Prospective Assessment of Mood and Quality of Life in Cushing Syndrome before and after Biochemical Control

Posted on November 17, 2025 by MaryO

Abstract

Context

Cushing syndrome (CS) impairs quality of life (QoL) and mood. Prospective real-life data on post-treatment recovery and predictors of improvement are limited.

Objectives

Evaluate changes in QoL, depression, and anxiety in patients with CS, before and after biochemical control, and identify predictors of clinically meaningful improvement.

Design and Setting

Prospective observational study at a tertiary center.

Patients

67 patients with endogenous CS (60 pituitary, 7 adrenal) were assessed with active disease and again after achieving biochemical control through surgery and/or medication.

Outcomes

Patient-reported outcomes included CushingQoL, Beck Depression Inventory-II (BDI-II), and State-Trait Anxiety Inventory (STAI).

Results

Mean and longest follow-up was 2.3 and 11.5 years, respectively. Treatment led to improvements in mean scores across all domains (QoL: +18.2±20.9, BDI: –6.8±8.6, STAI-State: –9.6±12.5, STAI-Trait: –8.6±12.6; all p < 0.001). However, minimal important difference was achieved in 64.6% for QoL, 67.9% for BDI, 53.2% and 52.8% for STAI subscales. After multivariable analysis, QoL improvements were predicted by lower baseline BMI, pre-treatment symptoms ❤ years, post-operative hydrocortisone replacement >6 months, and normal follow-up late-night salivary cortisol (LNSC). Depression improvements were predicted by symptoms ❤ years, normal follow-up LNSC, and surgical treatment. Anxiety improvements were predicted by younger age and >6 months post-operative hydrocortisone. Depression improved more gradually than QoL and anxiety.

Conclusions

Although effective treatment improves mood and QoL in CS, clinically meaningful recovery is variable and incomplete for some patients. Our findings highlight the need to limit diagnostic delay and provide comprehensive post-treatment care that includes normalization of cortisol circadian rhythm.

Accepted manuscripts
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© The Author(s) 2025. Published by Oxford University Press on behalf of the Endocrine Society.
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Endogenous Cushing’s Syndrome Market Insights Highlight Expanding Outlook Till 2032

Posted on November 15, 2025 by MaryO

DelveInsight’s “Endogenous Cushing’s Syndrome Market Insights, Epidemiology, and Market Forecast-2032′′ report offers an in-depth understanding of the Endogenous Cushing’s Syndrome, historical and forecasted epidemiology as well as the Endogenous Cushing’s Syndrome market trends in the United States, EU4 (Germany, Spain, Italy, France) the United Kingdom and Japan.

The latest healthcare forecast report provides an in-depth analysis of Endogenous Cushing’s Syndrome, offering comprehensive insights into the Endogenous Cushing’s Syndrome revenue trends, prevalence, and treatment landscape. The report delves into key Endogenous Cushing’s Syndrome statistics, highlighting the current and projected market size, while examining the efficacy and development of emerging Endogenous Cushing’s Syndrome therapies. Additionally, we cover the landscape of Endogenous Cushing’s Syndrome clinical trials, providing an overview of ongoing and upcoming studies that are poised to shape the future of Endogenous Cushing’s Syndrome treatment. This report is an essential resource for understanding the market dynamics and the evolving therapeutic options within the Endogenous Cushing’s Syndrome space.

To Know in detail about the Endogenous Cushing’s Syndrome market outlook, drug uptake, treatment scenario and epidemiology trends, Click here; Endogenous Cushing’s Syndrome Market Forecast
https://www.delveinsight.com/sample-request/endogenous-cushings-syndrome-market?utm_source=openpr&utm_medium=pressrelease&utm_campaign=gpr

Some of the key facts of the Endogenous Cushing’s Syndrome Market Report:
• The Endogenous Cushing’s Syndrome market size is anticipated to grow with a significant CAGR during the study period (2019-2032)
• In December 2024, Corcept Therapeutics, a US-based biotechnology company, has announced positive long-term results from its Phase III trial evaluating relacorilant as a treatment for individuals with endogenous hypercortisolism (Cushing’s syndrome).
• In October 2024, Sparrow Pharmaceuticals, a clinical-stage biopharmaceutical company focused on developing targeted therapies for unmet needs in endocrinology and immunology, announced the completion of its Phase 2 RESCUE trial evaluating clofutriben, a selective HSD-1 inhibitor, for endogenous Cushing’s syndrome. All eligible participants who completed the trial opted to continue treatment in an open-label extension (OLE) protocol. Encouraging results from the trial have accelerated plans for the next phase of development, set to begin next year. Additionally, the FDA has granted Orphan Drug Designation to clofutriben for the treatment of endogenous Cushing’s syndrome.
• Key Endogenous Cushing’s Syndrome Companies: Cortendo AB, RECORDATI GROUP, HRA Pharma, Corcept Therapeutics, and others
• Key Endogenous Cushing’s Syndrome Therapies: Levoketconazole, osilodrostat, metyrapone, CORT125134, and others
• The Endogenous Cushing’s Syndrome market is expected to surge due to the disease’s increasing prevalence and awareness during the forecast period. Furthermore, launching various multiple-stage Endogenous Cushing’s Syndrome pipeline products will significantly revolutionize the Endogenous Cushing’s Syndrome market dynamics.
• Research by Scaroni et al. (2023) indicates that Cushing syndrome occurs at an incidence rate of 1.5 per 1,000,000 individuals annually and has a prevalence of around 60 per 1,000,000 individuals in Europe. In about 80% of cases, Cushing syndrome is caused by adrenocorticotrophic hormone (ACTH) hypersecretion, resulting in ACTH-dependent Cushing syndrome.
• Cushing’s syndrome can be caused by either ACTH-dependent (80% of cases) or ACTH-independent (20% of cases) factors. The latter is primarily attributed to benign adrenal tumors (60%) or malignant tumors (40%). ACTH overproduction can either originate from the pituitary (85% of cases) or result from ectopic tumor secretion (15% of cases). The term “Cushing’s disease” is specifically used to refer to ACTH-secreting pituitary tumors.

Endogenous Cushing’s Syndrome Overview
Endogenous Cushing’s Syndrome is a rare hormonal disorder caused by the body’s overproduction of cortisol, a hormone produced by the adrenal glands. This overproduction can result from tumors or abnormalities in the pituitary gland (Cushing’s disease), adrenal glands, or other parts of the body that cause excessive cortisol secretion. It contrasts with exogenous Cushing’s syndrome, which results from external sources like long-term use of corticosteroid medications.

Get a Free sample for the Endogenous Cushing’s Syndrome Market Forecast, Size & Share Analysis Report:
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Endogenous Cushing’s Syndrome Epidemiology
The epidemiology section provides insights into the historical, current, and forecasted epidemiology trends in the seven major countries (7MM) from 2019 to 2032. It helps to recognize the causes of current and forecasted trends by exploring numerous studies and views of key opinion leaders. The epidemiology section also provides a detailed analysis of the diagnosed patient pool and future trends.

Endogenous Cushing’s Syndrome Epidemiology Segmentation:
The Endogenous Cushing’s Syndrome market report proffers epidemiological analysis for the study period 2019-2032 in the 7MM segmented into:
• Total Prevalence of Endogenous Cushing’s Syndrome
• Prevalent Cases of Endogenous Cushing’s Syndrome by severity
• Gender-specific Prevalence of Endogenous Cushing’s Syndrome
• Diagnosed Cases of Episodic and Chronic Endogenous Cushing’s Syndrome

Download the report to understand which factors are driving Endogenous Cushing’s Syndrome epidemiology trends @ Endogenous Cushing’s Syndrome Epidemiology Forecast
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Endogenous Cushing’s Syndrome Drugs Uptake and Pipeline Development Activities
The drugs uptake section focuses on the rate of uptake of the potential drugs recently launched in the Endogenous Cushing’s Syndrome market or expected to get launched during the study period. The analysis covers Endogenous Cushing’s Syndrome market uptake by drugs, patient uptake by therapies, and sales of each drug.
Moreover, the therapeutics assessment section helps understand the drugs with the most rapid uptake and the reasons behind the maximal use of the drugs. Additionally, it compares the drugs based on market share.
The report also covers the Endogenous Cushing’s Syndrome Pipeline Development Activities. It provides valuable insights about different therapeutic candidates in various stages and the key companies involved in developing targeted therapeutics. It also analyzes recent developments such as collaborations, acquisitions, mergers, licensing patent details, and other information for emerging therapies.

Endogenous Cushing’s Syndrome Therapies and Key Companies
• Levoketconazole: Cortendo AB
• osilodrostat: RECORDATI GROUP
• metyrapone: HRA Pharma
• CORT125134: Corcept Therapeutics

Discover more about therapies set to grab major Endogenous Cushing’s Syndrome market share @ Endogenous Cushing’s Syndrome Treatment Landscape
https://www.delveinsight.com/sample-request/endogenous-cushings-syndrome-market?utm_source=openpr&utm_medium=pressrelease&utm_campaign=gpr

Endogenous Cushing’s Syndrome Market Drivers
• Growing Prevalence of Endogenous Cushing’s Syndrome
• Advancements in Diagnostic Techniques
• Emerging Targeted Therapies
• Increasing Investment in Rare Disease Research
• Growing Awareness and Early Diagnosis
• Increased Focus on Orphan Drug Development

Endogenous Cushing’s Syndrome Market Barriers
• High Treatment Costs
• Limited Treatment Options
• Complexity in Diagnosis
• Side Effects of Current Treatments
• Small Patient Population
• Regulatory Challenges

Scope of the Endogenous Cushing’s Syndrome Market Report
• Study Period: 2019-2032
• Coverage: 7MM [The United States, EU5 (Germany, France, Italy, Spain, and the United Kingdom), and Japan]
• Key Endogenous Cushing’s Syndrome Companies: Cortendo AB, RECORDATI GROUP, HRA Pharma, Corcept Therapeutics, and others
• Key Endogenous Cushing’s Syndrome Therapies: Levoketconazole, osilodrostat, metyrapone, CORT125134, and others
• Endogenous Cushing’s Syndrome Therapeutic Assessment: Endogenous Cushing’s Syndrome current marketed and Endogenous Cushing’s Syndrome emerging therapies
• Endogenous Cushing’s Syndrome Market Dynamics: Endogenous Cushing’s Syndrome market drivers and Endogenous Cushing’s Syndrome market barriers
• Competitive Intelligence Analysis: SWOT analysis, PESTLE analysis, Porter’s five forces, BCG Matrix, Market entry strategies
• Endogenous Cushing’s Syndrome Unmet Needs, KOL’s views, Analyst’s views, Endogenous Cushing’s Syndrome Market Access and Reimbursement

Media Contact
Company Name: DelveInsight Business Research LLP
Contact Person: Gaurav Bora
Email: info@delveinsight.com
Contact No.: +14699457679
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Country: United States
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About DelveInsight
DelveInsight is a leading Healthcare Business Consultant, and Market Research firm focused exclusively on life sciences. It supports Pharma companies by providing comprehensive end-to-end solutions to improve their performance.
It also offers Healthcare Consulting Services, which benefits in market analysis to accelerate the business growth and overcome challenges with a practical approach.

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Clinical Efficacy and Safety of Fluconazole Treatment in Patients with Cushing’s Syndrome

Posted on November 11, 2025 by MaryO

Abstract

Background:

Ketoconazole is effective for treating Cushing’s syndrome (CS) but its use is limited by the risk of hepatotoxicity. Fluconazole, with similar antifungal properties, is being investigated as a potentially safer alternative for managing CS. This study aims to evaluate the efficacy and safety of fluconazole in patients with CS.

Methods:

This retrospective study evaluated a total of 22 patients with CS, including 12 with Cushing’s disease (CD), 3 with adrenal Cushing’s syndrome (ACS), and 7 with ectopic Adrenocorticotropic hormone (ACTH) syndrome. Fluconazole was administered orally, ranging from 112.5 to 450 mg daily, with the duration varying from 2 weeks to over 5 years. The efficacy of fluconazole was assessed by changes in 24-hour urinary free cortisol (24-h UFC) levels. Additionally, hepatic safety was assessed by monitoring changes in alanine aminotransferase (ALT) levels.

Results:

Following fluconazole treatment, 24-h UFC levels significantly decreased from 717.6 ± 1219.4 to 184.1 ± 171.8 µg/day (p = 0.035). ALT levels showed an increase from 38.5 ± 28.4 to 56.5 ± 47.8 U/L, though this change was not statistically significant (p = 0.090). ALT levels exceeding the upper limit of normal range (ULN) were observed in 12 patients (54.5%), with only 4 patients (18.2%) showing ALT levels more than three times the ULN. Out of 10 patients who received treatment for over 1 year, 5 patients (50.0%) experienced a recurrence, with 24-h UFC levels more than 1.5 times the ULN within 3 to 12 months after fluconazole treatment.

Conclusion:

Fluconazole effectively reduces hypercortisolism in patients with CS without significant liver injury, suggesting it as a viable therapeutic option for CS. While some cases have shown treatment escape, more studies are required to confirm the long-term efficacy.

Introduction

Cushing’s syndrome (CS) is a complex endocrine disorder characterized by excessive cortisol production, leading to complications such as insulin-resistant hyperglycemia, muscle weakness (proximal myopathy), osteoporosis, cardiovascular diseases, and neuropsychiatric disorders.1 The primary causes of CS include pituitary ACTH-secreting tumor (Cushing’s disease (CD), adrenal neoplasm (adrenal Cushing’s syndrome (ACS)), or nonpituitary ACTH-secreting tumor (ectopic ACTH syndrome (EAS)). The most common cause is CD. If left untreated, CS patients face a 3.8 to 5-fold increase in mortality compared to the general population.2,3 The first-line treatment for CS involves surgical removal of the offending tumor(s). In CD cases, transsphenoidal pituitary surgery achieves success rates between 65% and 90% for microadenomas. However, complete resection can be challenging, especially with macroadenomas, leading to recurrence or persistent hypercortisolism in approximately 20%–25% of patients.4 Alternative treatments include pituitary stereotactic radiosurgery, which effectively controls cortisol levels over several years but carries potential adverse effects.5,6 For EAS patients, managing hypercortisolism while awaiting definitive treatments like surgery is critical.7 Bilateral adrenalectomy offers immediate control over cortisol excess but necessitates lifelong steroid replacement therapy, impacting the quality of life.8 In addition, some corticotropic pituitary tumors may progress post-surgery, requiring further targeted interventions.9
However, some patients were not candidates for surgery due to factors such as advanced age, personal preference against surgery, or the absence of a definitive culprit lesion. When surgery fails to fully correct hypercortisolism (i.e., when 24-h UFC levels do not decrease or even progressively rise in the weeks to months following surgery, indicating persistence or relapse), pharmacotherapy can be employed to reduce cortisol overproduction and enhance clinical outcomes.10,11 In addition, it could be administered before surgical intervention to reduce perioperative complications.12,13 Various medications are used in the treatment of CS, including adrenal steroidogenesis inhibitors, dopamine agonists, somatostatin analogs, or glucocorticoid receptor antagonist.4,14
Ketoconazole, an imidazole fungicide and adrenal steroidogenesis inhibitor, has long been off-label used as the first-line medication for patients with CS who cannot undergo surgery or for whom surgery is non-curative. It reduces cortisol synthesis by inhibiting the side-chain cleavage enzymes 11β-hydroxylase and 17,20-lyase.10 Effective doses range from 200 to 1200 mg daily, but gradual dose increases may be necessary due to the potential for escape from cortisol inhibition.10,15 Ketoconazole is extensively metabolized in the liver, leading to an increased risk of hepatotoxicity.16 In 2013, the U.S. Food and Drug Administration (FDA) issued warnings about the potentially life-threatening liver toxicity associated with ketoconazole. As a result, ketoconazole is no longer available in many regions.
Fluconazole, another azole antifungal agent, has been explored as an alternative treatment for CS. It inhibits adrenal steroidogenesis through the CYP450 pathway, and the effects have been confirmed in vitro, using primary cultures of human adrenocortical tissues and two adrenocortical carcinoma cell lines. The effects were mainly observed in enzymes 11β-hydroxylase and 17α-hydroxylase, which are key in cortisol synthesis.17 Another study also demonstrated that fluconazole inhibits glucocorticoid production in vitro in the adrenal adenoma cell line Y-1.18 Case reports have also documented adrenal insufficiency in patients with severe comorbidities treated with fluconazole, suggesting its potential for managing hypercortisolism.19,20 Fluconazole is characterized by its small molecular size and low lipophilicity. It is minimally metabolized, with approximately 80% excreted unchanged in the urine.16 This contributes to its lower incidence of adverse effects, particularly liver injury. In a cohort study estimating the risk of clinical acute liver injury among users of oral antifungals (fluconazole, griseofulvin, itraconazole, ketoconazole, or terbinafine) in the general population from the General Practice Research Database in the United Kingdom, fluconazole was associated with a lower relative risk of acute liver injury compared to other agents.21
Levoketoconazole, the 2S, 4R enantiomer of ketoconazole, provides enhanced enzyme inhibition with greater therapeutic efficacy and fewer side effects compared to ketoconazole.22 The main challenge with using levoketoconazole in the treatment of CS is the limited data from Randomized controlled trials (RCTs). To date, there are only two prospective studies (SONICS and LOGICS) and one systematic review that evaluate the efficacy and safety of levoketoconazole in this context.23–25
Given that existing evidence on fluconazole treatment for CS is primarily limited to case reports, this study aims to evaluate the efficacy and safety of fluconazole in the first relatively large cohort of CS patients.

Patients and methods

Patients

This retrospective study analyzed a total of 22 patients with CS, including 12 cases of CD, 3 cases of ACS, and 7 cases of EAS. For patients who presented with Cushingoid appearance, a 1-mg overnight low-dose dexamethasone suppression test (LDDST) was performed. If the result revealed positive (>1.8 mcg/dL), further surveys were arranged. CS was diagnosed based on 24-h UFC levels (>three times the upper limit of normal range (ULN)), and 2-day LDDST (>1.8 mcg/dL). Once the biochemical diagnosis of CS was confirmed, morning plasma ACTH and cortisol levels were measured to differentiate between ACTH-dependent and ACTH-independent CS. Low ACTH levels (<5 pg/dL) accompanied by elevated cortisol concentrations (>15 mcg/dL) indicated an adrenal origin, consistent with ACTH-independent CS. In such cases, a computed tomography or magnetic resonance imaging scan was performed to evaluate for adrenal masses. If ACTH levels were greater than 5 pg/dL, ACTH-dependent CS was suspected. To identify the source of excessive ACTH secretion—either CD or EAS—further diagnostic testing was conducted, including high-dose dexamethasone suppression test (UFC suppresses >90%, or plasma cortisol suppresses > 50% from baseline, CD is most likely), or corticotropin-releasing hormone (CRH) stimulation test, or desmopressin (DDAVP) stimulation test (ACTH increases >50% and plasma cortisol increases >20% suggests CD), or inferior petrosal sinus sampling (central-to-peripheral ACTH ratio ⩾2 or ⩾3 post CRH or DDAVP suggests CD), or pituitary magnetic resonance imaging (pituitary mass >6 mm suggests CD).1,26 If the patient’s condition allowed, one or more of these tests were performed, and the final diagnosis was made based on a comprehensive interpretation of the combined results.

Methods

After the approval of the Institutional Review Board at Taipei Veterans General Hospital (IRB No. 2021-04-003CC), we conducted a retrospective study, which was waived for informed consent at Taipei Veterans General Hospital. Sample size calculations were not conducted because this was a retrospective study. We surveyed patients diagnosed with CS (CD, ACS, or EAS) who received fluconazole treatment at Taipei Veterans General Hospital in Taipei, Taiwan, between January 1st, 2015, and August 31st, 2020. Fluconazole was administered orally at doses ranging from 112.5 to 450 mg daily, with treatment durations ranging from 2 weeks to over 5 years (Fluconazole was not administered for other treatment purposes, such as infection). The inclusion criteria consisted of a confirmed diagnosis of CS (whether newly diagnosed, persistent, or recurrent) and a history of fluconazole treatment for CS. The exclusion criteria included patients who were not regularly followed up after fluconazole treatment or who lacked complete 24-h UFC data both before and after treatment with fluconazole.
The following data before initiation of treatment were collected: age, gender, body mass index (BMI), alcohol consumption, history of diabetes mellitus, history of chronic hepatitis, baseline 24-hour urinary free cortisol (24-h UFC) levels (reference range: 20–80 µg/day, measured by chemiluminescent immunoassay), morning serum cortisol, morning adrenocorticotropic hormone (ACTH) levels (measured by chemiluminescent immunoassay), and liver function index (alanine aminotransferase (ALT)). In addition, the history of surgery for pituitary tumor or ectopic lesion resection, as well as any other medical treatments apart from fluconazole, was recorded.
24-Hour UFC levels were monitored every 1 to 3 months after initiating fluconazole treatment. The average values from two 24-h UFC measurements (first and second data points within the first 4 months) were used to assess treatment efficacy. For the evaluation of hepatic safety, the maximum ALT level recorded within 6 months after starting fluconazole treatment was compared to the baseline ALT. In this study, we defined ALT levels exceeding three times the ULN as noteworthy liver injury.

Statistical analysis

Data are presented as mean ± standard deviation (SD) or as numbers (percentage), as appropriate. Due to the small sample sizes in some groups and the non-normal distribution of several variables, nonparametric statistical methods were employed to analyze the relationships between variables. Differences between groups were analyzed using the Pearson Chi-squared test, Student’s t-test, or one-way analysis of variance (ANOVA), as appropriate. A p-value less than 0.05 from the ANOVA was considered statistically significant, indicating that at least one group differed significantly from the others. All statistical analyses were performed using the SPSS software package (version 26; IBM Corporation, Armonk, NY, USA).

Results

The baseline characteristics of the patients are summarized in Table 1. No significant differences were found among the etiologies of CS in terms of age, gender, or history of diabetes (p = 0.271, p = 0.253, and p = 0.667, respectively). Cortisol (8AM), ACTH (8AM), and 24-h UFC levels were significantly higher in the EAS group (p = 0.041, p = 0.005, and p = 0.043, respectively) at diagnosis. BMI was significantly lower in the EAS group compared to the other groups (p = 0.002). Alcohol consumption and history of chronic hepatitis, both common causes of liver injury in Taiwan, showed no significant differences among the groups (p = 0.325 and p = 0.765, respectively). Regarding surgical history, eight patients (66.7%) in the CD group had undergone pituitary surgery, while no patients in the ACS group had a history of surgery. In the EAS group, two patients (28.6%) had undergone surgery: one had an anterior mediastinal tumor removal and left upper lung wedge resection, and the other had a suprasellar tumor resection (p = 0.064).
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Table 1. The baseline characteristics of patients with Cushing’s syndrome.
Characteristics All (n = 22) CD (n = 12) ACS (n = 3) EAS (n = 7) p-Value*
Age (years) 54.5 ± 15.5 49.8 ± 15.3 56.0 ± 12.5 61.9 ± 15.9 0.271
Female, n (%) 17 (77.3) 10 (83.3) 3 (100) 4 (57.1) 0.253
Body mass index (kg/m2) 25.1 ± 4.3 27.4 ± 2.8 27.2 ± 1.3 21.0 ± 3.8 0.002
Cortisol (8AM) (µg/dL) 26.7 ± 18.7 21.5 ± 8.6 14.0 ± 4.0 40.3 ± 26.1 0.041
ACTH (8AM) (pg/mL) 151.9 ± 172.1 98.0 ± 63.1 6.4 ± 0.9 306.5 ± 228.3 0.005
24-h UFC (µg/day) 760.5 ± 1387.8 277.9 ± 125.6 107.6 ± 78.2 1891.2 ± 2155.7 0.043
Alcohol consumption, n (%)a 1 (4.5) 0 (0.0) 0 (0.0) 1 (14.3) 0.325
History of diabetes, n (%) 11 (50.0) 5 (41.7) 2 (66.7) 4 (57.1) 0.667
History of chronic hepatitis, n (%) 2 (9.1) 1 (8.3) 0 (0.0) 1 (14.3) 0.765
Surgery history, n (%)b 10 (45.5) 8 (66.7) 0 (0.0) 2 (28.6) 0.064
Using other medication, n (%) 10 (45.5) 4 (33.3) 0 (0.0) 6 (85.7) 0.020
 Etomidate, n (%) 8 (36.4) 3 (25.0) 0 (0.0) 5 (71.4) 0.047
 Metyrapone, n (%) 1 (4.5) 0 (0.0) 0 (0.0) 1 (14.3) 0.325
 Pasireotide, n (%) 1 (4.5) 1 (8.3) 0 (0.0) 0 (0.0) 0.646
Data are expressed as mean ± SD or number (percentage). 24-h UFC (reference range: 20–80 µg/day)
a
Alcohol consumption was defined as men consume more than two alcoholic equivalents per day, while women consume more than one alcoholic equivalent, with one alcoholic equivalent being 10 g of alcohol.
b
Surgery for pituitary tumor or ectopic lesions.
*
p-Value <0.05 from ANOVA, indicating at least one group differed significantly from the others.
24-h UFC, 24-hour urinary free cortisol; ACS, adrenal Cushing’s syndrome; ACTH, adrenocorticotropic hormone; CD, Cushing’s disease; EAS, ectopic ACTH syndrome; SD, standard deviation.
During fluconazole treatment, significant differences were observed among the three groups concerning the use of additional medications (p = 0.020). In the CD group, three patients (25%) received etomidate and one patient (8.3%) received pasireotide. No patients in the ACS group received other medications. In the EAS group, five patients (71.4%) received etomidate, and one patient (14.3%) received metyrapone. For patients treated with etomidate, the duration was limited to a few days before switching to fluconazole. One patient received concomitant therapy with pasireotide and fluconazole.
Table 2 presents the laboratory results for hormonal parameters and ALT levels before and after fluconazole treatment. Prior to treatment, there were no statistically significant differences among the three groups in terms of serum cortisol (8AM), ACTH (8AM), 24-h UFC, and ALT levels (p = 0.739, p = 0.239, p = 0.157, and p = 0.738, respectively).
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Table 2. The laboratory exams of hormonal parameters and ALT before and after fluconazole treatment.
Variable All (n = 22) CD (n = 12) ACS (n = 3) EAS (n = 7) p-Value
Cortisol (8AM) before fluconazole (µg/dL) 18.3 ± 10.8 17.8 ± 11.6 14.8 ± 3.4 20.6 ± 12.1 0.739
ACTH (8AM) before fluconazole (pg/mL) 104.5 ± 122.2 101.9 ± 64.7 6.4 ± 0.9 150.7 ± 188.4 0.239
ACTH (8AM) after fluconazole treatment (pg/mL)a 75.7 ± 87.0 65.7 ± 44.3 6.8 ± 1.4 122.4 ± 133.4 0.020
24-h UFC before fluconazole (µg/day) 717.6 ± 1219.4 443.1 ± 391.5 139.2 ± 95.7 1436.0 ± 2000.0 0.157
24-h UFC after fluconazole (µg/day)b 184.1 ± 171.8 132.0 ± 117.3 53.3 ± 30.8 321.9 ± 198.8 0.017
Decline percentage (%) of 24-h UFC after fluconazole 39.2% ± 48.2% 50.2% ± 37.4% 55.8% ± 27.3% 13.1% ± 64.4% 0.228
Normalization of 24-h UFC after fluconazole, n (%) 6 (27.3) 4 (33.3) 2 (66.7) 0 (0.0) 0.074
24-h UFC <1.5× ULN after fluconazole, n (%) 10 (45.5) 6 (50.0) 3 (100.0) 1 (14.3) 0.040
ALT before fluconazole (U/L) 38.5 ± 28.4 42.4 ± 32.6 38.0 ± 14.1 30.8 ± 24.2 0.738
ALT after fluconazole (U/L)c 56.5 ± 47.8 76.7 ± 54.3 28.7 ± 12.7 28.8 ± 13.6 0.091
ALT >ULN after fluconazole, n (%)c 12 (54.5) 8 (66.7) 2 (66.7) 2 (28.6) 0.247
ALT >3× ULN after fluconazole, n (%)c 4 (18.2) 4 (33.3) 0 (0.0) 0 (0.0) 0.130
Data are expressed as mean ± SD or number (percentage). ALT (reference range: male: <41 U/L; female: <33 U/L). 24-h UFC (reference range: 20–80 µg/day).
a
The average of first and second ACTH after fluconazole treatment.
b
The average of first and second 24-h UFC after fluconazole treatment.
c
ALT: maximum in following 6 months.
1.
5×, 1.5 times upper limit of normal range; 3×, 3 times upper limit of normal range; 24-h UFC, 24-hour urinary free cortisol; ACS, adrenal Cushing’s syndrome; ACTH, adrenocorticotropic hormone; ALT, alanine aminotransferase; CD, Cushing’s disease; EAS, ectopic ACTH syndrome; ULN, upper limit of normal range.
Twenty-four-hour UFC levels after fluconazole treatment were monitored over the following months. The average values of the first and second 24-h UFC measurements showed significant declines compared to baseline levels as: decreased from 717.6 ± 1219.4 to 184.1 ± 171.8 µg/day in all patients (p = 0.035), decreased form 443.1 ± 391.5 to 132.0 ± 117.3 µg/day in the CD group (p = 0.009), decreased from 139.2 ± 95.7 to 53.3 ± 30.8 µg/day in the ACS group (p = 0.243), and decreased from 1436.0 ± 2000.0 to 321.9 ± 198.8 µg/day in the EAS group (p = 0.147). The percentage decline in 24-h UFC levels following treatment demonstrated a significant reduction as follows: 39.2% ± 48.2% in all patients, 50.2% ± 37.4% in the CD group, 55.8% ± 27.3% in the ACS group, and 13.1% ± 64.4% in the EAS group (p = 0.228) (Table 2 and Figure 1 illustrate these changes).
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Figure 1. 24-h UFC before and after fluconazole treatment in patients with Cushing’s syndrome.
24-h UFC, 24-hour urinary free cortisol; ACS, adrenal Cushing’s syndrome; CD, Cushing’s disease; EAS, ectopic ACTH syndrome.
Normalization of 24-h UFC levels (reference range 20–80 μg/day) was observed in six patients (27.3%) across three groups: four patients (33.3%) in the CD group, two patients (66.7%) in the ACS group, and no patients in the EAS group (p = 0.074). Additionally, 10 cases (45.5%) across 3 groups, 6 cases (50%) in the CD group, 3 cases (100%) in the ACS group, and 1 case (14.3%) in the EAS group showed 24-h UFC less than 1.5 times the ULN (p = 0.040). In this study, 10 patients (45.5%) received fluconazole treatment for more than 1 year. Among these, five patients (50.0%) experienced a recurrence of hypercortisolism, with 24-h UFC levels exceeding 1.5 times the ULN within 3–12 months after treatment with fluconazole.
For hepatic safety assessment, the maximum ALT levels within 6 months of fluconazole treatment were analyzed and are presented in Table 2. Compared to baseline levels, ALT increased from 38.5 ± 28.4 to 56.5 ± 47.8 U/L in all patients (p = 0.090), and increased from 42.4 ± 32.6 to 76.7 ± 54.3 U/L in the CD group (p = 0.047). (Table 2 and Figure 2 illustrate these changes). After fluconazole treatment, 12 cases (54.5%) of all patients, 8 cases (66.7%) in the CD group, 2 cases (66.7%) in the ACS group, and 2 cases (28.6%) in the EAS group revealed ALT levels exceeded the ULN (p = 0.247). Additionally, 4 cases (18.2%) of all patients, 4 cases (33.3%) in the CD group, and no cases in the ACS and EAS groups revealed ALT levels more than three times the ULN (p = 0.130).
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Figure 2. ALT before and after fluconazole treatment in patients with Cushing’s syndrome.
ACS, adrenal Cushing’s syndrome; ALT, Alanine aminotransferase; CD, Cushing’s disease; EAS, ectopic ACTH syndrome.

Discussion

To date, our study is the largest retrospective analysis providing the evaluation of the clinical efficacy and safety of fluconazole treatment in patients with CS. The major findings demonstrated that 24-h UFC levels significantly decreased across all groups after fluconazole treatment, with more than 50% reduction in both the CD and ACS groups. However, the EAS group showed only a 13.1% decline in 24-h UFC levels, although with a large interval (SD 64.4%) and small case numbers in this group, indicating greater variability in response and heterogeneity in this group. Regarding hepatic safety, while ALT levels increased after fluconazole treatment, particularly in the CD group, the changes were not statistically significant in other groups. The significant increase in ALT levels (42.4 ± 32.6 to 76.7 ± 54.3 U/L) in the CD group, but mild—less than two times ULN, may also be related to the high variability (large SD). Importantly, there was no severe hepatotoxicity in the study, because only four patients (18.2%) revealed ALT levels more than three times the ULN.
Fluconazole can be administered either intravenously or orally. Several case reports highlight its effectiveness and safety: Teng Chai et al. reported successful long-term treatment of recurrent CD in a 50-year-old woman using fluconazole with cabergoline, resulting in significant clinical and biochemical improvement without adverse effects.27 Zhao et al. reported that fluconazole normalized cortisol levels pre-surgery in a 48-year-old woman with CD and pulmonary cryptococcal infection.28 In another case, fluconazole with low-dose metyrapone normalized cortisol levels for 6 months in a 61-year-old woman with recurrent CD prior to radiotherapy.29 Riedl et al. demonstrated fluconazole’s efficacy and safety in an 83-year-old woman with CS from adrenocortical carcinoma.18 Canteros et al. reported effective cortisol reduction with mild side effects from fluconazole in a 39-year-old woman with EAS, enabling successful bilateral adrenalectomy.30 An 80-year-old woman with CS of unknown origin also showed effective cortisol control with fluconazole.31 Two of these six cases suffered from hepatic dysfunction at fluconazole doses over 400 mg/day; however, liver enzyme levels returned to normal after dosage reduction. A secondary analysis of a dose-adjustment trial for fluconazole in the treatment of invasive mycoses examined 85 patients who received prolonged high-dose treatment. For these cases, 27% experienced clinical symptoms, and 42% exhibited abnormal laboratory results. The common side effects were <5% of anorexia, hair loss, headache, and 12% of eosinophilia. However, these adverse effects did not progress, leading the study to conclude that fluconazole is well tolerated and generally safe.32
Ketoconazole has been used to treat hypercortisolism by inhibiting CYP450 enzymes, specifically 11β-hydroxylase and 17α-hydroxylase, and fluconazole has similar properties.17 Previous studies suggest that fluconazole is less potent in inhibiting glucocorticoid production compared to ketoconazole, with varying effects; however, cortisol reduction with fluconazole use has been confirmed.17,18 Unlike ketoconazole, which is extensively metabolized in the liver and associated with significant hepatotoxicity, fluconazole is minimally metabolized in the liver.16 According to the FDA, the risk of serious liver injury from ketoconazole is higher than with other azole agents.33 In our study of 22 patients, fluconazole was well tolerated, with no significant elevations in liver enzyme levels observed during 6 months of treatment. These findings suggest that fluconazole may represent a safer alternative to ketoconazole for the treatment of CS.
In five studies involving 310 patients with CS treated with an average dose of 673.9 mg/day of ketoconazole over an average of 12.6 months, normalization of urinary free cortisol was achieved in 64.3% of patients (median 50%, range 44.7%–92.9%). However, 23% of initially responsive patients eventually lost biochemical control.34 Another retrospective study of 200 patients with CD receiving ketoconazole at an average dose of 600 mg/day found that 64.7% of patients treated for over 2 years achieved UFC normalization, while 15.4% experienced recurrence, or “escape,” from cortisol control.15 In our study, 10 patients (45.5%) received fluconazole treatment for over 1 year, with 5 of these patients (50%) showing 24-h UFC levels not exceeding 1.5 times the ULN in the following 3–12 months (under control without escape). The long-term control of hypercortisolism with fluconazole appears to be less effective than with ketoconazole. However, this could be attributed to the small sample size in our study.
Table 1 shows baseline morning ACTH levels at diagnosis for all patients before any treatment, highlighting a statistically significant difference. In comparison, Table 2 presents morning ACTH levels prior to fluconazole treatment, where no statistical difference was observed. This is likely due to some patients in the CD and EAS groups having previously undergone surgery or received other medical treatments, which might reduce the tumor burden and the levels of ACTH.
Recent studies suggest that levoketoconazole demonstrates good efficacy and safety in the management of CS.23–25 However, no head-to-head trials have been conducted to compare ketoconazole, levoketoconazole, and fluconazole directly. Therefore, further clinical trials are warranted to provide clearer insights into the comparative efficacy and safety of these therapeutic options in CS.
The limitations of this study include its retrospective design, which lacked comparator groups, and the small sample sizes in the ACS and EAS groups. In addition, patients were treated by different physicians, each using their own clinical judgment, without standardized follow-up protocols, making some data difficult to collect and analyze. The heterogeneity in dosing regimens also posed challenges in assessing the dose-response relationship. Besides, the relationship between the timing and dosages of other medications (etomidate, pasireotide, and metyrapone) and their effects on laboratory findings is challenging to analyze due to the limited number of cases. There were no statistically significant differences in ACTH level changes before and after fluconazole treatment among the three groups. This may be a limitation, as we only monitored the first and second ACTH measurements following fluconazole treatment. Further investigations with longer monitoring of ACTH levels may be necessary. The study’s observation period was approximately 5.5 years, but further investigation is required to confirm the long-term efficacy and safety of fluconazole treatment in CS.

Conclusion

This study demonstrates that fluconazole is effective in treating patients with CS, as evidenced by a significant reduction in 24-h UFC levels. Moreover, fluconazole was generally well tolerated, with a minimal risk of liver injury, suggesting it may be an effective and safe option for managing hypercortisolism in CS.

Acknowledgments

The authors thank the Medical Sciences & Technology Building of Taipei Veterans General Hospital for providing experimental space and facilities.

ORCID iD

Footnotes

Ethics approval and consent to participate This study was approved by the Institutional Review Board at Taipei Veterans General Hospital (IRB No. 2021-04-003CC). Due to the retrospective nature of this study, informed patient consent was waived.

Consent for publication Not applicable.

Author contributions

Tang-Yi Liao: Data curation; Formal analysis; Writing – original draft.
Yi-Chun Lin: Data curation; Writing – review & editing.
Chun-Jui Huang: Data curation; Writing – review & editing.
Chii-Min Hwu: Conceptualization; Data curation.
Liang-Yu Lin: Conceptualization; Data curation; Funding acquisition; Investigation; Methodology; Writing – review & editing.
Funding The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was partly supported by research grants (Grant Nos. V108C-197, V109C-179, V110C-198, V111D62-002-MY3, V112C-183, V113C-094, V114C-116, and V114D77-002-MY3-1) to L.Y.L. from Taipei Veterans General Hospital, Taipei, Taiwan and MOST 111-2314-B-075-040-MY2 to L.Y.L. from National Science and Technology Council, Taiwan. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests The authors declare that there is no conflict of interest.

Availability of data and materials The data and materials generated and analyzed in the study are available from the corresponding author on reasonable request.

References

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10. Schteingart DE. Drugs in the medical treatment of Cushing’s syndrome. Expert Opin Emerg Drugs 2009; 14(4): 661–671.
11. Nieman LK. Medical therapy of Cushing’s disease. Pituitary 2002; 5(2): 77–82.
12. Valassi E, Franz H, Brue T, et al. Preoperative medical treatment in Cushing’s syndrome: frequency of use and its impact on postoperative assessment: data from ERCUSYN. Eur J Endocrinol 2018; 178(4): 399–409.
13. Varlamov EV, Vila G, Fleseriu M. Perioperative management of a patient with Cushing Disease. J Endocr Soc 2022; 6(3): bvac010.
14. Pivonello R, De Martino MC, De Leo M, et al. Cushing’s syndrome. Endocrinol Metab Clin North Am 2008; 37(1): 135–ix.
15. Castinetti F, Guignat L, Giraud P, et al. Ketoconazole in Cushing’s disease: is it worth a try? J Clin Endocrinol Metab 2014; 99(5): 1623–1630.
16. Como JA, Dismukes WE. Oral azole drugs as systemic antifungal therapy. N Engl J Med 1994; 330(4): 263–272.
17. van der Pas R, Hofland LJ, Hofland J, et al. Fluconazole inhibits human adrenocortical steroidogenesis in vitro. J Endocrinol 2012; 215(3): 403–412.
18. Riedl M, Maier C, Zettinig G, et al. Long term control of hypercortisolism with fluconazole: case report and in vitro studies. Eur J Endocrinol 2006; 154(4): 519–524.
19. Albert SG, DeLeon MJ, Silverberg AB. Possible association between high-dose fluconazole and adrenal insufficiency in critically ill patients. Crit Care Med 2001; 29(3): 668–670.
20. Santhana Krishnan SG, Cobbs RK. Reversible acute adrenal insufficiency caused by fluconazole in a critically ill patient. Postgrad Med J 2006; 82(971): e23.
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27. Teng Chai S, Haydar Ali Tajuddin A, Wahab NA, et al. Fluconazole as a safe and effective alternative to ketoconazole in controlling hypercortisolism of recurrent Cushing’s disease: a case report. Int J Endocrinol Metab 2018; 16(3): e65233.
28. Zhao Y, Liang W, Cai F, et al. Fluconazole for hypercortisolism in Cushing’s disease: a case report and literature review. Front Endocrinol (Lausanne) 2020; 11: 608886.
29. Burns K, Christie-David D, Gunton JE. Fluconazole in the treatment of Cushing’s disease. Endocrinol Diabetes Metab Case Rep 2016; 2016: 150115.
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Crinetics Pharma’s Promising Study on CRN04894 for Cushing’s Syndrome: A Potential Game-Changer?

Posted on November 1, 2025 by MaryO

Crinetics Pharmaceuticals is conducting a study titled ‘A Phase 1b/2a Open-label Multiple-ascending Dose Exploratory Study of CRN04894 in ACTH-dependent Cushing’s Syndrome.’ This study aims to evaluate the safety, tolerability, and pharmacokinetics of CRN04894, an ACTH receptor antagonist, in treating Cushing’s Syndrome, a condition characterized by excessive cortisol production. The study’s significance lies in its potential to offer a new treatment avenue for patients with Cushing’s disease or Ectopic ACTH Syndrome.

The intervention being tested is a drug named atumelnant, which is an orally active agent designed to block the action of ACTH at its receptor. This intervention is administered in tablet form and is intended to manage the symptoms of ACTH-dependent Cushing’s Syndrome.

The study employs an interventional design with a sequential model, featuring multiple ascending doses over 10 to 14 days. It is open-label, meaning there is no masking, and its primary purpose is treatment-focused, aiming to assess the drug’s effects on participants.

The study began on March 27, 2023, and is currently recruiting participants. The last update was submitted on April 8, 2025. These dates are crucial as they indicate the study’s progress and ongoing nature, which is essential for stakeholders tracking its development.

This clinical update could influence Crinetics Pharma’s stock performance positively by showcasing their commitment to advancing treatment options for Cushing’s Syndrome. Investors may view this as a promising development, potentially enhancing market sentiment. The study’s progress should be monitored alongside competitors in the endocrinology space to gauge its broader industry impact.

https://www.tipranks.com/news/company-announcements/crinetics-pharmas-promising-study-on-crn04894-for-cushings-syndrome-a-potential-game-changer

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The CuPeR Model: A Dynamic Online Tool for Predicting Cushing’s Disease Persistence and Recurrence After Pituitary Surgery

Posted on October 30, 2025 by MaryO

Abstract

Objective

Predicting postoperative persistence and recurrence of Cushing’s disease (CD) remains a clinical challenge, with no universally reliable models available. This study introduces the CuPeR model, an online dynamic nomogram developed to address these gaps by predicting postoperative outcomes in patients with CD undergoing pituitary surgery.

Methods

A retrospective cohort of 211 patients treated for CD between 2010 and 2024 was analyzed. Key patient and tumor characteristics, imaging findings, and treatment details were evaluated. Multivariate logistic regression identified independent predictors of postoperative persistence or recurrence of CD (PoRP-CD), which were then incorporated into the CuPeR model using stepwise selection based on Akaike Information Criterion. Internal validation was performed using a testing dataset, and a user-friendly online nomogram was developed to facilitate immediate, patient-specific risk estimation in clinical practice.

Results

The final predictive model identified four key factors: symptom duration, MRI Hardy’s grade, tumor site, and prior pituitary surgery. Longer symptom duration and a history of prior surgery significantly increased the risk of recurrence, while bilateral tumor location reduced this risk. The model demonstrated an area under the receiver operating characteristic curve (AUC-ROC) of 0.70, with 83% accuracy, specificity of 96%, and sensitivity of 33%.

Conclusions

The CuPeR model may offer a practical tool for predicting PoRP-CD, enhancing preoperative decision-making by providing personalized risk assessments.

Keywords

Cushing’s disease
Transsphenoidal surgery
Nomogram
Recurrence
Disease Persistence

Abbreviations

ACTH

Adrenocorticotropic Hormone

AIC

Akaike Information Criterion

AUC

Area Under the Curve

BMI

Body Mass Index

CD

Cushing’s Disease

CI

Confidence Interval

CRH

Corticotropin-Releasing Hormone

DFS

Disease-Free Survival

DL

Deep Learning

eTSS

Endoscopic Transsphenoidal Surgery

HR

Hazard Ratio

IPSS

Inferior Petrosal Sinus Sampling

ML

Machine Learning

MRI

Magnetic Resonance Imaging

OS

Overall Survival

PoRP-CD

Persistent or Recurrent Cushing’s Disease

SIADH

Syndrome of Inappropriate Antidiuretic Hormone Secretion

TSS

Transsphenoidal Surgery

UFC

Urinary Free Cortisol

Introduction

Cushing’s disease (CD) is a rare endocrine disorder, with an annual incidence rate of approximately 0.24 cases per 100,000 individuals [1]. Transsphenoidal surgery (TSS), performed using either endoscopic or microscopic approaches, remains the cornerstone of treatment for CD. Notably, meta-analytical studies have reported that TSS achieves remission and provides long-term disease control in 71–80 % of patients [[2], [3], [4]]. The remaining cases may experience persistent disease despite surgery, while others may face disease recurrence despite initial remission. In such cases, additional treatment options include second pituitary surgery, pituitary irradiation, targeted medical therapies, and bilateral adrenalectomy, each with varying success rates ranging from 25 % for medical therapy to 100 % for bilateral adrenalectomy [5].
To date, no single predictive factor has proven effective in reliably forecasting treatment outcomes in patients with CD [6]. This underscores the critical need for developing predictive models to assess the likelihood of postoperative recurrence or persistence of Cushing’s disease (PoRP-CD). However, only a limited number of studies have addressed this gap. Notably, two studies from Peking Union Medical College Hospital attempted to tackle this issue using machine learning (ML) and deep learning (DL) approaches [6,7]. These studies utilized demographic, clinical, and paraclinical variables to construct predictive models, with DL approaches showing potential to enhance predictive accuracy [7]. While the results of these models were promising, their applicability in routine clinical practice remains limited. Both studies focused exclusively on patients undergoing their initial transsphenoidal surgery, making them less applicable for cases involving patients with a prior history of pituitary surgery or radiotherapy. Furthermore, these models incorporated both preoperative and postoperative parameters, such as changes in cortisol and adrenocorticotropic hormone (ACTH) levels. However, serum cortisol, ACTH, and comprehensive endocrine testing should be available before any treatment decisions are made, and each patient should ideally be reviewed by a multidisciplinary tumor board, including neurosurgery, radiology, endocrinology, and oncology, prior to pituitary surgery. As such, more comprehensive and practical predictive tool that can support timely clinical decision-making and accommodate a broader range of patient scenarios in the management of CD.
The current study was designed to address these critical limitations and provide a more practical solution for predicting postoperative outcomes in CD. Applying one of the largest available CD cohorts, we incorporated a wide array of patient and tumor characteristics, imaging findings, and treatment details to develop a robust and comprehensive predictive model. This model offers treating surgeons reliable insights into the likelihood of tumor recurrence or persistence. By providing individualized risk predictions, the model is intended to assist clinicians in considering different therapeutic options before pituitary surgery, complementing—but not replacing—standard multidisciplinary decision-making. To further enhance its utility in clinical practice, we also developed an interactive online dynamic nomogram, allowing individualized predictions of postoperative persistence or recurrence.

Methods

Study design, patients, and endpoints

The experimental protocol was approved by the Institutional Review Board of Shahid Beheshti University of Medical Sciences (Tehran, Iran). This retrospective study investigates the clinical outcomes of pituitary surgery in patients with CD underwent pituitary surgery between 2010 and 2024 in the neurosurgery department at Loghman Hakim Hospital. Surgeries were conducted by a group of experienced neurosurgeons under the supervision of the first author (G.S). The primary objective of this study was to develop and validate a predictive model for assessing the risk of PoRP-CD. The secondary objectives were (a) to summarize patient and tumor characteristics; (b) to report surgical outcomes and remission rates following surgery; and (c) to analyze patient survival. This study was performed in accordance with the Declaration of Helsinki, and adheres to the reporting guidelines outlined in the STROBE Statement. Due to retrospective nature of the study informed consent was waived by Shahid Beheshti University of Medical Sciences Ethics Committee. All methods were performed in accordance with the relevant guidelines and regulations.

Preoperative assessments

The “index surgery” was set to the most recent pituitary surgery. Before the index surgery, patients underwent comprehensive clinical evaluations, including biochemical and neurological assessments as well as visual field examinations. This research utilized the Endocrine Society Clinical Practice Guideline to establish the diagnosis of CD [8]. Three main steps were involved in the diagnostic process: in the first step, the focus was on detecting hypercortisolemia, which was determined by examining 24-hour urinary free cortisol levels (normal: <60 mcg/24 h), as well as plasma and salivary cortisol profiles. Low-dose dexamethasone suppression testing was performed using the 2 mg/48 h protocol, which was the standard practice in our institution during the study period (2010 onward) [8]. The second step aimed to confirm ACTH-dependent cause of hypercortisolemia, through measuring plasma ACTH levels. The final step aimed to distinguish Cushing’s disease from ectopic sources of ACTH. This was performed using a high-dose dexamethasone suppression test (8  mg overnight), with a plasma cortisol suppression exceeding 50 % typically considered indicative of a pituitary origin [9].
Next, the patients were subjected to thin-slice (3 mm) 1.5-tesla dynamic pituitary gland magnetic resonance imaging (MRI) with gadolinium contrast. The MR evaluation adhered to a strict protocol, requiring an independent agreement of treating neurosurgeon and radiologist to confirm the diagnosis. MR scans were categorized according to the Hardy and Knosp classifications [10]. Normal scans required to demonstrate the absence of direct signs, including inhomogeneity in the pituitary, as well as indirect signs such as a deviation of the pituitary stalk, bulging or erosion of the Sella contour. In cases where the CD was confirmed but pituitary MRI was inconclusive, bilateral inferior petrosal sinus sampling (IPSS) was performed per standard protocol under corticotropin-releasing hormone (CRH) stimulation [11]. Patients with macroadenoma or signs of elevating the optic chiasm were candidates for Humphrey visual field examination.

Surgical approach

Patients underwent endoscopic transsphenoidal approach using conventional “Two Nostrils–Four Hands” technique [12]. Given the diminutive size and deep-seated location of most adenomas, locating the adenoma emerged as a formidable challenge, particularly when the tumor remained not visualized in pre-operative imaging studies. The surgical procedure entailed extensive drilling of the Sellar floor laterally up to the carotid artery on both sides, providing a comprehensive view of the medial wall of the cavernous sinus and exposure of the anterior and posterior intercavernous sinuses. The exploration of the entire Sella commenced in the region where the original tumor had been localized. Upon identification of a tumor, a selective adenomectomy was performed, accompanied by a thorough inspection of the pituitary gland to detect and eliminate any potential tumor remnants. The removal of any pseudo capsule was executed meticulously.
The primary surgical objective was selective adenomectomy, with further exploration guided by the side recommended by IPSS in cases where no adenoma was initially observed. The exploration involved making a plus-like incision on the corresponding half of the gland, enabling deep exploration to leave no part unexplored. In instances where creamy material suggestive of a tumor was drained after a pituitary incision, a tissue biopsy was obtained, although it was not conclusively considered a tumor. Exploration continued on the opposite side in such cases.
When no distinct adenoma was found, a peri-glandular inspection was conducted to visualize the medial wall of the cavernous sinus, diaphragm, and Sellar floor, aiming to detect an ectopic microadenoma. If an apparent tumor remained undetected, the procedure was repeated on the contralateral side, and a vertical medial incision on the pituitary gland adjacent to the pituitary stalk and neurohypophysis was made as a final effort for tumor detection. In the absence of identified pathology during the surgical procedure, hemi-hypophysectomy was considered on the side where IPSS had detected the gradient or on the side with an apparent or suspicious MRI finding. Considering the typical central location of corticotroph cells in the pituitary gland, microadenoma exploration extended posteriorly and medially to confirm extirpation.

Postoperative assessments

In this study, the patients were closely monitored for signs of diabetes insipidus and syndrome of inappropriate antidiuretic hormone secretion (SIADH). Serum sodium levels, urine-specific gravity, and volume were checked regularly. Following surgery, morning cortisol levels were measured on the first day, and other anterior pituitary hormones were evaluated on day 3. Hydrocortisone therapy was initiated based on the patient’s symptoms, signs of adrenal insufficiency, and low cortisol levels. The first postoperative check-up occurred two weeks after surgery, followed by another at three months, which included a comprehensive assessment of pituitary hormones. This evaluation was repeated every three months for two years and then annually. Additionally, patients underwent a dynamic 1.5-Tesla pituitary MRI at six months post-surgery and annually thereafter, with a minimum follow-up period of 12 months.
Remission was defined as having low cortisol levels, indicated by early morning serum cortisol level ≤ 5 μg/dL within two days post-surgery [13]. Persistent CD was characterized by ongoing hypercortisolism, and postoperative recurrence refers to the reappearance of CD symptoms despite initial remission marked by hypercortisolemia. In case of persistence or recurrence, patients were candidates for second-line treatment options selected by their physicians, including revision surgery, targeted medical therapy, pituitary radiotherapy, or bilateral adrenalectomy. Disease-free survival (DFS) was defined as the time from the index surgery to the first occurrence of disease recurrence or death from any cause, while overall survival (OS) was defined as the time from the index surgery to death from any cause.

Statistical analysis

Categorical variables were expressed as numbers and percentages, and continuous variables as mean, range, and standard deviation. The distribution of variables was checked using the Shapiro-Wilk test, which showed a deviation from normal distribution. Contingency tables were used for categorical variables with Pearson’s Chi-squared or Fisher’s Exact test used to examine their association with outcomes for univariate analyses. For continuous variables, the unpaired t-test was applied to compare means between two independent groups when the data met the assumption of normality. Analyses were conducted with R Statistical Software v4.4.0 (“Puppy Cup”). All statistical inferences were two-sided, and P < 0.05 were considered statistically significant.

Model development and internal validation

The dataset was split by “caret package” into a training set (70 %) and a testing set (30 %) using stratified sampling to ensure representative proportions of outcomes. Binary logistic regression was used to identify predictors of PoRP-CD. Patients with adequate follow-up data were included in the analysis. The variables with a marginal level of association (P < 0.15) in the univariate analysis were further included in the multivariate logistic regression analysis to identify the independent predictors of PoRP-CD. Imported factors included demographic, medical history, imaging and pathology results, and treatment details. To identify predictors of PoRP-CD, a multivariable logistic regression model was developed using stepwise selection based on Akaike Information Criterion (AIC). Model performance, including sensitivity, specificity, and area under the receiver operating characteristic curve (AUC-ROC), was evaluated using internal validation on the test dataset.

Nomogram creation and deployment

A nomogram was constructed using the validated logistic regression model. The nomogram was then integrated into a web-based application using the “Shiny package” in R program. The dynamic nomogram allows clinicians to input patient data and obtain individualized risk predictions for PoRP-CD.

Survival analysis

Survival analysis was conducted to evaluate DFS across various patient subgroups. The log-rank test was applied to assess statistical differences in survival distributions between subgroups. Cox proportional hazard regression was used to estimate hazard ratios (HR) and 95 % confidence intervals (CI). The “survival” and “survminer” R packages were applied in this section.

Results

Patients and tumors characteristics

A total of 211 patients with CD had been treated by a group of experienced neurosurgeons under the supervision of the first author (G.S) between March 2010 and January 2024 in the neurosurgery department at Loghman Hakim Hospital. Table 1 summarizes the baseline characteristics of patients at the timepoint of index surgery. The patients had a mean age of 35.9 ± 12.1 years (range: 11–67), among which 21 patients (9.9 %) were in the pediatric age range, and 165 (78.1 %) were female. Obesity was the most common patients’ symptoms (45.9 %), and physical examination reported centripetal obesity (84.3 %), moon face (75.8 %), and striae (64.4 %) as the most common clinical manifestations. Compared to the adult patients, pediatrics had less common hypertension on physical examination (35.2 vs. 5.9 %) and medical history of diabetes mellitus (36.8 vs. 4.7 %) (P < 0.05). The majority of patients (63.9 %, 135/211) had not received any prior treatment. Among those who had, surgery alone was the most common approach (n = 57, 27.0 %), performed once in 50 patients (23.6 %), twice in 6 patients (2.8 %), and three times in a single patient.

Table 1. Baseline characteristics of adult and pediatric patients with Cushing’s disease.

Demographics Total
n = 211		 Adults
n = 190		 Pediatrics
n = 21		 P Medical Hx Total
n = 211		 Adults
n = 190		 Ped.
n = 21		 P Drug-Family Hx Total
n = 211		 Adults
n = 190		 Ped.
n = 21		 P
Age; mean-SD (y) 35.9–12.1 38.3–10.2 14.8–1.7 0<.001 Hypertension 97 (45.9) 92 (48.4) 5 (23.8) 0.31 Cabergoline 3 (1.4) 3 (1.5) 0 1.0
Sex; female 165 (78.1) a 149 (78.4) 16 (76.1) 0.78 Diabetes mellitus 71 (33.6) 70 (36.8) 1 (4.7) 0<.001 Ketoconazole 12 (5.6) 12 (6.3) 0 0.61
Marital status; married 105 (70.0) b 103 (76.8) b 2 (12.5) b 0<.001 Dyslipidemia 45 (21.3) 42 (22.1) 3 (14.2) 0.56 Metyrapone 0 − − −
Smoking status; active–passive-non 17 (10)-27(17)-113(72) b 17 (11)–23(15)-101(70) b 0–4(25)-12(75) b 0.70 Prior pituitary surgery 57 (27.0)) 51 (26.8) 6 (28.5) 1.0 Pasireotide 0 − − −
Height; mean-SD (cm) 163.9–8.7 163.8–8.9 165.1–6.6 0.59 Fatty liver 37 (17.5) 32 (16.8) 5 (23.8) 0.36 Somatostatin 0 − − −
Weight; mean-SD (Kg) 74.1–22.5 74.6–22.5 69.3–23.1 0.58 Thromboembolism 6 (2.8) 6 (3.1) 0 1.0
BMI; mean-SD (Kg/m2) 28.8–6.1 29.0–6.2 27.6–5.5 0.72 DVT 3 (1.4) 3 (1.5) 0 1.0 FH of Cushing 5 (2.3) 4 (2.1) 1 (4.7) 0.43
Symptom duration; mean-SD (m) 30.7–41.2 32.0–43.2 20.0–14.2 0.78 MEN 1 (0.4) 1 (0.5) 0 1.0 FH of MEN 1 (0.4) 1 (0.5) 0 1.0
Presenting Symptoms
Obesity 75 (45.9) b 66 (45.2) b 9 (52.9) b 0.61 Striae 10 (6.1) b 8 (5.4) b 2 (11.7) b 0.27 Headache 4 (2.4) b 3 (2.0) b 1 (5.8) b 0.35
Menstrual disorders 16 (9.8) b 13 (8.9) b 3 (17.6) b 0.22 Edema 7 (4.2) b 7 (4.7) b 0 1.0 Diabetes mellitus 3 (1.8) b 3 (2.0) b 0 1.0
Hypertension 12 (7.3) b 12 (8.2) b 0 0.61 Muscular weakness 7 (4.2) b 6 (4.1) b 1 (5.8) b 0.54 Bone fracture 3 (1.8) b 3 (2.0) b 0 1.0
Blurred vision 10 (6.1) b 9 (6.1) b 1 (5.8) b 1.0 Moon face 6 (3.6) b 6 (4.1) b 0 1.0 Other 10 (6.1) b 10 (6.8) b 0 0.60
Clinical Manifestations
Acanthosis nigricans 35 (16.5) 34 (17.8) 1 (4.7) 0.12 Easy bruising 103 (48.8) 92 (48.4) 11 (52.3) 0.91 Male pat. hair loss 111 (52.6) 100 (52.6) 11 (52.3) 1.0
Acne 68 (32.2) 58 (30.5) 10 (47.6) 0.16 Ecchymosis 58 (27.5) 50 (26.3) 8 (38.0) 0.37 dysmenorrhea 96 (45.4) 84 (44.2) 12 (57.1) 0.49
Ankle edema 105 (49.7) 96 (50.5) 9 (42.8) 0.57 Exophthalmia 50 (23.7) 47 (24.7) 3 (14.2) 0.27 Moon face 160 (75.8) 141 (74.2) 19 (90.4) 0.69
Backache 66 (31.2) 60 (31.5) 6 (28.5) 0.88 Facial plethora 97 (45.9) 85 (44.7) 12 (57.1) 0.33 Osteoporosis 25 (11.8) 25 (13.1) 0 0.14
Blurred vision 70 (33.2) 67 (35.2) 3 (14.2) 0.27 Fatigue 146 (69.2) 130 (68) 16 (76.1) 0.76 Prox. myopathy 94 (44.5) 86 (45.2) 8 (38.0) 0.63
Buffalo hump 123 (58.3) 107 (56.3) 16 (76.1) 0.43 Fracture 12 (5.6) 12 (6.3) 0 0.61 Skin atrophy 81 (38.4) 73 (38.4) 8 (38.0) 1.0
Centripetal obesity 178 (84.3) 159 (83.6) 19 (90.4) 0.50 Headache 109 (51.6) 97 (51.0) 12 (57.1) 1.0 Striae 136 (64.4) 119 (62.6) 17 (80.9) 0.55
Cerebrospinal fluid leakage 5 (2.3) 4 (2.1) 1 (4.7) 0.41 Hirsutism 104 (49.3) 92 (48.4) 12 (57.1) 0.72 Supraclav. fat pad 38 (18.0) 33 (17.3) 5 (23.8) 0.67
Cranial nerve palsy 3 (1.4) 3 (1.5) 0 1.0 Hyperpigmentation 38 (18.0) 37 (19.4) 1 (4.7) 0.12 Visual field defect 24 (11.3) 22 (11.5) 2 (9.5) 1.0
Diplopia 18 (8.5) 15 (7.8) 3 (14.2) 0.41 Hypertension 69 (32.7) 67 (35.2) 2 (9.5) 0.009 Weight gain 108 (51.1) 95 (50.0) 13 (61.9) 0.39
Prior Treatments
Treatment naïve 135 (63.9) 122 (64.2) 13 (61.9) 1.0 Pituitary surgery alone 39 (18.4) 33 (17.3) 6 (28.5) 0.23 Radiotherapy alone 6 (2.8) 5 (2.6) 1 (4.7) 0.47
Medication alone 5 (2.3) 5 (2.6) 0 1.0 Combination therapy 17 (8.1) 17 (8.9) 0 0.22 Adrenalectomy alone 11 (5.2) 10 (5.2) 1 (4.7) 1.0
Hormonal Assessments
Hypothyroidism 24 (31.1) b 24 (31.1) b 0 0.09 GH deficiency 6 (8.8) b 6 (8.8) b 0 1.0 Hypogonadism 7 (9.8) b 7 (9.8) b 0 1.0
Panhypopituitarism 2 (2.5) b 2 (2.5) b 0 1.0
Imaging Features
Hardy’s grading
(sphenoid bone invasion)
0
1
2
3
4		 37 (21.1) b
102 (58.2) b
27 (15.4) b
4 (2.2) b
5 (2.8) b		 35 (22.7) b
88 (57.1) b
23 (14.9) b
3 (1.9) b
5 (3.2) b		 2 (9.5)
14 (66.7)
4 (19.0)
1 (4.7)
0		 0.45 Hardy’s staging
(suprasellar extension)
A
B
C
D
E		 36 (20.4) b
86 (48.8) b
14 (7.9) b
4 (2.2) b
36 (20.4) b		 34 (21.9) b
73 (47.1) b
14 (9.0) b
2 (1.2) b
32 (20.6) b		 2 (9.5)
13 (62)
0
2 (9.5)
4 (19.0)		 0.07 Knosp grading

0
1
2
3
4

 152 (82.6) b
13 (7.0) b
7 (3.8) b
4 (2.1) b
8 (4.3) b		 135 (82.8) b
10 (6.1) b
6 (3.6) b
4 (2.4) b
8 (4.9) b		 17 (80.9)
3 (14.2)
1 (4.7)
0
0		 0.46
Tumor size
Microadenoma
Macroadenoma
MR-negative		 122 (58.6) b
50 (24.0) b
36 17.3) b		 111 (59.3) b
42 (22.4) b
34 (18.1) b		 11 (52.3)
8 (38.0)
2 (9.5)		 0.28 Sphenoid shape
Sellar
Presellar
Conchal		 205 (97.6) b
3 (1.4) b
2 (0.9) b		 184 (97.3) b
3 (1.5) b
2 (1.0) b		 21 (100)
0
0		 1.0 Multifocality
Unifocal
Multifocal		 113 (80.1)
28 (19.8)		 97 (79.5)
25 (20.4)		 16(84.2)
3 (15.7)		 0.79
Invasion c
No invasion
Cavernous sinus
Carotid
Dura
Clivus		 185 (88.5) b
12 (5.7) b
3 (1.4) b
6 (2.8) b
3 (1.4) b		 165 (87.7) b
11 (5.8) b
3 (1.5) b
6 (3.1) b
3 (1.5) b		 20 (95.2) b
1 (4.8) b
0
0
0		 1.0 Tumor site
Right lobe
Left lobe
Bilateral
Central
Stalk		 22 (15.6)) b
16 (11.3)) b
51 (36.1) b
49 (34.7) b
3 (2.1) b		 20 (16.2) b
13 (10.5) b
43 (34.9) b
45 (36.5) b
2 (1.6) b		 2 (11.1) b
3 (16.6) b
8 (44.4) b
4 (22.2) b
1 (5.5) b		 0.38 Empty sella
No
Yes		 207 (98.1)
4 (1.8)		 187 (98.4)
3 (1.5)		 20(95.2)
1 (4.7)		 0.34
Pituitary apoplexy
No
Yes		 185 (97.3) b
5 (2.6) b		 167 (98.2) b
3 (1.7) b		 18 (90.0) b
2 (10.0) b		 0.08 Kissing carotids
No
Yes		 209 (99.0)
2 (0.9)		 188 (98.9)
2 (1.0)		 21 (100)
0		 1.0
a
the numbers in parentheses represent the percentage for each patient group.
b
percentage after ruling out missing data.
c
one patient had invasion to cavernous sinus and carotid and another one had clivus and dural invasion.
A comprehensive preoperative hormonal assessment was conducted on 77 patients (36.4 %), revealing hormonal dysregulation in 28 patients (36.3 %). Hypothyroidism was the most common abnormality, affecting 35 % of those assessed (24 out of 77). On MRI scans, most tumors were microadenomas (58.6 %), with fewer macroadenomas (24.0 %) and some cases with no detectable tumor (17.3 %). Tumors were commonly localized bilaterally (36.1 %) or centrally (34.7 %), and most were unifocal (80.1 %). Knosp grading indicated no cavernous sinus invasion in the majority (82.6 %), with only 6.4 % showing grades 3–4. According to Hardy’s grading, most patients had mild sphenoid bone invasion, predominantly grade 1 (58.2 %). For Hardy’s staging of suprasellar extension, nearly half were at stage B (48.8 %), with smaller groups in stages A and E (20.4 % each), and fewer in stages C and D. Other MRI findings are summarized in Table 1. There was no significant difference between adult and pediatric patients in terms of hormonal and imaging findings (P > 0.05). Pathology reports were available for 36 patients. The most common finding was sparse cellularity, observed in 11 patients (30.6 %) followed by dense cellularity identified in 9 patients (25 %). Crooke cell changes were the least common, present in 7 patients (19.4 %). Nine specimens (25 %) had no tumor identified in the sample submitted to pathology.

Treatment details and outcomes

A total of 36 patients (17.1 %) underwent preoperative IPSS, among which 13 had right lateralization, 13 left, 4 bilateral, 3 central, 2 central-right, and 1 central-left. Pituitary surgery was predominantly performed using the endoscopic transsphenoidal (eTSS) approach (98.5 %, 208/211), while the transplanum approach was used in 3 patients (1.5 %). Adenomectomy was the most common surgical procedure (n = 187, 88.6 %), followed by total hypophysectomy in 17 patients (8.1 %) and hemi-hypophysectomy in 7 patients (3.3 %). In addition, four patients in the total hypophysectomy group and one patient in the adenomectomy group also underwent hypophyseal stalk resection. Information on disease persistence or recurrence was available for 204 patients. Median follow-up of patients was 58.4 months (range: 4.5–170.4 months) after index surgery. In total, 23 patients (11.2 %) experienced persistent disease following the index surgery, while 10 patients (4.9 %) had disease recurrence, with a median time to recurrence of 7 months (range: 1–78 months). The median recurrence-free interval for the entire cohort was 37 months.
The surgical complication rates were as follows (Fig. 1A): cerebrospinal fluid leaks were observed in 22 patients (10.4 %), followed by cranial nerve injury in 7 patients (3.3 %) and meningitis in 5 patients (2.3 %). Carotid injury and intracerebral bleeding each occurred in 3 patients (1.4 %). Nasal bleeding, the need for a ventriculoperitoneal shunt, and embolic events were each reported in 1 patient (0.4 %). Perioperative mortality was observed in one female patient (0.4 %) due to an iatrogenic carotid injury. This patient had previously undergone three pituitary surgeries and received radiotherapy at the pituitary site. Hormonal dysregulation following surgery included hypothyroidism in 99 patients (46.9 %), diabetes insipidus in 76 patients (36 %), hypogonadism in 28 patients (13.2 %), growth hormone deficiency in 10 patients (4.7 %), and panhypopituitarism in 7 patients (3.3 %) (Fig. 1B).

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Fig. 1. Rates of surgical complications. (a) Intraoperative complications; (b) hormonal dysregulation rates following surgery.

Multivariate analysis on the predictors of Persistent/Recurrent Cushing’s disease

To identify potential predictive factors for PoRP-CD, we conducted a comprehensive binary logistic regression analysis, examining key clinical and imaging variables (Table 2). In the univariate analysis, factors including symptom duration (OR [odds ratio] 1.01, 95 % CI [confidence interval] 1.00–1.02, P = 0.04), MRI Hardy’s grade (OR 1.62, 95 % CI 0.98–2.69, P = 0.05), and previous pituitary surgery (OR 3.56, 95 % CI 1.39–9.07, P = 0.007) demonstrated significant association with PoRP-CD. MR-reported tumor size showed increased odds of recurrence with an increased tumor size (OR for microadenoma vs. no tumor: 2.41, 95 % CI: 0.50–11.53; OR for macroadenoma vs. no tumor: 4.15, 95 % CI 0.80–21.42), though the effect was not statistically significant (P > 0.05). To impede missing the marginal significant factors, three factors with P values between 0.05 and 0.15 were also included in the multivariate analysis, including “MRI Knosp grading”, “MR-reported tumor site”, and “previous pituitary radiotherapy”. In the multivariate analysis, “symptom duration” was positively correlated with recurrence, with an odds ratio (OR) of 1.03 (95 % CI: 1.01–1.06, P = 0.01), indicating a higher risk of recurrence with prolonged symptoms. Additionally, a history of “previous pituitary surgery” was significantly associated with recurrence, with an OR of 4.67 (95 % CI: 1.04–20.89, P = 0.04). Other factors, including tumor grading, tumor site, and previous radiotherapy, did not reach statistical significance.

Table 2. Regression analysis of patient and tumor’s factors related to postoperative persistence or recurrence in Cushing disease.

Parameters Univariate Analysis Multivariate Analysis
OR (95 % CI) P OR (95 % CI) P
Age 0.97 (0.94–1.01) 0.23
Sex (male vs. female) 1.17 (0.39–3.50) 0.77
Smoking (active smoker vs. non) 0.78 (0.65–10.28) 0.77
Family history of CD (positive vs. negative) 0.01 (0–Inf) 0.99
Family history of MEN (positive vs. negative) 0.01 (0–Inf) 0.99
Preoperative BMI 1.03 (0.94–1.13) 0.43
Symptom duration 1.01 (1.00–1.02) 0.04 ** 1.03 (1.01–1.06) 0.01 **
Preop serum ACTH (high vs. normal) 0.88 (0.13–6.00) 0.90
Preop free serum cortisol (high vs. normal) 1.18 (0.40–3.45) 0.74
Preop urine free cortisol (high vs. normal) 0.15 (0.01–2.98) 0.21
Knosp grading (ref: grade 0) 1.41 (0.93–2.15) 0.10 * 1.56 (0.61–3.97) 0.34
Hardy’s grading (ref: grade 0) 1.62 (0.98–2.69) 0.05 ** 1.98 (0.54–7.21) 0.29
Hardy’s staging (ref: stage A) 2.97 (0.61–14.38) 0.17
Tumor size
Macro vs. no tumor
Micro vs. no tumor		 4.15 (0.80–21.42)
2.41 (0.50–11.53)		 0.17
Multifocality (multifocal vs. unifocal) 1.68 (0.44–6.42) 0.44
MR-based tumor sitea
Bilateral vs. central
Left vs. central
Right vs. central
Stalk vs. central		 0.16 (0.01–1.53)
0.82 (0.18–4.40)
0.49 (0.09–2.82)
5.33 (0.37–144.16)		 0.14 * 0.34 (0.02–3.95)
0.23 (0.01–3.12)
5.36 (0.19–146.38)

  • (0.0002–0.67)
 0.03 **
0.39
0.27
0.31
Invasion (pos. vs. neg.) 1.18 (0.31–4.51) 0.80
Surgical approach (transplanum vs. eTSS) 6.21 (0.37–103.55) 0.20
Surgical type (adenomectomy vs. hypophysectomy) 1.55 (0.46–5.22) 0.47
Histopathology
Dense type vs. Crooke’s cell adenoma
Normal appearing vs. Crooke’s cell adenoma
Sparse type vs. Crooke’s cell adenoma		 2.00 (0.09–69.06)
0.80 (0.04–23.23)
0.28 (0.01–9.45)		 0.56
Ki-67 (>3% vs. ≤ 3 %) 1.34 (0.14–12.64) 0.79
Previous pituitary surgery (yes vs. no) 3.56 (1.39–9.07) 0.007 ** 4.67 (1.04–20.89) 0.04 **
Previous pituitary radiotherapy (yes vs. no) 3.36 (0.89–12.62) 0.07 * 3.63 (0.28–46.07) 0.31
Postop decrease in BMI 0.90 (0.73–1.03) 0.22
Abbreviations: ACTH − Adrenocorticotropic Hormone; BMI − Body Mass Index; CD − Cushing’s Disease; CI − Confidence Interval; eTSS − Endoscopic Transsphenoidal Surgery; Inf − Infinity; MEN − Multiple Endocrine Neoplasia; MR − Magnetic Resonance; OR − Odds Ratio; PoRP-CD − Persistent or Recurrent Cushing’s Disease; Preop − Preoperative; Postop − Postoperative.
aMR-reported.
* Significant at the level of 0.15.
** Significant at the level of 0.05.
The stepwise selection–in both forward and backward directions–retained four predictors— symptom duration, Hardy’s grading, tumor site, and prior surgery —for the final model. The final multivariate model with four predictors of “symptom duration”, “MRI Hardy’s grading”, “tumor site”, and “previous pituitary surgery” demonstrated significant associations for “symptom duration” (OR 1.03, 95 % CI 1.005–1.05, P = 0.02), previous pituitary surgery (OR 4.61, 95 % CI 1.12–22.0, P = 0.03), and a certain tumor site; tumors located bilaterally had significantly lower odds of recurrence compared to central tumors (OR 0.01, 95 % CI 0.0002–0.45, P = 0.02). On the testing dataset, the four-factor model achieved an AUC of 0.70, specificity of 96 %, and sensitivity of 33 %. The model’s accuracy in predicting PoRP-CD is 83 %.

Predicting persistent or recurrent Cushing’s disease–The CuPeR nomogram

A nomogram was developed based on the multivariate model comprising four key predictors: “Symptom duration”, “MRI Hardy’s grading”, “Previous pituitary surgery”, and “MRI-reported tumor site” (Fig. 2). This nomogram visually represents the impact of each predictor on the likelihood of PoRP-CD. The total score derived from the nomogram aligns with the probability scales, allowing for estimation of the risk of PoRP-CD. Higher cumulative points correspond to an increased likelihood of persistent or recurrent disease. To facilitate individualized predictions of postoperative persistence or recurrence, we developed an online dynamic nomogram (link: https://cushing.shinyapps.io/cuper/).

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Fig. 2. Nomogram for predicting postoperative persistence or recurrence of Cushing’s disease (PoRP-CD). This nomogram visually represents the predictive model for assessing the risk of recurrence or persistence of Cushing’s disease following surgery. Each predictor variable—Symptom duration (months), Knosp grading, Hardy’s grading, previous pituitary surgery, and tumor site— contributes a point value that aligns with the “Linear Predictor” scale, which maps to the “Probability of Persistence” scale, allowing estimation of recurrence likelihood.

Survival analysis

Survival analysis demonstrated a steady, gradual decline in DFS across the entire cohort, with the median DFS not reached despite substantial follow-up (Fig. 3A). Among the predefined variables, Hardy’s Grade 3 was associated with a significantly worse DFS compared with Grade 0 (HR = 6.02, 95 % CI: 1.09–33.02, P = 0.03) (Fig. 3B), whereas other Hardy’s Grades did not reach statistical significance (P > 0.05). Regarding tumor site, no site was a statistically significant risk factor for DFS; stalk tumors showed a trend toward poorer DFS but did not reach significance (HR = 5.09, 95 % CI: 0.84–30.63, P = 0.07) (Fig. 3C). Patients with a history of previous pituitary surgery had significantly worse DFS (HR = 4.72, 95 % CI: 2.29–9.75, P < 0.01) (Fig. 3D). In contrast, symptom duration was not associated with poor DFS (HR = 1.26, 95 % CI: 0.56–2.81, P = 0.57) (Fig. 3E). A similar analysis on OS was not performed, as only five events were recorded among the 211 patients (2.36 %), rendering meaningful statistical analysis infeasible.

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Fig. 3. Disease-free survival (DFS) analysis. (A) Kaplan-Meier curve of DFS for the entire cohort, showing a gradual decline over time; (B) DFS stratified by Hardy’s Grade, demonstrating significant impact of grade 3 on survival outcomes (P = 0.03); (C) DFS by tumor site, highlighting no significant association between tumor site and survival care (P > 0.05); (D) DFS based on previous surgery status, indicating a higher risk of recurrence or death in patients with prior surgical interventions (P < 0.01); (E) DFS by symptom duration, highlighting no significant association (P = 0.57).

Discussion

In this large cohort study, we developed the CuPeR model, a comprehensive predictive tool for PoRP-CD, by analyzing diverse patient and tumor characteristics, imaging findings, and treatment details. This model identified four key predictors—symptom duration, MRI Hardy’s grade, tumor site, and previous pituitary surgery. Multivariate analysis revealed that longer symptom duration and a history of prior surgery significantly increased recurrence risk, while bilateral tumor location was associated with a reduced risk. Validated with an AUC of 0.70 and 83 % accuracy on the testing dataset, the model offers significant clinical utility by providing treating surgeons with valuable insights into postoperative outcomes.
This study is among the few to develop a predictive model for estimating PoRP-CD (Table 3). Previous efforts, such as those by Liu et al. [6] and Fan et al. [7], employed machine learning and deep learning methodologies, respectively, demonstrating promising results (AUCs of 0.78 and 0.86). However, both studies were limited in their applicability to many clinical settings, as they focused solely on patients undergoing initial surgeries and incorporated postoperative parameters, which are unavailable for preoperative decision-making. By addressing these gaps, our study contributes a more practical tool for use in diverse clinical scenarios. Moreover, the findings of this study align with predictors identified in prior research. For instance, factors such duration of symptoms and history of previous pituitary surgery have been highlighted as critical for recurrence [6,14]. Importantly, our inclusion of MRI-based predictors and preoperative variables ensures the model’s relevance during preoperative planning, distinguishing it from previous approaches.

Table 3. Studies on predictive models or patients and tumors predictive factors of post-operative remission of Cushing’s disease.

Empty Cell Year Country Study Size Methods Main Findings Ref.
Predictive Models
Comprising 8 factors:
age,
disease coarse,
morning serum ACTH (preop),
morning serum cortisol (preop),
urine free cortisol (preop),
morning serum ACTH nadir (postop),
morning serum cortisol nadir (postop),
urine free cortisol nadir (postop)		 2019 China 354 Machine-learning using Random Forest algorithm Sensitivity 87 %, specificity 58 %
AUC 0.78		 [6]
Comprising 5 factors:
age,
disease coarse,
morning serum ACTH (postop),
morning serum cortisol nadir (postop),
urine free cortisol nadir (postop)		 2021 China 354 Deep-learning using factorization‑machine based neural approach AUC 0.86 [7]
Predictive Factors
Serum cortisol < 35 nmol/L (6–12 w after surgery) 1993 UK 11 Prospective Favorable long-term remission rate [15]
Serum 11-deoxycortisol > 150 nmol/L after metyrapone test at 14 days post-surgery 1997 Netherlands 29 Retrospective Higher risk of recurrence
Sensitivity 100 %, specificity 75 %		 [16]
Serum cortisol < 2 μ/dL (3–8 d after surgery) 2001 Japan 49 Retrospective Recurrent disease in 4 % of patients [17]
MRI-based tumor size and cavernous sinus invasion 2003 Italy 26 Retrospective Unfavorable factors of persistent disease [18]
No histological evidence of adenoma 2007 US 490 Retrospective Lower remission rate [19]
Long-term hypocortisolism after surgery (≥13 m) 2017 India 230 Retrospective Favorable for remission
Sensitivity 46 %, specificity 100 %		 [20]
Greater decrease in BMI after surgery
Lower DHEAS before surgery		 2017 Taiwan 41 Retrospective Favorable factors for higher remission [21]
High serum ACTH/cortisol ratio before surgery 2018 Turkey 119 Retrospective Risk factor for disease recurrence [22]
USP8 mutation 2018 Germany 48 Retrospective Higher recurrence rate [23]
Serum cortisol < 107 nmol/L after betamethasone suppression test following surgery 2018 Sweden 28 Interventional Sensitivity 85 %, specificity 94 %
AUC 0.92		 [24]
Tumor visualization on MRI before surgery 2022 Spain 40 Retrospective Favorable factor for remission [25]
Abbreviations: ACTH − Adrenocorticotropic Hormone; AUC − Area Under the Curve; BMI − Body Mass Index; DHEAS − Dehydroepiandrosterone Sulfate; MRI − Magnetic Resonance Imaging; PoRP-CD − Persistent or Recurrent Cushing’s Disease; Preop − Preoperative; Postop − Postoperative; USP8 − Ubiquitin Specific Peptidase 8.
Several other studies aimed to explore the predictive value of single predictors. Braun et al. (2020) summarized the predictors for CD remission following TSS in a systematic review. Key predictors include pre-surgical identification of the tumor via MRI and the absence of adenoma invasion into the cavernous sinus. Postoperative hormonal levels, particularly low cortisol (< 2 µg/dL) and ACTH levels (< 3.3 pmol/L) as well as low cortisol levels (< 35 nmol/L) at 6–12 weeks post-surgery and sustained hypocortisolism requiring long-term replacement therapy, were significant indicators of remission. Additionally, post-surgical decreases in BMI contributed to favorable outcomes. Other reported predictors included a high level of surgical expertise, younger patient age, non-mutant USP8 corticotroph tumors, and swift recovery from postoperative adrenal insufficiency [5].
This study has certain limitations that should be acknowledged. The reliance on retrospective data may result in potential biases in variable selection and data completeness. While the model demonstrated good predictive accuracy, its limited sensitivity may restrict its ability to identify all high-risk patients. Moreover, the model has not been externally validated in independent cohorts, which limits its generalizability to other clinical settings. Despite these limitations, the study possesses significant strengths that underscore its contribution to the field. Applying one of the largest CD cohorts, it provides a robust statistical foundation and enhances the reliability of the findings. The comprehensive inclusion of diverse patient and tumor characteristics, imaging findings, and treatment details resulted in a clinically relevant and well-rounded predictive model. Notably, this model stands out for its applicability to a broader spectrum of patients, including those with prior surgeries or radiotherapy, addressing a gap left by earlier studies. Furthermore, the development of an online dynamic nomogram bridges the gap between research and clinical practice, allowing personalized predictions and aiding surgeons in making informed decisions before pituitary surgery.
Although this study incorporated long-term follow-up (median 58 months) to define persistence and recurrence and to internally validate the model, external validation in prospective, multi-institutional cohorts remains essential to confirm its broader applicability. Although the CuPeR model incorporates a wide array of clinical, radiological, biochemical, and demographic variables, other potential prognostic factors were not included and may warrant consideration in future studies. For instance, the presence of osteoporosis, degree of tumor invasion, and early recovery of the adrenal axis during the postoperative period have all been reported as relevant predictors of outcomes in Cushing’s disease [26]. Moreover, the role of surgical expertise is critical, as higher surgeon and institutional experience are strongly associated with improved remission and lower recurrence rates [27]. Incorporating novel parameters, such as genetic markers or advanced imaging techniques, could further enhance the predictive accuracy and clinical utility of the model. Prospective implementation of the nomogram in routine clinical workflows will provide valuable insights into its performance and its potential to improve patient outcomes.

Conclusions

This study introduced a practical, predictive model for estimating the risk of postoperative persistence and recurrence in Cushing’s disease, possibly offering a reliable tool for preoperative planning. By integrating key clinical predictors into an interactive online dynamic nomogram, the CuPeR model may provide surgeons with personalized risk assessments to aid in preoperative planning. Its focus on preoperative data ensures broader applicability, paving the way for tailored therapeutic strategies and improved patient outcomes in diverse clinical scenarios.

Funding details

None.

CRediT authorship contribution statement

Guive Sharifi: Supervision, Conceptualization. Elham Paraandavaji: Investigation, Data curation. Nader Akbari Dilmaghani: Investigation, Data curation. Tohid Emami Meybodi: Investigation, Data curation. Ibrahim Mohammadzadeh: Investigation, Data curation. Neginalsadat Sadeghi: Investigation, Data curation. Amirali Vaghari: Visualization. Behnaz Niroomand: Visualization. Seyed Mohammad Tavangar: Resources. Mohammad reza Mohajeri Tehrani: Validation. Zahra Davoudi: Resources. Marjan Mirsalehi: Writing – review & editing. Seyed Ali Mousavinejad: Validation, Resources. Farzad Taghizadeh-Hesary: Writing – review & editing, Writing – original draft.

Informed consent

Not applicable.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

None.
The data that support the findings of this study are available on request from the corresponding author.

References

https://www.sciencedirect.com/science/article/pii/S2214623725000353

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