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Risk category system to identify pituitary adenoma patients with AIP mutations

https://tokushima-u.repo.nii.ac.jp/records/2006375
https://tokushima-u.repo.nii.ac.jp/records/2006375
f76005f9-c47a-4447-824e-b91ebf862b73
名前 / ファイル ライセンス アクション
jmg_55_4_254.pdf jmg_55_4_254.pdf (502 KB)
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Item type 文献 / Documents(1)
公開日 2019-05-14
アクセス権
アクセス権 open access
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_6501
資源タイプ journal article
出版社版DOI
関連識別子 https://doi.org/10.1136/jmedgenet-2017-104957
関連名称 10.1136/jmedgenet-2017-104957
出版タイプ
出版タイプ VoR
出版タイプResource http://purl.org/coar/version/c_970fb48d4fbd8a85
タイトル
タイトル Risk category system to identify pituitary adenoma patients with AIP mutations
著者 Caimari, Francisca

× Caimari, Francisca

en Caimari, Francisca

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Hernández-Ramírez, Laura Cristina

× Hernández-Ramírez, Laura Cristina

en Hernández-Ramírez, Laura Cristina

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Dang, Mary N

× Dang, Mary N

en Dang, Mary N

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Gabrovska, Plamena

× Gabrovska, Plamena

en Gabrovska, Plamena

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Iacovazzo, Donato

× Iacovazzo, Donato

en Iacovazzo, Donato

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Stals, Karen

× Stals, Karen

en Stals, Karen

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Ellard, Sian

× Ellard, Sian

en Ellard, Sian

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Korbonits, Márta

× Korbonits, Márta

en Korbonits, Márta

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岩田, 武男

× 岩田, 武男

WEKO 1264
e-Rad 10350399

ja 岩田, 武男
ISNI

ja-Kana イワタ, タケオ

en Iwata, Takeo

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吉本, 勝彦

× 吉本, 勝彦

WEKO 1648
徳島大学 教育研究者総覧 60308/profile-ja.html
e-Rad 90201863

ja 吉本, 勝彦
ISNI

ja-Kana ヨシモト, カツヒコ

en Yoshimoto, Katsuhiko

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抄録
内容記述 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.
書誌情報 en : Journal of Medical Genetics

巻 55, 号 4, p. 254-260, 発行日 2018-02-10
収録物ID
収録物識別子タイプ ISSN
収録物識別子 00222593
収録物ID
収録物識別子タイプ ISSN
収録物識別子 14686244
収録物ID
収録物識別子タイプ NCID
収録物識別子 AA00702295
出版者
出版者 British Medical Association
備考
値 Collaborators : Members of the FIPA consortium are listed at http://www.fipapatients.org/fipaconsortium/.
権利情報
権利情報 © 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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識別子 350705
言語
言語 eng
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