Yang Tian, Feng Jing, Yao Ruchen, Feng Qi, Shen Jun
Renji Hospital, School of Medicine, Shanghai Jiao Tong University; Division of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Inflammatory Bowel Disease Research Center, Shanghai Institute of Digestive Disease, 160# Pu Jian Ave, Shanghai, 200127, China.
NHC Key Laboratory of Digestive Diseases (Renji Hospital, Shanghai Jiaotong University School of Medicine), Shanghai, China.
Insights Imaging. 2024 Mar 13;15(1):69. doi: 10.1186/s13244-024-01637-4.
Predicting secondary loss of response (SLR) to infliximab (IFX) is paramount for tailoring personalized management regimens. Concurrent pancreatic manifestations in patients with Crohn's disease (CD) may correlate with SLR to anti-tumor necrosis factor treatment. This work aimed to evaluate the potential of pancreatic radiomics to predict SLR to IFX in biologic-naive individuals with CD.
Three models were developed by logistic regression analyses to identify high-risk subgroup prone to SLR. The area under the curve (AUC), calibration curve, decision curve analysis (DCA), and integrated discrimination improvement (IDI) were applied for the verification of model performance. A quantitative nomogram was proposed based on the optimal prediction model, and its reliability was substantiated by 10-fold cross-validation.
In total, 184 CD patients were enrolled in the period January 2016 to February 2022. The clinical model incorporated age of onset, disease duration, disease location, and disease behavior, whereas the radiomics model consisted of five texture features. These clinical parameters and the radiomics score calculated by selected texture features were applied to build the combined model. Compared to other two models, combined model achieved favorable, significantly improved discrimination power (AUC 0.851 vs 0.694, p = 0.02; AUC 0.851 vs 0.740, p = 0.04) and superior clinical usefulness, which was further converted into reliable nomogram with an accuracy of 0.860 and AUC of 0.872.
The first proposed pancreatic-related nomogram represents a credible, noninvasive predictive instrument to assist clinicians in accurately identifying SLR and non-SLR in CD patients.
This study first built a visual nomogram incorporating pancreatic texture features and clinical factors, which could facilitate clinicians to make personalized treatment decisions and optimize cost-effectiveness ratio for patients with CD.
• The first proposed pancreatic-related model predicts secondary loss of response for infliximab in Crohn's disease. • The model achieved satisfactory predictive accuracy, calibration ability, and clinical value. • The model-based nomogram has the potential to identify long-term failure in advance and tailor personalized management regimens.
预测英夫利昔单抗（IFX）治疗的继发性反应丧失（SLR）对于制定个性化治疗方案至关重要。克罗恩病（CD）患者同时出现胰腺表现可能与抗肿瘤坏死因子治疗的SLR相关。本研究旨在评估胰腺影像组学预测初治CD患者对IFX治疗SLR的潜力。
通过逻辑回归分析建立三个模型，以识别易于出现SLR的高危亚组。应用曲线下面积（AUC）、校准曲线、决策曲线分析（DCA）和综合判别改善（IDI）来验证模型性能。基于最优预测模型构建定量列线图，并通过10倍交叉验证证实其可靠性。
2016年1月至2022年2月期间共纳入184例CD患者。临床模型纳入了发病年龄、病程、病变部位和疾病行为，而影像组学模型由五个纹理特征组成。将这些临床参数和通过选定纹理特征计算的影像组学评分应用于构建联合模型。与其他两个模型相比，联合模型具有良好的、显著提高的判别能力（AUC：0.851对0.694，p = 0.02；AUC：0.851对0.740，p = 0.04）和更高的临床实用性，进一步转化为可靠的列线图，准确率为0.860，AUC为0.872。
首个提出的与胰腺相关的列线图是一种可靠的非侵入性预测工具，可协助临床医生准确识别CD患者的SLR和非SLR。
本研究首次构建了一个结合胰腺纹理特征和临床因素的可视化列线图，可帮助临床医生为CD患者做出个性化治疗决策并优化成本效益比。
• 首个提出的与胰腺相关的模型可预测克罗恩病患者对英夫利昔单抗的继发性反应丧失。
• 该模型具有令人满意的预测准确性、校准能力和临床价值。
• 基于模型的列线图有潜力提前识别长期治疗失败并制定个性化治疗方案。
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