Article Text

Download PDFPDF

Original Article
Risk category system to identify pituitary adenoma patients with AIP mutations
  1. Francisca Caimari1,2,
  2. Laura Cristina Hernández-Ramírez1,3,
  3. Mary N Dang1,
  4. Plamena Gabrovska1,
  5. Donato Iacovazzo1,
  6. Karen Stals4,
  7. Sian Ellard4,
  8. Márta Korbonits1
  9. on behalf of The International FIPA consortium
  1. 1 Centre of Endocrinology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
  2. 2 Department of Endocrinology, Universitat Autònoma de Barcelona (UAB), Barcelona, Spain
  3. 3 Section of Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, Maryland, USA
  4. 4 Department of Molecular Genetics, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK
  1. Correspondence to Professor Márta Korbonits, Centre of Endocrinology, William Harvey Research Institute, Barts and The London School of Medicine, Queen Mary University of London, London EC1M 6BQ, UK; m.korbonits{at}


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 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.

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.

  • AIP mutations
  • acromegaly
  • familial pituitary adenoma
  • screening
  • risk category system

This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See:

View Full Text

Statistics from


  • Contributors FC and MK planned the study. FC, LCH-R, MND, PG and DI collected the data. FC performed the statistical analysis. KS and SE performed the genetic analysis. FC and MK wrote the manuscript. All authors reviewed and approved the manuscript.

  • Funding FC was supported by a Fellowship of the Fundación Alfonso Martin Escudero. LCH-R was supported by grants from the National Council of Science and Technology and the Secretariat of Public Education from the Mexican Government. DI is supported by a George Alberti Research Training Fellowship funded by Diabetes UK. MK’s familial pituitary adenoma studies are supported by the Barts and the London Charity, the Wellcome Trust, the UK’s Medical Research Council and Pfizer Ltd.

  • Competing interests None declared.

  • Patient consent Obtained.

  • Ethics approval The Cambridge East Research Ethics Committee.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Collaborators Members of the FIPA consortium are listed at

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.