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Updated: Sep 4, 2025

A Novel Method: Super-selective Adrenal Venous Sampling
Published on: September 15, 2017
Clinical Features and Risk Factors of Adrenal Insufficiency in Patients With Cancer Admitted to the
Min Kwan Kwon1,2, Junhwan Kim1,2, Jonghwa Ahn1,2,3
1Department of Internal Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Background:
The symptoms of adrenal insufficiency (AI) overlap with the common effects of advanced cancer and chemotherapy. Considering that AI may negatively affect the overall prognosis of cancer patients if not diagnosed in a timely manner, we analyzed the incidence, risk factors, and predictive methods of AI in cancer patients.
Methods:
We retrospectively analyzed the medical records of 184 adult patients with malignancy who underwent a rapid adrenocorticotrophic hormone stimulation test in the medical hospitalist units of a tertiary hospital. Their baseline characteristics and clinical features were evaluated, and the risk factors for AI were identified using logistic regression analysis.
Results:
Of the study patients, 65 (35%) were diagnosed with AI, in whom general weakness (63%) was the most common symptom. Multivariate logistic regression showed that eosinophilia (adjusted odds ratio [aOR], 4.28; 95% confidence interval [CI], 1.10-16.63; P = 0.036), history of steroid use (aOR, 2.37; 95% CI, 1.10-5.15; P = 0.028), and history of megestrol acetate use (aOR, 2.71; 95% CI, 1.38-5.33; P = 0.004) were associated with AI. Baseline cortisol levels of 6.2 μg/dL and 12.85 μg/dL showed a specificity of 95.0% and 95.4% for AI diagnosis, respectively.
Conclusion:
AI was found in about one-third of patients with cancer who showed general symptoms that may be easily masked by cancer or chemotherapy, suggesting that clinical suspicion of AI is important while treating cancer patients. History of corticosteroids or megestrol acetate were risk factors for AI and eosinophilia was a pre-test predictor of AI. Baseline cortisol level appears to be a useful adjunct marker for AI.
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