Clinical Outcome of Autonomous Cortisol Secretion in Adrenal Incidentalomas - Substudy of the ENSAT (European Network for the Study of Adrenal Tumor) Registry
Conditions: Adrenal Incidentaloma
Sponsor: Wuerzburg University Hospital

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Study protocol 
Clinical Outcome of Autonomous Cortisol Secretion in Adrenal Incidentalomas - 
Substudy of the ENSAT (European Network for the Study of Adrenal Tumor) Registry 
"NAPACA Outcome study" 
 
Clinicaltrial.gov number: NCT04917757 
 
Protocol version 1 December 2014 (updated 29 December 2016, and 4 October 2018) 
 
 
 
 

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Project outline and justification for data request 
 
1. Investigators 
1.1. 
Recipient Scientists, coordinators of the proposed project 
Massimo Terzolo and Martin Fassnacht 
 
1.2. 
Status of the Recipient Scientist 
Internal Medicine 1 
San Luigi Hospital  
Regione Gonzole 10 
10043 Orbassano (Italy) 
Tel. ++39 011 6705457 - ++39 011 9026788 
E-mail: terzolo@usa.net 
 
Division of Endocrinology and Diabetes 
Department of Internal Medicine I 
University Hospital Würzburg 
Oberdürrbacher Str. 6 
97080 Würzburg (Germany) 
Tel. ++49 931 201 39704 
E-mail: Fassnacht_M@ukw.de  
 
1.3. 
Associated Investigators 
Timo Deutschbein (Würzburg) 
Giuseppe Reimondo (Orbassano) 
 
2. Project 
2.1. 
Name of Project 
CLINICAL OUTCOMES OF AUTONOMOUS CORTISOL SECRETION IN ADRENAL 
INCIDENTALOMAS. 
 
2.2. 
Scientific context 
The natural history of adrenal incidentalomas is largely unknown. A number of recent studies 
have provided evidence for an increased rate of cardiovascular (CV) events and mortality in 
patients with adrenal incidentalomas and autonomous cortisol secretion. However, evidence 
comes from limited patient cohorts with rather short follow-up. Furthermore, a heterogeneous 
definition of autonomous cortisol secretion hampered to recognize which levels of functional 
autonomy are associated to increased morbidity and/or mortality. 
 
2.3. 
Aim 
The primary aim of the study is to assess mortality, CV events and the rate of vascular and 
metabolic comorbidities potentially linked to cortisol excess (hypertension, diabetes, 
dyslipidemia, obesity) in patients with adrenal incidentalomas and calculate HRs for patient 
groups stratified by cortisol values following the 1-mg overnight dexamethasone test. 
Two types of CV events are differentiated:  
• 
‘major CV events’: clinically symptomatic myocardial infarction or stroke followed by 
hospitalization, or CV-related death. 
• 
‘minor CV events’: any other type of myocardial infarction and therapeutic procedures for 
coronary heart disease (PTCA, surgical bypass), any stroke, transient ischemic attack, 
heart failure, deep vein thrombosis, pulmonary embolism. 

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CV events are optimally registered by hospital medical records reporting one (or more) of the 
followings: acute myocardial infarction and related therapeutic procedures (PTCA, surgical 
bypass), stroke, TIA, heart failure, deep vein thrombosis, pulmonary embolism, sudden death, 
or death from cardiovascular cause.  
However, it will be allowed to obtain data with telephonic interview using a structured 
questionnaire aimed to recognize the presence of the above-mentioned comorbidities and the 
occurrence of major CV events (clinically symptomatic myocardial infarction, stroke, death). 
 
We will assess: 
- 
Overall Survival (OS) as primary endpoint, defined as the time interval between the date 
of discovery of adrenal incidentaloma and the date of death from any cause, in patients 
stratified by different cortisol cut-offs. 
- 
Event-free Survival (ES), defined as the time interval between the date of discovery of 
adrenal incidentaloma and the date of occurrence of a ‘major’ and/or ‘minor’ CV event, in 
patients stratified by different cortisol cut-offs. 
- 
CV mortality, defined as death from any CV cause, in patients stratified by different 
cortisol cut-offs. Other causes of death will be specified, as well.  
 
2.4. 
Methods 
Retrospective, multi-center study 
CV events are optimally registered by hospital medical records or can be obtained with 
telephonic interview using a structured questionnaire aimed to recognize the presence of the 
above-mentioned comorbidities and the occurrence of CV events. 
 
Statistical analysis:  
 
CV event rates will be expressed as the number of events per 1000 person-years.  
Kaplan-Meier analysis will be used to construct survival curves and compute risks. Cox 
regression will be used for time-to-event analysis, and hazard ratios (HRs) computed with 
accompanying 95% confidence intervals (95% CI). Analysis will be stratified according to 
post-dexamethasone cortisol levels with three pre-specified cutoffs: ≤50 nmol/L (1.8 μg/dL), 
51-138 nmol/L (1.9-5.0 µg/dl) and >138 nmol/L (>5 μg/dL), However, additional cutoffs 
might be analysed as well.  
 
Depending on the level of comprehensive documentation of the patients’ characteristics two 
cohorts will be separately analysed:  
• 
Cohort A: all requested data are available 
• 
Cohort B: patients with missing data, but the following data are available: date of 
diagnosis the adrenal incidentaloma, result of 1mg DST, and survival status (or date of 
death).  
 
2.5. 
Requested clinical annotations (type, justification) 
Inclusion criteria: 
• 
Age ≥ 18 years 
• 
Adrenal mass detected by sensitive imaging tests (CT or MRI) not done for suspected 
adrenal disease since 1-1-2000 (modified in Oct 2018 to 1-1-1996 to allow longer 
follow-up time) 
• 
Imaging characteristics typical of adrenal adenoma: unenhanced or delayed enhanced 
CT, MRI with chemical shift and FDG-PET are all acceptable to secure this diagnosis. 

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In the absence of appropriate imaging study, results of 12-month follow-up showing 
unchanged mass characteristics can be considered as surrogate criterion. 
• 
Availability of 1-mg overnight dexamethasone test results done at diagnosis or during 
follow-up 
• 
Follow-up duration of at least 36 months (from the date of diagnosing the adrenal 
mass the first time) 
• 
Availability of follow-up data on living status and occurrence of CV events (telephone 
interview allowed to capture data)  
 
Exclusion criteria: 
 
• 
Presence of clinical features of overt Cushing’s syndrome 
• 
UFC ≥ 2 x ULN 
• 
ACTH-dependent Cushing syndrome 
• 
Any active malignancy 
 
Minimum clinical annotations: 
- 
Date of birth, date of diagnosis 
- 
Imaging characteristics (mass size, density on unenhanced CT (HU units), absolute or 
relative wash-out on delayed enhanced CT, results of MRI with chemical shift, results of 
FDG-PET, or imaging during follow-up > 12 months after initial imaging demonstrating 
unchanged tumor size) 
- 
Serum cortisol following 1-mg DST, UFC, plasma ACTH (only serum cortisol after 
dexamethasone will be entered into the statistical model) 
- 
Presence of obesity, hypertension, diabetes, dyslipidemia at initial diagnosis 
- 
Information on prevalent CV events 
- 
Date of last follow-up (date of death) 
- 
Presence of obesity, hypertension, diabetes, dyslipidemia at last follow-up 
- 
Information on incident CV events and date of first event 
 
Minimum expected patient cohort per center: 50 
 
Data acquisition via ENS@T registry   
 
2.6. 
Requested samples (type, justification of sample size) 
None 
 
2.7. 
Expected results 
To assess the existence of a relationship between risk of death and CV events with different 
levels of cortisol following an overnight 1-mg dexamethasone suppression test.  
 
2.8. 
Projected time frame 
Deadline for affirmation of participation in the study (e-mail to Fassnacht_m@ukw.de): 31-
10-2018 
 
Deadline for data acquisition: 31-11-2018 
Deadline for data analysis: 31-03-2019 
Expected manuscript submission: 31-12-2019 
Targeted Journals: depending on outcome 
 
3. Publication policy 
 

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1. Recipient scientist formally agrees with the provider(s) - at the time of the request or soon 
after the provider(s) have accepted the collaboration - the(ir) presence (if any) as co-authors in 
the publications originating from the collaboration.  
2. Number of authors per center and order of authorships are specified as a general rule as 
follows: 51-100: 1 author; 101-150: 2; 151-200: 3; 201-250: 4; 251-350: 5; 351-450: 6; 450-
600: 7. A minimum of 50 patients per center to qualify for authorship. 
3. The order of authors depends on the number of recruited patients per center. However, due to 
the work already done and their role in analysing the data, the following authorship positions 
are already predefined: Massimo Terzolo as first author, Martin Fassnacht as last author. The 
next 5 most attractive positions will be given to the 5 best recruiting centers and these centers 
can choose in downward order on the respective position. 
4. Depending on the contribution of each centre, or if number of authors has to be limited on the 
basis of a specific journal style, co-authors will be represented as “on behalf of ENS@T” and 
placed in an appropriate list depending on the Journal format (acknowledgment or 
collaborators list). In this case the recipient scientist will contact all provider(s) and obtain 
agreement.  
5. The authors agree to acknowledge ENS@T contribution: “This project has been supported by 
the European Network for the Study of Adrenal Tumors (ENS@T).”  
 
4. Conditions of data usage 
 
1. The Recipient scientist will use the data for research purposes only. 
2. The data will be used by the Recipient scientist solely in connection with the Research Project 
as outlined above. 
3. The Recipient scientist shall use the data in compliance with all applicable laws and 
government regulations of the Recipient's country.  
4. The Recipient Scientist shall not release the data to any person other than the personnel under 
the Recipient Scientist’s direct supervision. 
5. When the Research Project is completed, a detailed description of the use of the data will be 
made available to the appropriate ENS@T Working Group 
6. In the event that a journal publication or scientific article is published based on use of the data, 
the Recipient Scientist will send a copy of such publication, or the publication cite, promptly 
after it becomes available to the Recipient, to the appropriate ENS@T Working Group 
 
 
Date 
 
1 December 2014 (updated 29 December 2016, and 4 October 2018) 
 
Massimo Terzolo, Martin Fassnacht