An Algorithm for the Diagnosis of Behçet Disease Uveitis in Adults

Ilknur Tugal-Tutkun; Sumru Onal; Miles Stanford; Mehmet Akman; Jos W.R. Twisk; Maarten Boers; Merih Oray; P. Özdal; Sibel Kadayifcilar; Radgonde Amer; Sivakumar R. Rathinam; Rajesh Vedhanayaki; Moncef Khairallah; Yonca Akova; F. Yalcindag; Esra Kardes; Berna Basarir; Çigdem Altan; Yilmaz Özyazgan; Ahmet Gül

doi:10.1080/09273948.2020.1736310

An Algorithm for the Diagnosis of Behçet Disease Uveitis in Adults

Ilknur Tugal-Tutkun^*
, Sumru Onal
, Miles Stanford
, Mehmet Akman
, Jos W.R. Twisk
, Maarten Boers
, Merih Oray
, P. Özdal
, Sibel Kadayifcilar
, Radgonde Amer
, Sivakumar R. Rathinam
, Rajesh Vedhanayaki
, Moncef Khairallah
, Yonca Akova
, F. Yalcindag
, Esra Kardes
, Berna Basarir
, Çigdem Altan
, Yilmaz Özyazgan
, Ahmet Gül

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

51 Scopus citations

Abstract

Purpose: To develop an algorithm for the diagnosis of Behçet’s disease (BD) uveitis based on ocular findings. Methods: Following an initial survey among uveitis experts, we collected multi-center retrospective data on 211 patients with BD uveitis and 207 patients with other uveitides, and identified ocular findings with a high diagnostic odds ratio (DOR). Subsequently, we collected multi-center prospective data on 127 patients with BD uveitis and 322 controls and developed a diagnostic algorithm using Classification and Regression Tree (CART) analysis and expert opinion. Results: We identified 10 items with DOR >5. The items that provided the highest accuracy in CART analysis included superficial retinal infiltrate, signs of occlusive retinal vasculitis, and diffuse retinal capillary leakage as well as the absence of granulomatous anterior uveitis or choroiditis in patients with vitritis. Conclusion: This study provides a diagnostic tree for BD uveitis that needs to be validated in future studies.

Original language	English
Pages (from-to)	1154-1163
Number of pages	10
Journal	Ocular Immunology and Inflammation
Volume	29
Issue number	6
DOIs	https://doi.org/10.1080/09273948.2020.1736310
State	Published - 2021
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2020 Taylor & Francis Group, LLC.

Keywords

Behçet disease
classification and regression tree (CART) analysis
classification criteria
diagnosis
uveitis

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10.1080/09273948.2020.1736310

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Tugal-Tutkun, I., Onal, S., Stanford, M., Akman, M., Twisk, J. W. R., Boers, M., Oray, M., Özdal, P., Kadayifcilar, S., Amer, R., Rathinam, S. R., Vedhanayaki, R., Khairallah, M., Akova, Y., Yalcindag, F., Kardes, E., Basarir, B., Altan, Ç., Özyazgan, Y., & Gül, A. (2021). An Algorithm for the Diagnosis of Behçet Disease Uveitis in Adults. Ocular Immunology and Inflammation, 29(6), 1154-1163. https://doi.org/10.1080/09273948.2020.1736310

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title = "An Algorithm for the Diagnosis of Beh{\c c}et Disease Uveitis in Adults",

abstract = "Purpose: To develop an algorithm for the diagnosis of Beh{\c c}et{\textquoteright}s disease (BD) uveitis based on ocular findings. Methods: Following an initial survey among uveitis experts, we collected multi-center retrospective data on 211 patients with BD uveitis and 207 patients with other uveitides, and identified ocular findings with a high diagnostic odds ratio (DOR). Subsequently, we collected multi-center prospective data on 127 patients with BD uveitis and 322 controls and developed a diagnostic algorithm using Classification and Regression Tree (CART) analysis and expert opinion. Results: We identified 10 items with DOR >5. The items that provided the highest accuracy in CART analysis included superficial retinal infiltrate, signs of occlusive retinal vasculitis, and diffuse retinal capillary leakage as well as the absence of granulomatous anterior uveitis or choroiditis in patients with vitritis. Conclusion: This study provides a diagnostic tree for BD uveitis that needs to be validated in future studies.",

keywords = "Beh{\c c}et disease, classification and regression tree (CART) analysis, classification criteria, diagnosis, uveitis",

author = "Ilknur Tugal-Tutkun and Sumru Onal and Miles Stanford and Mehmet Akman and Twisk, \{Jos W.R.\} and Maarten Boers and Merih Oray and P. {\"O}zdal and Sibel Kadayifcilar and Radgonde Amer and Rathinam, \{Sivakumar R.\} and Rajesh Vedhanayaki and Moncef Khairallah and Yonca Akova and F. Yalcindag and Esra Kardes and Berna Basarir and {\c C}igdem Altan and Yilmaz {\"O}zyazgan and Ahmet G{\"u}l",

note = "Publisher Copyright: {\textcopyright} 2020 Taylor \& Francis Group, LLC.",

year = "2021",

doi = "10.1080/09273948.2020.1736310",

language = "אנגלית",

volume = "29",

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journal = "Ocular Immunology and Inflammation",

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Tugal-Tutkun, I, Onal, S, Stanford, M, Akman, M, Twisk, JWR, Boers, M, Oray, M, Özdal, P, Kadayifcilar, S, Amer, R, Rathinam, SR, Vedhanayaki, R, Khairallah, M, Akova, Y, Yalcindag, F, Kardes, E, Basarir, B, Altan, Ç, Özyazgan, Y & Gül, A 2021, 'An Algorithm for the Diagnosis of Behçet Disease Uveitis in Adults', Ocular Immunology and Inflammation, vol. 29, no. 6, pp. 1154-1163. https://doi.org/10.1080/09273948.2020.1736310

TY - JOUR

T1 - An Algorithm for the Diagnosis of Behçet Disease Uveitis in Adults

AU - Tugal-Tutkun, Ilknur

AU - Onal, Sumru

AU - Stanford, Miles

AU - Akman, Mehmet

AU - Twisk, Jos W.R.

AU - Boers, Maarten

AU - Oray, Merih

AU - Özdal, P.

AU - Kadayifcilar, Sibel

AU - Amer, Radgonde

AU - Rathinam, Sivakumar R.

AU - Vedhanayaki, Rajesh

AU - Khairallah, Moncef

AU - Akova, Yonca

AU - Yalcindag, F.

AU - Kardes, Esra

AU - Basarir, Berna

AU - Altan, Çigdem

AU - Özyazgan, Yilmaz

AU - Gül, Ahmet

PY - 2021

Y1 - 2021

N2 - Purpose: To develop an algorithm for the diagnosis of Behçet’s disease (BD) uveitis based on ocular findings. Methods: Following an initial survey among uveitis experts, we collected multi-center retrospective data on 211 patients with BD uveitis and 207 patients with other uveitides, and identified ocular findings with a high diagnostic odds ratio (DOR). Subsequently, we collected multi-center prospective data on 127 patients with BD uveitis and 322 controls and developed a diagnostic algorithm using Classification and Regression Tree (CART) analysis and expert opinion. Results: We identified 10 items with DOR >5. The items that provided the highest accuracy in CART analysis included superficial retinal infiltrate, signs of occlusive retinal vasculitis, and diffuse retinal capillary leakage as well as the absence of granulomatous anterior uveitis or choroiditis in patients with vitritis. Conclusion: This study provides a diagnostic tree for BD uveitis that needs to be validated in future studies.

AB - Purpose: To develop an algorithm for the diagnosis of Behçet’s disease (BD) uveitis based on ocular findings. Methods: Following an initial survey among uveitis experts, we collected multi-center retrospective data on 211 patients with BD uveitis and 207 patients with other uveitides, and identified ocular findings with a high diagnostic odds ratio (DOR). Subsequently, we collected multi-center prospective data on 127 patients with BD uveitis and 322 controls and developed a diagnostic algorithm using Classification and Regression Tree (CART) analysis and expert opinion. Results: We identified 10 items with DOR >5. The items that provided the highest accuracy in CART analysis included superficial retinal infiltrate, signs of occlusive retinal vasculitis, and diffuse retinal capillary leakage as well as the absence of granulomatous anterior uveitis or choroiditis in patients with vitritis. Conclusion: This study provides a diagnostic tree for BD uveitis that needs to be validated in future studies.

KW - Behçet disease

KW - classification and regression tree (CART) analysis

KW - classification criteria

KW - diagnosis

KW - uveitis

UR - https://www.scopus.com/pages/publications/85083581112

U2 - 10.1080/09273948.2020.1736310

DO - 10.1080/09273948.2020.1736310

M3 - ???researchoutput.researchoutputtypes.contributiontojournal.article???

C2 - 32286112

AN - SCOPUS:85083581112

SN - 0927-3948

VL - 29

SP - 1154

EP - 1163

JO - Ocular Immunology and Inflammation

JF - Ocular Immunology and Inflammation

IS - 6

ER -

An Algorithm for the Diagnosis of Behçet Disease Uveitis in Adults

Abstract

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Keywords

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