based on the scientific rigor of the proposal.

References

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