- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT04788927
Development of a Predictive Model for the Risk of Metastatic Disease in PPGLs, a Retrospective Cohort Study (PPGL-Pred)
Development of a Comprehensive Predictive Model for Risk of Metastatic Disease in PPGLs Based on a Combination of Clinical, Biochemical, Genetic, and Pathoanatomical Characteristics a Retrospective National Cohort Study
Study Overview
Status
Detailed Description
Phaeochromocytomas and paragangliomas (PPGLs) are tumours of the adrenal medulla and extra-adrenal sympathetic nervous system, respectively, that often secrete catecholamines(1). The tumours are derived from the neural crest and approximately 50% are caused by a germline variant. Because of the strong heritability, genetic testing is recommended in all patients with PPGLs (2-5). Most PPGLs are non-malignant (defined as non-metastatic) tumours and respond well to surgical treatment. Approximately 15% of PPGLs are metastatic and incurable by currently available therapies(1). The latest WHO Blue Book classifies all PPGLs as possibly malignant due to their unpredictable behaviour(6).
PPGLs are very heterogeneous tumours predisposed by more than 20 distinct genes(1). In two thirds of the tumours a germline or somatic variant can be identified and thus PPGLs have been divided into distinct biological subgroups on the basis of these variants(1). A consensus statement from 2017 stated the necessity for a targeted gene panel (Next-Generation Sequencing, NGS) in all PPGL patients and testing of tumour DNA if possible to identify potential future targets for drug therapies(2). Furthermore, epigenetic changes in PPGLs and other endocrine tumours have been shown to be associated with the risk of metastatic disease(7-11) and future research should be focused on understanding both epigenetic and genetic changes in PPGLs as this will open opportunities for targeted molecular therapies and personalized medicine(11,12). It has been demonstrated that DNA methylation-based tumour classification is a valuable asset for clinical decision making(13).
Many histopathological predictive risk factors for poor prognosis have been proposed and scoring systems have been developed to identify those PPGLs that have a metastatic potential. The PASS (Pheochromocytoma of the Adrenal Gland Scaled Score) and GAPP (Grading system for Adrenal Phaeochromocytoma and Paraganglioma) scores are the most well-known (1,14-18). In a recent meta-analysis the algorithms were evaluated and it was concluded that both algorithms had a low positive predictive value but a high negative predictive value for PPGLs which indicated that the models were relevant for ruling out metastatic potential for both tumour types rather than identifying cases with an increased risk of disseminated disease. This could most probably be attributed to subjective assessment of criteria involved in these scoring systems. The authors concluded that the inclusion of NGS data and an overall molecular approach is needed to accurately pinpoint cases at risk for future metastases(19). Furthermore, there is a need for an algorithm based on objective measurements to ensure objectivity in the pathological diagnosis of PPGLs, similar to algorithms for adrenocortical carcinomas like the Helsinki Score and the Reticulin Algorithm(19-21). To this end computer-assisted techniques have shown promising results(11,20).
Correctly identifying PPGLs with a future risk of metastatic disease is a clinical challenge which impacts not only the physicians but also the patients and their family members. Today's clinical guidelines are based on 'rule all in' methods which have a costly impact on the healthcare resources and the quality of life of the patients. An algorithm based on histopathological, genetic, epigenetic, and clinical variables may be helpful in stratifying patients into risk categories with different needs for clinical follow-up.
Pilot Study: Patients followed at Copenhagen University Hospital, Copenhagen have been part of a pilot study on the effect of genetic screening of family members with SDHX variants on the clinical presentation of cases. Variants of the SDHX (SDHA, -AF2, -B, -C, -D) genes are a frequent cause of familial PPGLs. The investigators found distinct differences in the clinical and histopathological characteristics between genetic variants in SDHB. Family screening for SDHB variants resulted in earlier detection of tumours in two families. Patients with SDHA, SDHC and SDHD variants also had severe phaenotypes, underlining the necessity for a broad genetic screening of the proband. The study corroborated previous findings of poor prognostic markers and found that the genetic variants and clinical phenotype are linked and therefore useful in the decision of clinical follow-up. This study has been presented as master thesis at the University of Copenhagen 2019 (Grade A) and the manuscript has been published(22). The study corroborates the feasibility of the current project.
Process of the study
Part 1: Description of the genotype-phaenotype association in a nation-wide cohort of approximately 400 patients with PPGLs or germ-line genetic variants predisposing to PPGLs using clinical data, biochemical variables, tumour characteristics and imaging results. This national cohort will provide characterization of patients making it possible to identify a metastatic and non-metastatic clinical course, respectively.
Part 2: Identification of novel prognostic biomarkers using formalin-fixed paraffin-embedded tumor tissue samples for genetic testing (NGS for somatic variants), DNA methylation, PASS scoring, and immunohistochemical markers. Twenty patients with a poor prognosis (proof of metastases) and 20 patients with a good prognosis (non-metastatic) will be included from the Capital Region of Denmark. The results will be used to develop a new algorithm for clinical prognosis.
Part 3: Validation of the new algorithm in a second subcohort of patients with tumor tissue specimens selected at random from the national cohort. Tumor specimens will be subjected to investigation of the same novel prognostic biomarkers identified in part 2. Results will be entered into the new algorithm to test whether the clinical course can be accurately predicted.
Dissemination Positive, negative or inconclusive results will be published in peer-reviewed international journals and presented at scientific meetings and in relevant patient fora. The study group members are affiliated to ENDO-ERN (European Reference Network on Rare Endocrine Conditions), a European collaboration of highly specialized centres treating rare endocrine conditions through which results can be disseminated (https://endo-ern.eu/).
To ensure completeness and transparency in the reporting of results the investigators will use the STROBE reporting guidelines relevant to cohort studies.
Patient involvement:
Patients with lived experiences contribute additional expertise and give valuable, novel insights and thus improve the effectiveness of the study. Furthermore, the patient perspective is essential in the presentation of the results. Relevant patients with the disease in question from our outpatient clinic will be invited to participate in the Steering Committee.
Safety and ethical considerations Treatment of personal data: General Data Protection Regulation will be strictly adhered to. Approval by the Ethics Committee for the Capital Region has been granted (H-20065699, 19th of February 2021).
Database: The database will be established under RedCap, which is accessible nation-wide and managed centrally by the data protection unit of The Capital Region.
Statistics: Based on previous studies which have developed similar algorithms (20,21) the investigators will need approximately 200 patients to achieve statistical power in relation to validation of the algorithm in the larger cohort. Study population characteristics will be presented using descriptive statistics. Group differences will be tested primarily using non-parametric tests (Mann-Whitney, Wilcoxon) or t-test. Associations between the genotype and phaenotype will be analysed by ANOVA (analysis of variance) and regression analysis controlling for relevant confounders, i.e. age and sex, where appropriate. The sensitivity and specificity of the algorithm to predict poor or good outcome will be determined using multiple regression analyses, Chi2 and ROC (Receiver Operating Characteristics). The investigators will seek help from professional statisticians at Copenhagen University at Statistical Advisory Service for PhD-students and students at the Faculty of Health Sciences.
Study Type
Enrollment (Anticipated)
Contacts and Locations
Study Contact
- Name: Ulla Feldt-Rasmussen, Professor
- Phone Number: +45 35451023
- Email: ufeldt@rh.dk
Study Contact Backup
- Name: Ailsa Maria Main, MD
- Phone Number: +45 27125249
- Email: ailsa.maria.main.02@regionh.dk
Study Locations
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Copenhagen, Denmark, 2100
- Rigshospitalet
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Copenhagen, Denmark, DK-2100
- National University Hospital, Department of Medical Endocrinology
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Location: Nation-wide cohort of all patients followed in one of the tertiary hospitals: Copenhagen (Rigshospitalet), Århus (Skejby) and Odense University hospital.
Identification: The patients will be retrieved from the National Danish Registry of Hospital Diagnoses by use of their national identification number (CPR).
Description
Inclusion Criteria:
- All Danish patients diagnosed with PPGLs or genetic variants that predispose to PPGLs since 1996 will be included.
Exclusion Criteria:
- None from the initial data collection. If there are no tumour tissue or blood samples from a patient in the biobanks they will subsequently be excluded.
Study Plan
How is the study designed?
Design Details
- Observational Models: Cohort
- Time Perspectives: Retrospective
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Malignant or non-malignant disease
Time Frame: 25 ys (1996-2021) retrospective data collection of approximately 400 patients until death or until today.
|
Defined as metastatic disease
|
25 ys (1996-2021) retrospective data collection of approximately 400 patients until death or until today.
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Collaborators and Investigators
Sponsor
Investigators
- Principal Investigator: Ulla Feldt-Rasmussen, Prof., Dr. med., Rigshospitalet, Denmark
Publications and helpful links
General Publications
- Nicolas M, Dahia P. Predictors of outcome in phaeochromocytomas and paragangliomas. F1000Res. 2017 Dec 21;6:2160. doi: 10.12688/f1000research.12419.1. eCollection 2017.
- Pacak K, Tella SH. Pheochromocytoma and Paraganglioma. In: De Groot LJ, Chrousos G, Dungan K, et al., eds. Endotext. South Dartmouth MA: MDText.com, Inc.; 2000
- Plouin PF, Amar L, Dekkers OM, Fassnacht M, Gimenez-Roqueplo AP, Lenders JW, Lussey-Lepoutre C, Steichen O; Guideline Working Group. European Society of Endocrinology Clinical Practice Guideline for long-term follow-up of patients operated on for a phaeochromocytoma or a paraganglioma. Eur J Endocrinol. 2016 May;174(5):G1-G10. doi: 10.1530/EJE-16-0033.
- Lloyd RV OR, Klöppel G, Rosai J. WHO Classification of Tumours of Endocrine Organs 4th ed. Lyon IARC; 2017
- Oishi T, Iino K, Okawa Y, Kakizawa K, Matsunari S, Yamashita M, Taniguchi T, Maekawa M, Suda T, Oki Y. DNA methylation analysis in malignant pheochromocytoma and paraganglioma. J Clin Transl Endocrinol. 2016 Dec 23;7:12-20. doi: 10.1016/j.jcte.2016.12.004. eCollection 2017 Mar.
- Lee SE, Oh E, Lee B, Kim YJ, Oh DY, Jung K, Choi JS, Kim J, Kim SJ, Yang JW, An J, Oh YL, Choi YL. Phenylethanolamine N-methyltransferase downregulation is associated with malignant pheochromocytoma/paraganglioma. Oncotarget. 2016 Apr 26;7(17):24141-53. doi: 10.18632/oncotarget.8234.
- Backman S, Maharjan R, Falk-Delgado A, Crona J, Cupisti K, Stalberg P, Hellman P, Bjorklund P. Global DNA Methylation Analysis Identifies Two Discrete clusters of Pheochromocytoma with Distinct Genomic and Genetic Alterations. Sci Rep. 2017 Mar 22;7:44943. doi: 10.1038/srep44943.
- Jouinot A, Assie G, Libe R, Fassnacht M, Papathomas T, Barreau O, de la Villeon B, Faillot S, Hamzaoui N, Neou M, Perlemoine K, Rene-Corail F, Rodriguez S, Sibony M, Tissier F, Dousset B, Sbiera S, Ronchi C, Kroiss M, Korpershoek E, de Krijger R, Waldmann J, K D, Bartsch, Quinkler M, Haissaguerre M, Tabarin A, Chabre O, Sturm N, Luconi M, Mantero F, Mannelli M, Cohen R, Kerlan V, Touraine P, Barrande G, Groussin L, Bertagna X, Baudin E, Amar L, Beuschlein F, Clauser E, Coste J, Bertherat J. DNA Methylation Is an Independent Prognostic Marker of Survival in Adrenocortical Cancer. J Clin Endocrinol Metab. 2017 Mar 1;102(3):923-932. doi: 10.1210/jc.2016-3205.
- Jouinot A, Bertherat J. MANAGEMENT OF ENDOCRINE DISEASE: Adrenocortical carcinoma: differentiating the good from the poor prognosis tumors. Eur J Endocrinol. 2018 May;178(5):R215-R230. doi: 10.1530/EJE-18-0027. Epub 2018 Feb 23.
- Pang Y, Liu Y, Pacak K, Yang C. Pheochromocytomas and Paragangliomas: From Genetic Diversity to Targeted Therapies. Cancers (Basel). 2019 Mar 28;11(4):436. doi: 10.3390/cancers11040436.
- Capper D, Jones DTW, Sill M, Hovestadt V, Schrimpf D, Sturm D, Koelsche C, Sahm F, Chavez L, Reuss DE, Kratz A, Wefers AK, Huang K, Pajtler KW, Schweizer L, Stichel D, Olar A, Engel NW, Lindenberg K, Harter PN, Braczynski AK, Plate KH, Dohmen H, Garvalov BK, Coras R, Holsken A, Hewer E, Bewerunge-Hudler M, Schick M, Fischer R, Beschorner R, Schittenhelm J, Staszewski O, Wani K, Varlet P, Pages M, Temming P, Lohmann D, Selt F, Witt H, Milde T, Witt O, Aronica E, Giangaspero F, Rushing E, Scheurlen W, Geisenberger C, Rodriguez FJ, Becker A, Preusser M, Haberler C, Bjerkvig R, Cryan J, Farrell M, Deckert M, Hench J, Frank S, Serrano J, Kannan K, Tsirigos A, Bruck W, Hofer S, Brehmer S, Seiz-Rosenhagen M, Hanggi D, Hans V, Rozsnoki S, Hansford JR, Kohlhof P, Kristensen BW, Lechner M, Lopes B, Mawrin C, Ketter R, Kulozik A, Khatib Z, Heppner F, Koch A, Jouvet A, Keohane C, Muhleisen H, Mueller W, Pohl U, Prinz M, Benner A, Zapatka M, Gottardo NG, Driever PH, Kramm CM, Muller HL, Rutkowski S, von Hoff K, Fruhwald MC, Gnekow A, Fleischhack G, Tippelt S, Calaminus G, Monoranu CM, Perry A, Jones C, Jacques TS, Radlwimmer B, Gessi M, Pietsch T, Schramm J, Schackert G, Westphal M, Reifenberger G, Wesseling P, Weller M, Collins VP, Blumcke I, Bendszus M, Debus J, Huang A, Jabado N, Northcott PA, Paulus W, Gajjar A, Robinson GW, Taylor MD, Jaunmuktane Z, Ryzhova M, Platten M, Unterberg A, Wick W, Karajannis MA, Mittelbronn M, Acker T, Hartmann C, Aldape K, Schuller U, Buslei R, Lichter P, Kool M, Herold-Mende C, Ellison DW, Hasselblatt M, Snuderl M, Brandner S, Korshunov A, von Deimling A, Pfister SM. DNA methylation-based classification of central nervous system tumours. Nature. 2018 Mar 22;555(7697):469-474. doi: 10.1038/nature26000. Epub 2018 Mar 14.
- Kulkarni MM, Khandeparkar SG, Deshmukh SD, Karekar RR, Gaopande VL, Joshi AR, Kesari MV, Shelke RR. Risk Stratification in Paragangliomas with PASS (Pheochromocytoma of the Adrenal Gland Scaled Score) and Immunohistochemical Markers. J Clin Diagn Res. 2016 Sep;10(9):EC01-EC04. doi: 10.7860/JCDR/2016/20565.8419. Epub 2016 Sep 1.
- Bialas M, Okon K, Dyduch G, Ciesielska-Milian K, Buziak M, Hubalewska-Dydejczyk A, Sobrinho-Simoes M. Neuroendocrine markers and sustentacular cell count in benign and malignant pheochromocytomas - a comparative study. Pol J Pathol. 2013 Jun;64(2):129-35. doi: 10.5114/pjp.2013.36004.
- Stenman A, Zedenius J, Juhlin CC. The Value of Histological Algorithms to Predict the Malignancy Potential of Pheochromocytomas and Abdominal Paragangliomas-A Meta-Analysis and Systematic Review of the Literature. Cancers (Basel). 2019 Feb 15;11(2):225. doi: 10.3390/cancers11020225.
- Pennanen M, Heiskanen I, Sane T, Remes S, Mustonen H, Haglund C, Arola J. Helsinki score-a novel model for prediction of metastases in adrenocortical carcinomas. Hum Pathol. 2015 Mar;46(3):404-10. doi: 10.1016/j.humpath.2014.11.015. Epub 2014 Dec 9.
- Duregon E, Fassina A, Volante M, Nesi G, Santi R, Gatti G, Cappellesso R, Dalino Ciaramella P, Ventura L, Gambacorta M, Dei Tos AP, Loli P, Mannelli M, Mantero F, Berruti A, Terzolo M, Papotti M. The reticulin algorithm for adrenocortical tumor diagnosis: a multicentric validation study on 245 unpublished cases. Am J Surg Pathol. 2013 Sep;37(9):1433-40. doi: 10.1097/PAS.0b013e31828d387b.
- Main AM, Rossing M, Borgwardt L, Gronkaer Toft B, Rasmussen AK, Feldt-Rasmussen U. Genotype-phenotype associations in PPGLs in 59 patients with variants in SDHX genes. Endocr Connect. 2020 Aug;9(8):793-803. doi: 10.1530/EC-20-0279.
- Ebbehoj A, Jacobsen SF, Trolle C, Robaczyk MG, Rasmussen AK, Feldt-Rasmussen U, Thomsen RW, Poulsen PL, Stochholm K, Sondergaard E. Pheochromocytoma in Denmark during 1977-2016: validating diagnosis codes and creating a national cohort using patterns of health registrations. Clin Epidemiol. 2018 Jun 13;10:683-695. doi: 10.2147/CLEP.S163065. eCollection 2018.
- Lenders JW, Duh QY, Eisenhofer G, Gimenez-Roqueplo AP, Grebe SK, Murad MH, Naruse M, Pacak K, Young WF Jr; Endocrine Society. Pheochromocytoma and paraganglioma: an endocrine society clinical practice guideline. J Clin Endocrinol Metab. 2014 Jun;99(6):1915-42. doi: 10.1210/jc.2014-1498. Erratum In: J Clin Endocrinol Metab. 2023 Feb 08;:
- NGS in PPGL (NGSnPPGL) Study Group; Toledo RA, Burnichon N, Cascon A, Benn DE, Bayley JP, Welander J, Tops CM, Firth H, Dwight T, Ercolino T, Mannelli M, Opocher G, Clifton-Bligh R, Gimm O, Maher ER, Robledo M, Gimenez-Roqueplo AP, Dahia PL. Consensus Statement on next-generation-sequencing-based diagnostic testing of hereditary phaeochromocytomas and paragangliomas. Nat Rev Endocrinol. 2017 Apr;13(4):233-247. doi: 10.1038/nrendo.2016.185. Epub 2016 Nov 18.
Study record dates
Study Major Dates
Study Start (Anticipated)
Primary Completion (Anticipated)
Study Completion (Anticipated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
- Pathologic Processes
- Neoplasms by Histologic Type
- Neoplasms
- Disease Attributes
- Neuroectodermal Tumors
- Neoplasms, Germ Cell and Embryonal
- Neoplasms, Nerve Tissue
- Neoplastic Processes
- Disease Susceptibility
- Neoplasm Metastasis
- Neuroendocrine Tumors
- Genetic Predisposition to Disease
- Pheochromocytoma
- Paraganglioma
Other Study ID Numbers
- PPGL-Pred
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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