Three Cases of Ectopic, Cyclic Cushing Syndrome: A New Square Wave Variant

Posted on November 3, 2025 by MaryO

Abstract

Cyclic Cushing syndrome (CCS) is characterized by unpredictable, intermittent phases of excess cortisol, alternating with periods of normal or subnormal adrenocorticotropic hormone (ACTH) and cortisol levels. The mechanism is unclear. Due to its rarity and diverse clinical presentation, unpredictable phases, and various etiologies, CCS poses significant diagnostic and management challenges for endocrinologists. The authors describe 3 cases in which each patient’s initial presentation was a life-threatening hypercortisolemic phase that lasted from 4 days to 3 months, followed by spontaneous resolution to prolonged eucortisolemic phases lasting from 10 to 26 months. Further testing indicated an ectopic ACTH-secreting source; however, the locations of the offending tumors were indeterminate. The authors propose the term square wave CCS variant to characterize the unique, prolonged intercyclic phases of hypercortisolemia and eucortisolemia with this subtype that are distinct from conventional CCS characterized by shorter phases of transient hypercortisolemia shifting to periods of eucortisolemia or hypocortisolemia. This uncharacteristic pattern of cyclicity poses diagnostic and therapeutic challenges, thus underscoring the importance of careful diagnostic workup and treatment of these patients.

Keywords: ectopic, cyclic, Cushing syndrome, eucortisolemia, hypercortisolemia

Introduction

Cyclic Cushing syndrome (CCS) is a rare variant of Cushing syndrome (CS) characterized by intermittent episodes of cortisol peaks alternating with variable periods of normal or subnormal adrenocorticotropic hormone (ACTH) and cortisol levels (troughs) []. These cycles can occur at regular or irregular intervals [], with unpredictable intercyclic phases typically lasting from days to months [, ]. The prevalence of CCS in patients with CS is low, ranging from 8% to 19% []. Several alternative terms (eg, intermittent, variable, periodic, and episodic hypercortisolism) have been proposed to characterize the variable cyclicity of ACTH and cortisol secretion in patients with CCS [].

We describe 3 cases of suspected ectopic ACTH-dependent CS with an indeterminate ACTH source that presented with life-threatening hypercortisolemia lasting from 4 days to 3 months, followed by spontaneous eucortisolemic phases lasting from 10 to 26 months. The term square wave is proposed to describe this unique cyclic pattern to highlight the unpredictability of severe hypercortisolemia followed by spontaneous prolonged eucortisolemic phases, which is distinct from previously described transient regular or irregular cycles with shorter intercyclic phases of CCS that require medical intervention.

Case Presentation

Case 1

A 75-year-old man with atrial fibrillation, bilateral leg edema, 6-month weight loss of 7 pounds (3.2 kg), and generalized muscle weakness was referred for cardiac ablation therapy. However, just before he underwent the procedure, he was found to be profoundly hypokalemic with potassium of 2.9 mEq/L (SI: 2.9 mmol/L) (reference range, 3.6-5.3 mEq/L [SI: 3.6-5.3 mmol/L]) and hyperglycemic, with blood glucose of 498 mg/dL (SI: 27.8 mmol/L) (reference range, 70-99 mg/dL [SI: 3.9-5.5 mmol/L]) and glycated hemoglobin (HbA1c) of 7.4%. He was emergently treated with potassium supplementation and insulin therapy.

Case 2

A 61-year-old woman presented to the emergency department with palpitations, uncontrolled hypertension, weight loss of 20 pounds (9.1 kg) over 2 weeks, new signs of hyperandrogenism (eg, hirsutism, acne, muscle atrophy), lower back pains, easy bruising, and proximal muscle weakness.

Case 3

A 57-year-old woman presented to the emergency department in August 2021 with a 2-month history of facial swelling and generalized muscle weakness. She had reported a similar episode in April 2019 with hypokalemia (potassium, 2.5 mEq/L [SI: 2.5 mmol/L]) that was treated with potassium repletion therapy.

Diagnostic Assessment

Case 1

Further laboratory tests revealed elevated morning (Am) cortisol of 76.8 µg/dL (SI: 2119 nmol/L) (reference range, 5-25 µg/dL [SI: 138-690 nmol/L]), Am ACTH of 368 pg/mL (SI: 81 pmol/L) (reference range, 6-50 pg/mL [SI: 1.3-11.0 pmol/L]), and 24-hour urine free cortisol (UFC) of 4223 µg/24 hours (SI: 11 656 nmol/24 hours) (reference range, 1.5-18.1 µg/24 hours [SI: 4-50 nmol/24 hours]) (Table 1). Magnetic resonance imaging (MRI) of the pituitary (Fig. 1) and 68Ga-DOTATATE positron emission tomography (PET) (Table 2) of the chest, pelvis, and abdomen failed to identify the source of ACTH secretion. Inferior petrosal sinus sampling (IPSS) showed no significant ACTH gradient, supporting the likelihood of an ectopic ACTH-secreting source (Table 3).

Table 1.

Summary of biochemical testing data for the 3 patients with a square wave pattern of cyclic Cushing syndrome

Test, reference range Patient 1 (male, 75 years) Patient 2 (female, 61 years) Patient 3 (female, 57 years)
IP EP IP EP IP EP
AM cortisol 5-23 µg/dL (138-690 nmol/L) 76.8 µg/dL (2119 nmol/L) 14.2 µg/dL (392 nmol/L) 38.4 µg/dL (1060 nmol/L) 17.9 µg/dL (494 nmol/L) 56.8 µg/dL (1568 nmol/L) 14.4 µg/dL (397 nmol/L)
AM ACTH 6-50 pg/mL (1.3-11.0 pmol/L) 368 pg/mL (81 pmol/L) 38.1 pg/mL (8.4 pmol/L) 118 pg/mL (26 pmol/L] 16.5 pg/mL (3.6 pmol/L) 159 pg/mL (35 pmol/L] 39 pg/mL (8.6 pmol/L)
PM cortisol 2.9-17.3 µg/dL (80-477 nmol/L) 57.8 µg/dL (1594 nmol/L) — — — — <0.05 µg/dL (<1.4 nmol/L)
24-h UFC 1.5-18.1 µg/24 hours (4-50 nmol/24 hours) 4223 µg/24 hours (11 656 nmol/24 hours) 10.5 µg/24 hours (29 nmol/24 hours) 52.9 µg/24 hours (146 nmol/24 hours) 13 µg/24 hours (36 nmol/24 hours) 670.5 µg/24 hours (1851 nmol/24 hours) 23 µg/24 hours (63 nmol/24 hours)
Post 1-mg DST cortisol <1.8 ng/dL (<50 nmol/L) 74.6 ng/dL (2059 nmol/L) — 26.9 ng/dL (743 nmol/L) 1.4 ng/dL (<50 nmol/L) 16.7 ng/dL (461 nmol/L) —
Salivary cortisol < 0.09 µg/dL (<2.5 nmol/L) — 0.08 µg/dL (2.2 nmol/L) — 0.04 µg/dL (1.1 nmol/L) — —
S-DHEA 7-162 µg/dL (0.19-4.37 µmol/L) — 63 µg/dL — — — —
Chromogranin A <311 ng/mL* (<311 µg/L) 725 ng/mL (30.6 nmol/L) — — — — —
Lipase 8-78 U/L 40.0 U/L (40.0 U/L) — — — — —
Hemoglobin A1c <5.7% 8.9% 5.9% 9.2% 5.9% — —

International System of Units are included within parentheses.

Dash (–) indicates that no data are available.

* Method dependent.

Abbreviations: ACTH, adrenocorticotropic hormone; AM, morning; DST, dexamethasone suppression test; EP, eucortisolemic phase; IP, initial presentation; PM, afternoon; S-DHEA, serum dehydroepiandrosterone; UFC, urine free cortisol.

Figure 1.

Figure 1.

Case 1. (A) Sagittal and (B) coronal magnetic resonance images demonstrating normal appearance of the pituitary gland. From Barrow Neurological Institute, Phoenix, Arizona.

Table 2.

Imaging workup summary

Case Imaging modalities Interpretation
Case 1 Pituitary MRI, CT chest/abdomen/pelvis, pelvic USG, 68Ga-DOTATATE PET/CT No ectopic ACTH-secreting source identified
Case 2 Pituitary MRI, CT chest/abdomen/pelvis, 68Ga-DOTATATE PET/CT No ectopic ACTH-secreting source identified
Case 3 Pituitary MRI, CT chest/abdomen/pelvis, pelvic USG, 68Ga-DOTATATE PET/CT No ectopic ACTH-secreting source identified

Abbreviations: ACTH, adrenocorticotropic hormone; CT, computed tomography; MRI, magnetic resonance imaging; PET, positron emission tomography; USG, ultrasound.

Table 3.

ACTH levels from inferior petrosal sinus sampling

Variable −5 Minutes 0 Minutes +2 Minutes +5 Minutes +10 Minutes
CASE 1
Right IPS 239 pg/mL (52.6 pmol/L) 221 pg/mL (48.6 pmol/L) 218 pg/mL (48.0 pmol/L) 239 pg/mL (52.6 pmol/L) 217 pg/mL (47.8 pmol/L)
Left IPS 226 pg/mL (49.8 pmol/L) 221 pg/mL (48.6 pmol/L) 216 pg/mL (47.6 pmol/L) 251 pg/mL (55.3 pmol/L) 213 pg/mL (46.9 pmol/L)
Peripheral 225 pg/mL (49.5 pmol/L) 219 pg/mL (48.2 pmol/L) 210 pg/mL (46.2 pmol/L) 217 pg/mL (47.8 pmol/L) 237 pg/mL (52.2 pmol/L)
Right IPS: peripheral ratio 1.06 1.00 1.03 1.10 .92
Left IPS: peripheral ratio 1.00 1.00 1.02 1.15 .89
CASE 2
Right IPS 59 pg/mL (13.0 pmol/L) 79 pg/mL (17.4 pmol/L) 203 pg/mL (44.7 pmol/L) 296 pg/mL (65.2 pmol/L) 374 pg/mL (82.3 pmol/L)
Left IPS 61 pg/mL (13.4 pmol/L) 77 pg/mL (17.0 pmol/L) 196 pg/mL (43.2 pmol/L) 313 pg/mL (68.9 pmol/L) 341 pg/mL (75.1 pmol/L)
Peripheral 62 pg/mL (13.7 pmol/L) 64 pg/mL (14.1 pmol/L) 146 pg/mL (32.2 pmol/L) 235 pg/mL (51.8 pmol/L) 368 pg/mL (81.0 pmol/L)
Right IPS: peripheral ratio .95 1.23 1.39 1.26 1.02
Left IPS: peripheral ratio .98 1.20 1.34 1.33 .93
CASE 3
Right IPS 119 pg/mL (26.1 pmol/L) 121 pg/mL (26.6 pmol/L) 380 pg/mL (83.8 pmol/L) 581 pg/mL (128.0 pmol/L) 232 pg/mL (51.2 pmol/L)
Left IPS 124 pg/mL (27.4 pmol/L) 133 pg/mL (29.3 pmol/L) 358 pg/mL (78.9 pmol/L) 568 pg/mL (125.0 pmol/L) 262 pg/mL (57.7 pmol/L)
Peripheral 113 pg/mL (24.9 pmol/L) 111 pg/mL (24.4 pmol/L) 322 pg/mL (70.9 pmol/L) 527 pg/mL (116.0 pmol/L) 178 pg/mL (39.1 pmol/L)
Right IPS: peripheral ratio 1.04 1.09 1.18 1.10 1.31
Left IPS: peripheral ratio 1.10 1.20 1.13 1.08 1.48

International System of Units are included within parentheses.

Baseline IPS: P > 2.0; Suggests pituitary (Cushing’s disease).

Post-stim IPS: P > 3.0; Confirms pituitary ACTH source.

Abbreviations: ACTH, adrenocorticotropic hormone; IPS, inferior petrosal sinus.

Case 2

Laboratory tests revealed elevated Am cortisol of 38.4 µg/dL (SI: 1060 nmol/L) and Am ACTH of 118 pg/mL (SI: 26 pmol/L), hypokalemia (potassium, 2.9 mEq/L [SI: 2.9 mmol/L]) and new-onset type 2 diabetes mellitus with a random blood glucose of 489 mg/dL (SI: 27.2 mmol/L) and HbA1c of 9.2% (reference range, < 5.7%) (Table 1). Lumbar spine radiography and spine MRI demonstrated compression fractures of L1 to L4 vertebrae, and pituitary MRI showed a 2-mm hypo-enhancing foci within the midline and to the right of the pituitary gland (Fig. 2).

Figure 2.

Figure 2.

Case 2. (A) Sagittal and (B) coronal magnetic resonance images of the pituitary gland show 2-mm hypo-enhancing foci (arrows) within the midline and to the right side of the pituitary gland. From Barrow Neurological Institute, Phoenix, Arizona.

Case 3

During the present hospital admission, the patient was hypokalemic (potassium, 2.7 mEq/L [SI: 2.7 mmol/L]) and hypercortisolemic with Am cortisol and Am ACTH levels of 56.8 µg/dL (SI: 1568 nmol/L) and 159 pg/mL (SI: 35 pmol/L), respectively. After 4 days of hospitalization, the patient spontaneously became eucortisolemic with an Am cortisol of 16.8 µg/dL (SI: 464 nmol/L), 24-hour UFC of 670.5 µg/24 hours (SI: 1851 nmol), and late-night salivary cortisol of 0.03 µg/dL (SI: 0.828 nmol/L) with symptom improvement (Table 1). Pituitary MRI revealed a flattened, normal-appearing pituitary gland (Fig. 3).

Figure 3.

Figure 3.

Case 3. (A) Sagittal and (B) coronal magnetic resonance images of the pituitary gland showing a flattened pituitary gland. No discrete, sizable, differentially enhancing mass is detected within the sella. From Barrow Neurological Institute, Phoenix, Arizona.

Treatment

Case 1

Because of the patient’s worsening clinical condition and severe hypercortisolemia with no identifiable ACTH source, ketoconazole was considered to induce eucortisolemia. While electrocardiography and liver function tests were being measured before starting ketoconazole, the patient’s Am cortisol levels spontaneously normalized to 14.2 µg/dL (SI: 392 nmol/L) with symptomatic improvement.

Case 2

The patient began insulin, spironolactone, and levothyroxine therapy. After 2 days in the hospital, her Am cortisol decreased to 17.9 µg/dL (SI: 494 nmol/L) and remained within the range of 9.4 to 17.9 µg/dL (SI: 259-494 nmol/L). An IPSS performed 3 weeks later showed no significant ACTH gradient, supporting the likelihood of an ectopic ACTH-secreting source. By month 3, her Am cortisol levels consistently remained below 15 µg/dL (SI: 414 nmol/L). Blood pressure was controlled with one antihypertensive agent, and insulin was discontinued due to frequent hypoglycemic episodes.

Case 3

The patient was readmitted 18 months later with worsening muscle weakness, uncontrolled hypertension, hypokalemia (potassium, 2.4 mEq/L [SI: 2.4 mmol/L]), and hypercortisolemia with elevated Am cortisol and Am ACTH levels. 68Ga-DOTATATE PET did not reveal an ectopic ACTH source (Table 2), and IPSS did not reveal any significant ACTH gradient (Table 3). However, computed tomography (CT) of the chest, abdomen, and pelvis revealed a 0.7-cm lung nodule. During this hospitalization, the patient received supportive treatment, including antihypertensive therapy and electrolyte replacement. No pharmacologic intervention was required to control her cortisol levels.

Outcome and Follow-Up

Case 1

Late-night salivary cortisol levels measured were within the normal range (0.08 µg/dL, 0.06 µg/dL, and 0.08 µg/dL [SI: 2.2 nmol/L, 1.7 nmol/L, and 2.2 nmol/L]; reference range, < 0.09 µg/dL [SI: < 2.5 nmol/L]). Because of these biochemical and symptomatic improvements, ketoconazole therapy was deferred. At the most recent outpatient clinic follow-up 26 months after his cortisol levels normalized, the patient remained in remission without recurrence of hypercortisolemic symptoms.

Case 2

The patient remained in biochemical and clinical remission for 15 months until she began experiencing abdominal distention, bilateral leg edema, and facial swelling again. Blood pressure increased at this time, requiring 3 antihypertensive medications. Her Am cortisol levels rose to 29.1 µg/dL (SI: 803 nmol/L), but repeat IPSS showed no ACTH gradient, and 68Ga-DOTATATE PET/CT of the chest, abdomen, and pelvis was unremarkable (Tables 2 and 3). Block-and-replace therapy of osilodrostat and hydrocortisone was initiated to preemptively prevent hypercortisolemic episodes; after 3 months of therapy, she underwent successful bilateral adrenalectomy (BLA).

Case 3

On day 5 of hospitalization, her Am cortisol level decreased to 14.4 µg/dL (SI: 397 nmol/L) (reference range, 5-25 µg/dL [SI: 138-690 nmol/L]). Her symptoms improved, and she remained well for 11 months before recurrence of muscle weakness, hypokalemia, and hypercortisolemia with an Am cortisol of 58.7 µg/dL (SI: 1620 nmol/L) and Am ACTH of 194 pg/mL (SI: 43 pmol/L). The patient became eucortisolemic without any medical intervention and declined further treatment. She continues with regular outpatient follow-up.

Discussion

Diagnosing CCS poses considerable challenges because of its heterogeneous clinical manifestations, erratic intercyclic duration, frequency of phases, and various etiologies. Patients may experience transient or continuous symptoms with variable degrees of severity []. Our patients presented with severe hypercortisolemia lasting from days to months, followed by an extended period of spontaneous eucortisolemia, lasting from months to years. This unique presentation of cortisol kinetics differs from the classic presentation of CCS, which typically features shorter intercyclic phases [].

We coined the term square wave variant of CCS to characterize this unique feature of prolonged cyclicity of hypercortisolemia shifting spontaneously to eucortisolemia without medical intervention. The term square wave was chosen because the cortisol secretion pattern in these cases resembles a square waveform, with abrupt transitions between prolonged periods of high and low cortisol levels rather than the gradual fluctuations or short irregular peaks seen in typical CCS. This visual and kinetic analogy helps distinguish the pattern observed in our patients from the more classically described forms of CCS.

The absence of a standardized definition of CCS complicates the classification of cases such as ours, which diverge from conventional descriptions in the medical literature [, , ]. Most cases of CCS are associated with pituitary tumors (67%), whereas ectopic ACTH-secreting tumors (17%) and adrenal tumors (11%) are less common [, ]. Our patients had evidence of ectopic CS, of which the ACTH-secreting source was unidentifiable despite extensive imaging. The variability of symptom duration, severity, and timing in our patients implies distinct mechanisms for suppressing or desensitizing adrenal cortisol synthesis during the extended symptom-free periods. Other mechanisms include enhanced effects of specific neurotransmitters, hypothalamic dysregulation, spontaneous tumor hemorrhage, cyclic growth and apoptosis of ACTH-secreting tumor cells, and positive and negative feedback mechanisms []. Another explanation for the prolonged eucortisolemic phase may be due to altered POMC gene expression and defective ACTH secretion from the ectopic tumor []. Over time, the tumor may dedifferentiate or develop a transcriptional or posttranscriptional defect, leading to the secretion of ACTH with a decreased ability to stimulate adrenal cortisol secretion [, ]. Conversely, CCS might also be an exaggerated physiological cyclical variation of ACTH and cortisol secretion [, ]. However, the prolonged eucortisolemic phase observed in our patients argues against this exaggeration theory.

Recent studies have suggested that the anomalous cyclicity of cortisol and ACTH may be influenced by dysregulation of the peripheral clock system in endocrine tumors []. Certain tumors may exhibit aberrant expression of circadian regulators such as CLOCK, PER1, PER2, PER3, and TIMELESS, which can disrupt the physiological rhythmicity of cortisol and ACTH secretion [, ]. For instance, cortisol-secreting adrenal adenomas demonstrate downregulation of PER1, CRY1, and Rev-ERB, whereas adrenocortical carcinomas upregulate CRY1 and PER1 and downregulate BMAL1 and RORα. In patients with CS, clock gene expression in peripheral blood mononuclear cells has been shown to be significantly flattened, contributing to the loss of circadian variation in cortisol levels [].

Surgery is the preferred treatment option for CCS patients, provided the tumor is localizable []. Medical therapy is used when the tumor is undetectable, unresectable, or recurs. Medical therapy can overtreat and induce iatrogenic adrenal insufficiency during the eucortisolemic phases. This risk can be mitigated by the block-and-replace strategy of high-dose steroidogenesis inhibitors to suppress adrenal cortisol production and supplemented with exogenous glucocorticoids []. In patients for whom the ectopic tumor is unidentifiable, the initial tumor resection is ineffective, or if medical management does not adequately control hypercortisolemia, BLA may be considered [].

Although treatment of CCS resembles that of CS, the heterogeneity in the severity and duration of symptoms prohibits the implementation of some conventional treatment strategies. Consequently, long-term medical therapy may not align with the patient’s preferences, especially those whose course of illness is characterized by prolonged eucortisolemia and milder symptoms. Such patients should be educated to monitor symptoms closely during the eucortisolemic phase to recognize the signs and symptoms of hypercortisolism using objective parameters such as self-assessment of weight, blood pressure, and capillary blood glucose. Periodic biochemical monitoring may also be helpful, including standby kits for self-testing of late-night salivary cortisol and 24-hour UFC. If the source of ectopic ACTH secretion continues to elude detection, BLA during the eucortisolemic phase may be considered to prevent future life-threatening hypercortisolemic episodes.

Learning Points

  • Unlike typical CCS, there may be a subset of patients with a distinct square wave variant of CCS marked by severe hypercortisolemia followed by prolonged periods of eucortisolemia.
  • Ectopic ACTH-secreting sources in CCS may be linked to unusually long symptom-free intervals of eucortisolemia and hypocortisolemia between episodes of hypercortisolemia.
  • If possible, CCS management should be individualized to address its cause, with vigilant monitoring during the eucortisolemic phase to detect potential recurrence early.
  • If the source of the ectopic ACTH-secreting tumor is not identifiable, BLA may be considered during the eucortisolemic phase to prevent future life-threatening hypercortisolemic episodes.

Acknowledgments

We thank the staff of Neuroscience Publications at Barrow Neurological Institute for assistance with manuscript preparation.

Abbreviations

ACTH
adrenocorticotropic hormone
BLA
bilateral adrenalectomy
CCS
cyclic Cushing syndrome
CS
Cushing syndrome
CT
computed tomography
HbA1c
glycated hemoglobin
IPSS
inferior petrosal sinus sampling
MRI
magnetic resonance imaging
PET
positron emission tomography
UFC
urine free cortisol

Contributor Information

Mercedes Martinez-Gil, Department of Internal Medicine, Creighton University School of Medicine, Phoenix, AZ 85012, USA.

Tshibambe N Tshimbombu, Department of Neurology, Barrow Neurological Institute, St. Joseph’s Hospital and Medical Center, Phoenix, AZ 85013, USA.

Yvette Li Yi Ang, Division of Endocrinology, Department of Medicine, National University Hospital, Singapore 119228, Singapore.

Monica C Rodriguez, Barrow Pituitary Center, Barrow Neurological Institute, University of Arizona College of Medicine and Creighton University School of Medicine, Phoenix, AZ 85012, USA.

Kevin C J Yuen, Barrow Pituitary Center, Barrow Neurological Institute, University of Arizona College of Medicine and Creighton University School of Medicine, Phoenix, AZ 85012, USA.

Contributors

All authors contributed substantially to the manuscript. K.C.J.Y. supervised the project, provided content review, and edited the text. M.M.-G. and T.N.T. contributed equally to the preparation, writing, and submission of the manuscript. M.C.R. was responsible for the clinical management of one of the cases. Y.L.Y.A. contributed to the diagnosis, management, and writing of one of the cases. All authors reviewed and approved the final version of the manuscript.

Funding

All authors declare that they have no known competing financial interests or personal relationships that could appear to influence the work reported in this manuscript.

Disclosures

The authors have no personal, financial, or institutional interest in any of the drugs, materials, or devices described in this manuscript.

Informed Patient Consent for Publication

Signed informed consents were obtained directly from the patients.

Data Availability Statement

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

https://pmc.ncbi.nlm.nih.gov/articles/PMC12559019/

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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/).

  1. Download: Download high-res image (97KB)
  2. Download: Download full-size image

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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  2. Download: Download full-size image

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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Risk Comparison and Assessment Model of Deep Vein Thrombosis in Patients with Pituitary Adenomas After Surgery

Posted on October 22, 2025 by MaryO

Abstract

Background

Deep vein thrombosis (DVT), a major component of venous thromboembolism (VTE), is a common postoperative complication. Its occurrence after pituitary adenoma surgery is influenced by multiple factors.

Methods

This retrospective study analyzed 1440 pituitary adenoma cases treated at Beijing Tiantan Hospital (2018–2023). The incidence of postoperative DVT was recorded, and logistic regression was used to identify associated risk factors. Differences across pituitary adenoma subtypes were compared. Additionally, Regression and machine learning models were developed to predict DVT.

Results

Among 397 patients who underwent postoperative lower limb ultrasound, 104 (7.2 %) developed DVT. Significant risk factors included advanced age, higher body mass index (BMI), intravenous cannulation, prolonged hospital stay, shorter preoperative activated partial thromboplastin time (APTT), longer thrombin time (TT), elevated platelet count, and higher postoperative D-dimer levels. Patients with Cushing’s disease exhibited a significantly higher DVT incidence, potentially related to decreased pre- and postoperative APTT and PT/INR values. Conversely, patients with prolactin-secreting adenomas had a lower DVT incidence, possibly due to younger age and higher postoperative PT values. A support vector machine (SVM) model showed strong predictive performance (AUC: 0.82; accuracy: 86.08 %; specificity: 96.72 %).

Conclusion

DVT incidence varies by pituitary adenoma subtype. Machine learning enhances predictive models for postoperative DVT in pituitary adenoma patients.

Introduction

Venous thromboembolism (VTE), encompassing both deep vein thrombosis (DVT) and pulmonary embolism, is a common cardiovascular disorder. It typically presents with clinical symptoms such as lower limb swelling, chest pain, tachypnea, and, in severe cases, may result in fatal outcomes [1]. The development of VTE is influenced by three factors known as the Virchow triad: altered venous blood flow, endothelial or vessel wall damage, and hypercoagulability [2]. Surgical procedures can increase the risk of VTE, particularly DVT in the lower extremities, due to intraoperative injuries and postoperative hemodynamic changes [[3], [4], [5]]. In the absence of anticoagulant prophylaxis, the incidence of VTE following brain tumor surgery ranges from 3 % to 30 % [[6], [7], [8]]. Although pituitary adenomas are commonly considered benign cranial tumors, emerging evidence suggests that patients undergoing resection of pituitary adenomas may have a higher risk of postoperative VTE compared to those with other sellar or parasellar tumors such as craniopharyngiomas, meningiomas, or chordomas [9].
This disparity may be attributed to the unique hormone secretion functions of pituitary adenomas, as well as dysregulation of water and electrolyte balance—following surgery. Despite this, the risk factors contributing to the development of postoperative VTE in pituitary adenomas have not been extensively explored. Limited studies have identified a particularly elevated VTE risk in patients with Cushing’s disease, a hormone-secreting subtype of pituitary adenoma [10]. Given the relatively high incidence of postoperative DVT in this population, the present study aims to systematically investigate risk factors associated with lower extremity DVT after pituitary adenoma surgery. Furthermore, we seek to compare thrombotic risk across different clinical subtypes of pituitary adenomas and to construct a tailored risk prediction model to guide perioperative thromboprophylaxis in affected patients.

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Sleep Disturbances in Patients With Cushing Syndrome and Mild Autonomous Cortisol Secretion

Posted on October 16, 2025 by MaryO

The Journal of Clinical Endocrinology & Metabolism, dgaf553, https://doi.org/10.1210/clinem/dgaf553

Abstract

Context

The impact of active hypercortisolism on sleep is incompletely characterized. Studies report impaired sleep in patients with Cushing syndrome (CS). Patients with mild autonomous cortisol secretion (MACS) demonstrate mild nocturnal hypercortisolism that could impact sleep.

Objectives

To characterize sleep abnormalities in patients with CS and MACS using the Pittsburgh Sleep Quality Index (PSQI), identify factors associated with poor sleep, and compare sleep abnormalities in patients with MACS versus referent subjects.

Methods

We conducted a single-center cross-sectional study of adults with active CS and MACS. Clinical and biochemical severity scores for hypercortisolism were calculated. Parallelly, we enrolled referent subjects. Quality of life was assessed using 1) Short Form-36 in all participants, and 2) Cushing QoL in patients with active hypercortisolism. Sleep quality was assessed using PSQI.

Results

PSQI was assessed in 154 patients with CS (mean 12, SD ±4.5), 194 patients with MACS (mean 11, SD 4.6), and 89 referents (mean 5, SD ±3.4). Patients with MACS exhibited shorter sleep duration, longer sleep latency, more severe daytime dysfunction, lower sleep efficiency, and a higher sleep medication use compared to referent subjects (P = <0.001 for all). Age-, sex, and BMI adjusted analysis demonstrated no differences in PSQI or its subcomponents between patients with CS and MACS (P >0.05 for all). In a multivariable analysis of patients with MACS, younger age, female sex and higher clinical hypercortisolism severity score were associated with impaired sleep. In patients with CS, only younger age was associated with poor sleep.

Conclusions

Patients with MACS demonstrate sleep impairment that is similar to patients with CS. Younger women with higher clinical severity of MACS are more likely to have impaired sleep.

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A Silent Invader: Asymptomatic Rhodococcus Infection Unmasked In a Patient With Ectopic ACTH-Dependent Cushing’s Syndrome

Posted on October 8, 2025 by MaryO

Introduction: Rhodococcus species, particularly Rhodococcus equi, are rare opportunistic pathogens that typically affect immunocompromised individuals. These infections usually present with respiratory or systemic symptoms and are often linked to environmental exposure. Asymptomatic Rhodococcus infections are exceedingly rare and pose unique diagnostic and therapeutic challenges.

Case description: We report the case of a 29-year-old male who presented with new-onset diabetes mellitus, resistant hypertension and significant weight gain. Physical examination revealed features consistent with Cushing’s syndrome. Biochemical evaluation confirmed ACTH-dependent hypercortisolism with an elevated plasma ACTH level, and a lack of suppression on high-dose dexamethasone testing; imaging identified a suspicious pulmonary nodule. Bronchoscopic biopsy revealed no malignancy, however cultures grew Rhodococcus species. The patient denied any respiratory symptoms or environmental exposure. Initial antibiotic therapy with ciprofloxacin and rifampin was started. Follow-up imaging showed rapid enlargement of the pulmonary mass, prompting surgical resection. Histopathology revealed malakoplakia, and repeat cultures again yielded Rhodococcus spp. Antibiotics were adjusted to azithromycin and rifampin, and the patient was started on ketoconazole to manage hypercortisolism.

Conclusion: This case highlights the importance of considering opportunistic infections such as Rhodococcus spp. in immunocompromised patients, even in the absence of symptoms. It underscores the diagnostic value of investigating incidental findings in such populations and illustrates the need for prompt, multidisciplinary management to prevent disease progression.

References

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From https://www.ejcrim.com/index.php/EJCRIM/article/view/5711

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

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