Performance of existing diagnosis/classification criteria for Behcet's disease in Iranian patients: analysis of 5666 patients and 2406 controls.

Autor: Davatchi, Fereydoun, Shahram, Farhad, Nadji, Abdolhadi, Chams-Davatchi, Cheyda, Shams, Hormoz, Akhlaghi, Ma'ssoomeh, Abdollahi, Bahar Sadeghi, Ziaie, Naghmeh
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Zdroj: APLAR Journal of Rheumatology; Sep2006, Vol. 9 Issue 3, p238-243, 6p, 1 Diagram, 6 Charts
Abstrakt: Aim: To analyse the performance of existing diagnosis/classification criteria for Behcet's disease (BD) in Iranian patients. There are 13 sets: Curth (1946), Hewitt (1969), Mason and Barnes (1969), Hewitt revised (1971), Japan (1972), Hubault and Hamza (1974), O'Duffy (1974), Cheng and Zhang (1980), Dilsen (1986), Japan revised (1988), International (1990), Iran (1993), Classification Tree (1993), and Dilsen revised criteria (2000). Methods: All patients from the Behcet's Disease Registry (5666) and control patients (2406) entered the study. Sensitivity, specificity and accuracy were calculated. Results: The most sensitive was Curth criteria with (99.7%), followed by Classification Tree (97.3%), Zhang (93.5%), Iran (91.4%), Japan revised (86.4%), Japan (85.3%), Dilsen (83.7%), Hubault and Hamza (81.6%), Dilsen revised (81.2%), International criteria (79.8%), Hewitt (73.8%), O'Duffy (70.7%), and Masson and Barnes (65.7%). The most specific was Masson and Barnes (99.6%), followed by the International criteria (98.3%), Dilsen revised (98.2%), O'Duffy (97.6%), Japan (97.1%), Japan revised (97%), Classification Tree (96.7%), Hewitt (95.8%), Iran (95.8%), Zhang (92.4%), Dilsen (91.4%), Hubault (90.8%), and Curth (78.6%). The most accurate criteria was Classification Tree (97.1%), followed by Curth (93.4%), Zhang (93.1%), Iran (92.7%), Japan revised (89.6%), Japan (88.8%), Dilsen revised (86.2%), Dilsen (86%), International criteria (85.3%), Hubault (84.3%), Hewitt (80.4%), O'Duffy (78.8%), and Mason and Barnes (75.8%). Discussion: Among the existing criteria, the best to classify Iranian patients is the Classification Tree. The second most accurate is Curth criteria. The difference is statistically significant. Further, Curth criteria is not optimized, having very high sensitivity and low specificity. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index