4.5 Article Proceedings Paper

Risk Estimator for Adrenal Tumor Functionality

Journal

WORLD JOURNAL OF SURGERY
Volume 38, Issue 8, Pages 2019-2024

Publisher

SPRINGER
DOI: 10.1007/s00268-014-2524-0

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Adrenal lesions are a common imaging finding with a prevalence approaching 10 %. Although guidelines recommend dedicated laboratory tests to rule out tumor functionality, many patients never undergo this workup. This study investigates the use of demographic and clinical variables to create an easy scoring system for predicting adrenal tumor functionality (functional adrenal tumors, or FATs). Altogether, 2,807 patients in the NSQIP 2005-2010 database underwent adrenalectomy as their principal operation and had a postoperative diagnosis consistent with an adrenal lesion/disorder. Patients were divided into two groups based on a postoperative diagnosis consistent with tumor functionality. Univariate and multivariate logistic regression analyses were performed to identify specific predictors of FATs and for Cushing's, Conn's, or pheochromocytoma. Overall, 13.2 % (n = 402) of adrenalectomies performed were for FATs. Patients with a FAT were younger (age < 40, p < 0.01), overweight (BMI > 30 kg/m(2), p < 0.01), hypertensive (p < 0.001). They also had elevated white blood cells (WBC > 11, p < 0.001), serum creatinine (Cr > 1.25 mg/dl, p < 0.001), and sodium (Na > 143 mmol/L, p < 0.001). On multivariate regression, patients with these characteristics were 20.53 times (CI 15.79-25.27) more likely to have a FAT (model c-statistic 0.634, CI 0.605-0.663; Hosmer-Lemeshow test (H-L), p = 0.035). Patients who were younger (p < 0.001), female (p < 0.001), diabetic (p = 0.07), overweight (p = 0.027), with elevated WBCs (p < 0.001) and lower Cr (p < 0.001) were 63.62 times (CI 58.03-69.21) more likely to have Cushing's (model c-statistic 0.685, CI 0.648-0.722; H-L p = 0.954). After external validation, this risk estimator might be used to quantify the probability of tumor functionality in patients with incidental adrenal masses. Although predictive power may be limited, it helps identify patients at high risk for FATs that need more urgent referral to a specialist.

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