William R Best1. 1. Midwest Center for Health, Services and Policy Research, Edward Hines Jr VA Hospital, Hines, Illinois, USA. william.best@va.gov
Abstract
BACKGROUND: The Crohn's Disease Activity Index (CDAI) was developed in the 1970s to assess the degree of illness in individuals with Crohn's disease and has since been used widely in clinical trials of the condition. The Harvey-Bradshaw Index (HBI) is a simplification of the CDAI, designed to make data collection and computation easier. It is purported, on the basis of a 0.93 correlation coefficient, to give "essentially the same information." However, correlation is an incomplete way to assess sameness, and this study aimed to develop a method for predicting CDAI from HBI values, including relevant prediction limits. MATERIALS AND METHODS: Data used in developing both indexes were combined. Single visits of 224 patients with Crohn's disease were plotted on a scattergram. HBI values seen were integers from 0 through 19. Mean and standard deviation of CDAI were determined for each HBI value that included a sufficient number of patients. Standard deviation of CDAI showed a linear increase with increasing HBI. Therefore, regression of CDAI on HBI was weighted on the inverse of the estimated CDAI standard deviation. RESULTS: Regression predicted a 27-CDAI-unit increase for each HBI unit. Calculated 95% prediction limits were almost straight, diverging lines, bracketing 95% of observations. A table gives central tendency and 95% prediction limits of CDAI for any HBI, as well as key clinical benchmarks. CONCLUSIONS: There is a good but far from perfect relationship between CDAI and HBI. CDAI is preferred for clinical trials; HBI is easier to use.
BACKGROUND: The Crohn's Disease Activity Index (CDAI) was developed in the 1970s to assess the degree of illness in individuals with Crohn's disease and has since been used widely in clinical trials of the condition. The Harvey-Bradshaw Index (HBI) is a simplification of the CDAI, designed to make data collection and computation easier. It is purported, on the basis of a 0.93 correlation coefficient, to give "essentially the same information." However, correlation is an incomplete way to assess sameness, and this study aimed to develop a method for predicting CDAI from HBI values, including relevant prediction limits. MATERIALS AND METHODS: Data used in developing both indexes were combined. Single visits of 224 patients with Crohn's disease were plotted on a scattergram. HBI values seen were integers from 0 through 19. Mean and standard deviation of CDAI were determined for each HBI value that included a sufficient number of patients. Standard deviation of CDAI showed a linear increase with increasing HBI. Therefore, regression of CDAI on HBI was weighted on the inverse of the estimated CDAI standard deviation. RESULTS: Regression predicted a 27-CDAI-unit increase for each HBI unit. Calculated 95% prediction limits were almost straight, diverging lines, bracketing 95% of observations. A table gives central tendency and 95% prediction limits of CDAI for any HBI, as well as key clinical benchmarks. CONCLUSIONS: There is a good but far from perfect relationship between CDAI and HBI. CDAI is preferred for clinical trials; HBI is easier to use.
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