Department of Internal Medicine, Division of Gastroenterology and Hepatology, Maastricht University Medical Center+, Maastricht, The Netherlands.
School for Nutrition and Translational Research in Metabolism, Maastricht University Medical Center+, Maastricht, The Netherlands.
J Crohns Colitis. 2021 Nov 8;15(11):1885-1897. doi: 10.1093/ecco-jcc/jjab087.
Crohn's disease [CD] is characterised by a heterogeneous disease course. Patient stratification at diagnosis using clinical, serological, or genetic markers does not predict disease course sufficiently to facilitate clinical decision making. The current study aimed to investigate the additive predictive value of histopathological features to discriminate between a long-term mild and severe disease course.
Diagnostic biopsies from treatment-naïve CD patients with mild or severe disease courses in the first 10 years after diagnosis were reviewed by two gastrointestinal pathologists after developing a standardised form comprising 15 histopathological features. Multivariable logistic regression models were built to identify predictive features and compute receiver operating characteristic [ROC] curves. Models were internally validated using bootstrapping to obtain optimism-corrected performance estimates.
In total, 817 biopsies from 137 patients [64 mild, 73 severe cases] were included. Using clinical baseline characteristics, disease course could only moderately be predicted (area under receiver operating characteristic curve [AUROC]: 0.738 [optimism 0.018], 95% confidence interval [CI] 0.65-0.83, sensitivity 83.6%, specificity 53.1%). When adding histopathological features, in colonic biopsies a combination of [1] basal plasmacytosis, [2] severe lymphocyte infiltration in lamina propria, [3] Paneth cell metaplasia, and [4] absence of ulcers were identified and resulted in significantly better prediction of a severe course (AUROC: 0.883 [optimism 0.033], 95% CI 0.82-0.94, sensitivity 80.4%, specificity 84.2%).
In this first study investigating the additive predictive value of histopathological features in biopsies at CD diagnosis, we found that certain features of chronic inflammation in colonic biopsies contributed to prediction of a severe disease course, thereby presenting a novel approach to improving stratification and facilitating clinical decision making.
克罗恩病（CD）的病程具有异质性。在诊断时使用临床、血清学或遗传标志物对患者进行分层，并不能充分预测疾病的病程，从而无法为临床决策提供便利。本研究旨在探讨组织病理学特征对区分长期轻度和重度病程的附加预测价值。
对诊断时处于轻度或重度病程的治疗初治 CD 患者的诊断性活检进行回顾性研究，由两位胃肠病病理学家在制定了包含 15 个组织病理学特征的标准表格后进行评估。采用多变量逻辑回归模型来识别预测特征并计算受试者工作特征（ROC）曲线。使用 bootstrap 进行内部验证，以获得矫正后的模型性能估计。
共纳入了 137 例患者的 817 份活检标本[64 份轻度，73 份重度病例]。使用临床基线特征，仅能对病程进行中度预测（ROC 曲线下面积 [AUROC]：0.738 [矫正后 0.018]，95%置信区间 [CI] 0.65-0.83，敏感性 83.6%，特异性 53.1%）。当加入组织病理学特征时，在结肠活检中，[1]基底浆细胞增多、[2]固有层严重淋巴细胞浸润、[3]潘氏细胞化生和[4]无溃疡这四种特征的组合被确定，并可显著改善对重度病程的预测（AUROC：0.883 [矫正后 0.033]，95% CI 0.82-0.94，敏感性 80.4%，特异性 84.2%）。
本研究首次探讨了在 CD 诊断时活检组织病理学特征的附加预测价值，发现结肠活检中某些慢性炎症特征有助于预测严重的病程，从而为改善分层和为临床决策提供便利提供了一种新方法。
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