A Modern Assessment of Cancer Risk in Adrenal Incidentalomas

医学 霍恩斯菲尔德秤 肾上腺切除术 入射(几何) 肾上腺皮质癌 逻辑回归 回顾性队列研究 弗雷明翰风险评分 风险评估 放射科 内科学 外科 核医学 计算机断层摄影术 光学 计算机科学 疾病 计算机安全 物理
作者
Bora Kahramangil,Emin Köse,Erick M. Remer,Jordan Reynolds,Robert J. Stein,Brian Rini,Allan Siperstein,Eren Berber
出处
期刊:Annals of Surgery [Lippincott Williams & Wilkins]
卷期号:275 (1): e238-e244 被引量:67
标识
DOI:10.1097/sla.0000000000004048
摘要

Objective: The aim of this study was to analyze the incidence of and risk factors for adrenocortical carcinoma (ACC) in adrenal incidentaloma (AI). Summary of Background Data: AI guidelines are based on data obtained with old-generation imaging and predominantly use tumor size to stratify risk for ACC. There is a need to analyze the incidence and risk factors from a contemporary series. Methods: This is a retrospective review of 2219 AIs that were either surgically removed or nonoperatively monitored for ≥12 months between 2000 and 2017. Multivariate logistic regression was performed to define risk factors. ROC curves constructed to determine optimal size and attenuation cut-offs for ACC. Results: 16.8% of AIs underwent upfront surgery and rest initial nonoperative management. Of conservatively managed patients, an additional 7.7% subsequently required adrenalectomy. Overall, ACC incidence in AI was 1.7%. ACC rates by size were 0.1%, 2.4%, and 19.5% for AIs of <4, 4 to 6, and >6 cm, respectively. The optimal size cut-off for ACC in AI was 4.6 cm. ACC risks by Hounsfield density were 0%, 0.5%, and 6.3% for lesions of <10, 10 to 20, and >20 HU, with an optimal cut-off of 20 HU to diagnose ACC. 15.5% of all AIs and 19.2% of ACCs were hormonally active. Male sex, large tumor size, high Hounsfield density, and >0.6 cm/year growth were independent risk factors for ACC. Conclusion: This contemporary analysis demonstrates that ACC risk per size in AI is less than previously reported. Given these findings, modern management of AIs should not be based just on size, but a combination of thorough hormonal evaluation and imaging characteristics.
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