Objective We developed a validated index for assessing histological disease activity in UC and established its responsiveness. Methods Two hundred biopsies were scored. The outcome was the Global Visual Evaluation (GVE). Eight histological features were tested. The Nancy index was developed by multiple linear regression and bootstrap process to create an index that best matched the GVE. Goodness of fit was assessed by the adjusted R squared (adjusted R-2). The second step was the validation of the index: 100 biopsies were scored for the Nancy index by three pathologists from different centres. Inter-reader reliability was evaluated for each reader. The relationship between the change of the Nancy index and the Geboes index was assessed to assess the responsiveness. Results After backward selection with bootstrap validation, 3/8 items were selected: ulceration (adjusted R-2=0.55), acute inflammatory infiltrate (adjusted R-2=0.88) and chronic inflammatory infiltrate (adjusted R-2=0.79). The Nancy index is defined by a 5-level classification ranging from grade 0 (absence of significant histological disease activity) to grade 4 (severely active disease). The intraclass correlation coefficient (ICC) for the intrareader reliability was 0.88 (95% CI 0.82 to 0.92) and the index had good interreader reliability (ICC=0.86 (0.81 to 0.99)). The correlation between the Nancy index and the Geboes score or the GVE was very good. The index had a good responsiveness with a high correlation between changes in the Geboes score and changes in the Nancy index (0.910 (0.813 to 0.955)). Conclusions A three descriptor histological index has been validated for use in clinical practice and clinical trials.

Development and validation of the Nancy histological index for UC

Danese S;
2017

Abstract

Objective We developed a validated index for assessing histological disease activity in UC and established its responsiveness. Methods Two hundred biopsies were scored. The outcome was the Global Visual Evaluation (GVE). Eight histological features were tested. The Nancy index was developed by multiple linear regression and bootstrap process to create an index that best matched the GVE. Goodness of fit was assessed by the adjusted R squared (adjusted R-2). The second step was the validation of the index: 100 biopsies were scored for the Nancy index by three pathologists from different centres. Inter-reader reliability was evaluated for each reader. The relationship between the change of the Nancy index and the Geboes index was assessed to assess the responsiveness. Results After backward selection with bootstrap validation, 3/8 items were selected: ulceration (adjusted R-2=0.55), acute inflammatory infiltrate (adjusted R-2=0.88) and chronic inflammatory infiltrate (adjusted R-2=0.79). The Nancy index is defined by a 5-level classification ranging from grade 0 (absence of significant histological disease activity) to grade 4 (severely active disease). The intraclass correlation coefficient (ICC) for the intrareader reliability was 0.88 (95% CI 0.82 to 0.92) and the index had good interreader reliability (ICC=0.86 (0.81 to 0.99)). The correlation between the Nancy index and the Geboes score or the GVE was very good. The index had a good responsiveness with a high correlation between changes in the Geboes score and changes in the Nancy index (0.910 (0.813 to 0.955)). Conclusions A three descriptor histological index has been validated for use in clinical practice and clinical trials.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11699/3843
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