Best William R
Midwest Center for Health, Services and Policy Research, Edward Hines Jr VA Hospital, Hines, Illinois, USA.
Inflamm Bowel Dis. 2006 Apr;12(4):304-10. doi: 10.1097/01.MIB.0000215091.77492.2a.
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.
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.
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.
There is a good but far from perfect relationship between CDAI and HBI. CDAI is preferred for clinical trials; HBI is easier to use.
克罗恩病活动指数(CDAI)于20世纪70年代制定,用于评估克罗恩病患者的疾病程度,此后在该疾病的临床试验中得到广泛应用。哈维 - 布拉德肖指数(HBI)是CDAI的简化版,旨在使数据收集和计算更简便。据称,基于0.93的相关系数,它能给出“基本相同的信息”。然而,相关性是评估一致性的一种不完整方法,本研究旨在开发一种根据HBI值预测CDAI的方法,包括相关的预测界限。
将用于制定这两种指数的数据合并。在散点图上绘制了224例克罗恩病患者的单次就诊情况。观察到的HBI值为从0到19的整数。对于每个包含足够患者数量的HBI值,确定CDAI的均值和标准差。CDAI的标准差随HBI的增加呈线性增加。因此,CDAI对HBI的回归以估计的CDAI标准差的倒数加权。
回归预测每个HBI单位CDAI增加27个单位。计算出的95%预测界限几乎是直线,呈发散状,包含了95%的观察值。一个表格给出了任何HBI对应的CDAI的中心趋势和95%预测界限,以及关键的临床基准。
CDAI与HBI之间存在良好但远非完美的关系。在临床试验中更倾向使用CDAI;HBI更易于使用。