In silico validation of the Autoinflammatory Disease Damage Index. Issue 11 (4th August 2018) - ter Haar, Nienke M; van Delft, Amber Laetitia Justine; Annink, Kim Valerie; van Stel, Henk; Al-Mayouf, Sulaiman M; Amaryan, Gayane; Anton, Jordi; Barron, Karyl S; Benseler, Susanne; Brogan, Paul A; Cantarini, Luca; Cattalini, Marco; et al.
Abstract : Introduction: Autoinflammatory diseases can cause irreversible tissue damage due to systemic inflammation. Recently, the Autoinflammatory Disease Damage Index (ADDI) was developed. The ADDI is the first instrument to quantify damage in familial Mediterranean fever, cryopyrin-associated periodic syndromes, mevalonate kinase deficiency and tumour necrosis factor receptor-associated periodic syndrome. The aim of this study was to validate this tool for its intended use in a clinical/research setting. Methods: The ADDI was scored on paper clinical cases by at least three physicians per case, independently of each other. Face and content validity were assessed by requesting comments on the ADDI. Reliability was tested by calculating the intraclass correlation coefficient (ICC) using an 'observer-nested-within-subject' design. Construct validity was determined by correlating the ADDI score to the Physician Global Assessment (PGA) of damage and disease activity. Redundancy of individual items was determined with Cronbach's alpha. Results: The ADDI was validated on a total of 110 paper clinical cases by 37 experts in autoinflammatory diseases. This yielded an ICC of 0.84 (95% CI 0.78 to 0.89). The ADDI score correlated strongly with PGA-damage (r=0.92, 95% CI 0.88 to 0.95) and was not strongly influenced by disease activity (r=0.395, 95% CI 0.21 to 0.55). After comments from disease experts, some item definitions were refined. The interitem correlation in all different categories was lower than 0.7, indicating that there was no redundancy between individual damage items. Conclusion: The ADDI is a reliable and valid instrument to quantify damage in individual patients and can be used to compare disease outcomes in clinical studies.