Charlesworth Richard P G, Andronicos Nicholas M, Scott David R, McFarlane James R, Agnew Linda L
Brain Behaviour Research Group, University of New England, Armidale, NSW, Australia.
Tamworth Rural Referral Hospital and Tamara Private Hospital, Tamworth, NSW, Australia.
Adv Med Sci. 2017 Mar;62(1):136-142. doi: 10.1016/j.advms.2016.06.002. Epub 2016 Jun 14.
The aim of this pilot study was to attempt to define a set of equations from histological observations of tissue affected with coeliac disease (CD) to predict Marsh score.
MATERIAL/METHODS: Tissue from 15 patients with untreated CD, 6 patients with treated CD and 9 healthy control patients were stained using the standard H&E, Giemsa's staining for tissue sections and Alcian Blue protocols. A number of histological measures were then taken from each section and the data was used to ultimately design a set of linear predictive algorithms to calculate Marsh score.
Using MANOVA and discriminant analysis, two linear functions were defined which could accurately predict the Marsh score of patients 62.5% (full Marsh score) to 79.2% (simplified Marsh score) of the time.
This pilot study has shown that a set of objective histological measures can be used to define algorithms to predict Marsh score in CD patients and also monitor treatment compliance and progression.
本初步研究旨在尝试从乳糜泻（CD）病变组织的组织学观察结果中确定一组方程，以预测马什评分。
材料/方法：对15例未经治疗的CD患者、6例经治疗的CD患者和9例健康对照患者的组织进行染色，采用标准苏木精-伊红染色、组织切片吉姆萨染色和阿尔辛蓝染色方法。然后从每个切片中获取一些组织学测量数据，并将这些数据最终用于设计一组线性预测算法来计算马什评分。
使用多变量方差分析和判别分析，定义了两个线性函数，这两个函数能够在62.5%（完整马什评分）至79.2%（简化马什评分）的时间内准确预测患者的马什评分。
本初步研究表明，一组客观的组织学测量方法可用于定义算法，以预测CD患者的马什评分，并监测治疗依从性和病情进展。
