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ID 113266
Author
Caimari, Francisca Queen Mary University of London|Universitat Autònoma de Barcelona
Hernández-Ramírez, Laura Cristina Queen Mary University of London|National Institutes of Health
Dang, Mary N Queen Mary University of London
Gabrovska, Plamena Queen Mary University of London
Iacovazzo, Donato Queen Mary University of London
Stals, Karen Royal Devon and Exeter NHS Foundation Trust
Ellard, Sian Royal Devon and Exeter NHS Foundation Trust
Korbonits, Márta Queen Mary University of London
Content Type
Journal Article
Description
Background
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.
Methods
A n 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.
Results
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.
Conclusion
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.
Journal Title
Journal of Medical Genetics
ISSN
00222593
14686244
NCID
AA00702295
Publisher
British Medical Association
Volume
55
Issue
4
Start Page
254
End Page
260
Published Date
2018-02-10
Remark
Collaborators : Members of the FIPA consortium are listed at http://www.fipapatients.org/fipaconsortium/.
Rights
© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license(http://creativecommons.org/licenses/by/4.0/), which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited.
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language
eng
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departments
Oral Sciences