How accurate are clinical activity indices for scoring of disease activity in inflammatory bowel disease (IBD)?
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Lone G. M. Jørgensen
Abstract
Clinical activity indices are essential instruments in monitoring inflammatory bowel diseases such as Crohn's disease (CD) and ulcerative colitis (UC). To subclassify components of disease indices in CD and UC, investigate technical noise in estimation of the indices, establish a signal-to-noise ratio (SNR), evaluate correlation between indices and calculate the reference change value (RCV) for selected biochemical variables in individual cases, 50 patients with CD and 49 patients with UC were included in the study. Qualitative index variables were assessed for scoring errors. The standard deviation (SD) was estimated according to a rectangular model, while SD in biochemical variable scoring was estimated according to a Gaussian model; a combined SD was also calculated. These values were investigated for their individual contribution to variation. The 95% CI of an index value was based on ±1.96×SD combined and a change in separate biochemical variables was calculated as RCV 1.96×√2×SD combined. Correlation between different disease activity indices was assessed for unexplained variation. The Crohn's disease activity index (CDAI) had the highest variation compared to the van Hees (Hees) and the Harvey-Bradshaw index (HBI) in CD, but it also had the best SNR, whereas HBI had the lowest. In UC the clinical activity index (CAI) showed the highest variance, but the best SNR compared to Seo's activity index (AI). The 95% CI of the CDAI discriminatory activity sum of 150 in individual cases was 105–195, whereas the 95% interval for a change was ±62.4. Self-reported wellness contributed 40% to total variance in the CDAI. Factors of clinical importance increased errors in estimates and variance of the indices. Poor correlation was obtained between activity indices, with up to 70% unexplained variance. The SD combined for estimated errors was as high as 23 points, with the best SNR being approximately 20. Index factors increase the sensitivity of SNRs to errors and lower the disease specificity. Sensitivity optimisation may be achieved by standardisation of the variables and their use.
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