Risk category system to identify pituitary adenoma patients with AIP mutations
Caimari, Francisca (Institut d'Investigació Biomèdica Sant Pau)
Hernández-Ramírez, Laura Cristina (Queen Mary University of London. William Harvey Research Institute)
Dang, Mary N. (Queen Mary University of London. William Harvey Research Institute)
Gabrovska, Plamena (Queen Mary University of London. William Harvey Research Institute)
Iacovazzo, Donato (Queen Mary University of London. William Harvey Research Institute)
Stals, Karen (Royal Devon & Exeter Hospital (Exeter, Regne Unit))
Ellard, Sian (Royal Devon & Exeter Hospital (Exeter, Regne Unit))
Korbonits, Márta (Queen Mary University of London. William Harvey Research Institute)
Universitat Autònoma de Barcelona

Data:	2018
Resum:	Predictive tools to identify patients at risk for gene mutations related to pituitary adenomas are very helpful in clinical practice. We therefore aimed to develop and validate a reliable risk category system for aryl hydrocarbon receptor-interacting protein (AIP) mutations in patients with pituitary adenomas. An international cohort of 2227 subjects were consecutively recruited between 2007 and 2016, including patients with pituitary adenomas (familial and sporadic) and their relatives. All probands (n=1429) were screened for AIP mutations, and those diagnosed with a pituitary adenoma prospectively, as part of their clinical screening (n=24), were excluded from the analysis. Univariate analysis was performed comparing patients with and without AIP mutations. Based on a multivariate logistic regression model, six potential factors were identified for the development of a risk category system, classifying the individual risk into low-risk, moderate-risk and high-risk categories. An internal cross-validation test was used to validate the system. 1405 patients had a pituitary tumour, of which 43% had a positive family history, 55. 5% had somatotrophinomas and 81. 5% presented with macroadenoma. Overall, 134 patients had an AIP mutation (9. 5%). We identified four independent predictors for the presence of an AIP mutation: age of onset providing an odds ratio (OR) of 14. 34 for age 0-18 years, family history (OR 10. 85), growth hormone excess (OR 9. 74) and large tumour size (OR 4. 49). In our cohort, 71% of patients were identified as low risk (<5% risk of AIP mutation), 9. 2% as moderate risk and 20% as high risk (≥20% risk). Excellent discrimination (c-statistic=0. 87) and internal validation were achieved. We propose a user-friendly risk categorisation system that can reliably group patients into high-risk, moderate-risk and low-risk groups for the presence of AIP mutations, thus providing guidance in identifying patients at high risk of carrying an AIP mutation. This risk score is based on a cohort with high prevalence of AIP mutations and should be applied cautiously in other populations.
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	AIP mutations ; Acromegaly ; Familial pituitary adenoma ; Screening ; Risk category system
Publicat a:	Journal of medical genetics, Vol. 55, issue 4 (April 2018) , p. 254-260, ISSN 1468-6244

DOI: 10.1136/jmedgenet-2017-104957
PMID: 29440248

7 p, 481.9 KB

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