Clinical Trial: Structured Evaluation of adRENal Tumors Discovered Incidentally - Prospectively Investigating the Testing Yield

Study Status: Recruiting
Recruit Status: Recruiting
Study Type: Observational [Patient Registry]

Official Title: Structured Evaluation of adRENal Tumors Discovered Incidentally - Prospectively Investigating the Testing Yield

Brief Summary: Standard diagnostic work-up for adrenal incidentalomas (AI) consists of periodical biochemical analysis and CT-scanning in case the initial work-up does not demonstrate the presence of hormonal hypersecretion or adrenocortical carcinoma (ACC), respectively. The overall aim of this study is to improve the cost-effectiveness of the diagnostic strategy for AI. Cost-effectiveness of urine steroid profiling (USP) will be compared to the standard diagnostic strategy of repeated CT-imaging.

Detailed Summary:

Rationale: Standard diagnostic work-up for adrenal incidentalomas (AI) consists of periodical biochemical analysis and CT-scanning in case the initial work-up does not demonstrate the presence of hormonal hypersecretion or adrenocortical carcinoma (ACC),respectively. With respect to the diagnosis of ACC, the health benefits of this strategy are controversial for the following reasons: a. critical appraisal of literature has revealed a much lower ACC frequency of 1.9% than previously presumed; b. CT sensitivity and specificity are suboptimal; c. risk of unnecessary adrenalectomies; d. exposure to ionising radiation; e. risk of CT contrast reactions (nephropathy, allergic reaction); f. health care related and economical costs. The hypothesis to be tested is that incorporation of a single baseline urinary steroid profiling (USP) into the management algorithm of AI is more cost-effective than a strategy solely based on repeat CT-scanning.

Objective: SERENDIPITY aims to improve the cost-effectiveness of the diagnostic strategy for AI by the application of a single baseline USP. In addition, we aim to examine the psychological impact for patients with AI being currently subjected to repeated laboratory tests and CT-scanning during several years.

Study design: This is a prospective observational multicenter study. Study population: Patients are eligible if they meet the following inclusion criteria: adrenal mass > 1 cm in diameter incidentally discovered during CT or MRI-scanning, performed for reasons other than an evaluation for adrenal disease and age 18 years or older. The exclusion criteria are: extra-adrenal malignancy (i.e. active or past medical history of malignancy, except for basal cell carcinoma), radiologic diagnosis of simple cyst or bilateral adrenal masses, allergy to radiocontrast, renal insufficiency (i.e. eG
Sponsor: University Medical Center Groningen

Current Primary Outcome: Cost-effectiveness [ Time Frame: 2 years ]

difference in cost-effectiveness of the current management strategy based on repeat CT-scanning to detect ACC among patients with an AI compared with a strategy using a single baseline USP


Original Primary Outcome: Same as current

Current Secondary Outcome:

  • frequency of ACC among patients with AI at baseline or during follow-up [ Time Frame: 2 years ]
  • determination of the percentage of AI that meets the criteria of a malignant CT- phenotype at baseline or during follow-up [ Time Frame: 2 years ]
  • distribution of pathologic diagnosis in surgically removed adrenal glands [ Time Frame: 2 years ]
  • QoL in patients with an AI at baseline and during follow-up [ Time Frame: 2 years ]
  • frequency distribution between hormonal hypersecreting and non-functional AI [ Time Frame: 2 years ]
  • conversion rate from non-functioning AI towards a hypersecreting AI during follow-up [ Time Frame: 2 years ]
  • costs of diagnostic procedures and surgical interventions [ Time Frame: 2 years ]


Original Secondary Outcome: Same as current

Information By: University Medical Center Groningen

Dates:
Date Received: December 19, 2014
Date Started: January 2015
Date Completion: January 2019
Last Updated: October 25, 2016
Last Verified: October 2016