Selection of glucocorticoid-sensitive patients in interstitial lung disease secondary to connective tissue diseases population by radiomics.
Selection of glucocorticoid-sensitive patients in interstitial lung disease secondary to connective tissue diseases population by radiomics.
复制标题
放射组学筛选结缔组织病继发间质性肺病人群中糖皮质激素敏感患者
DOI：
10.2147/tcrm.s181043
复制
发表时间：
2018
影响因子：
2.8
通讯作者：
Li X
中科院分区：
文献类型：
--
作者：
Feng DY;Zhou YQ;Xing YF;Li CF;Lv Q;Dong J;Qin J;Guo YF;Jiang N;Huang C;Hu HT;Guo XH;Chen J;Yin LH;Zhang TT;Li X
糖皮质激素对结缔组织病（CTD）相关间质性肺病（ILD）的影响存在争议。这项多中心研究旨在使用放射组学方法识别糖皮质激素敏感患者。本研究共纳入了416例由主治医生决定开始糖皮质激素治疗（伴或不伴环磷酰胺）的CTD-ILD患者。高剂量定义为脉冲静脉注射甲泼尼龙，初始剂量为1 mg/kg/天的泼尼松龙或0.8 mg/kg/天的甲泼尼龙。低剂量定义为低于高剂量的剂量。放射组学特征从计算机断层扫描图像上描绘的原发性肺病变中手动提取，并通过方差、单变量特征选择和最小绝对收缩和选择算子回归模型进行选择。这些预测模型是使用来自两个中心的309名患者的数据开发的，并在来自其他四家医院的107名患者中进行了外部验证。训练组和验证组的治疗反应分别为38.5%和36.4%。从1,029个具有预测价值的特征中选择了11个放射组学特征。为放射组学特征构建的随机森林模型预测治疗反应的灵敏度为0.897。诺模图的校准曲线表明预测和观察之间的良好协议。决策曲线分析表明，糖皮质激素是有益的，如果预测的反应率为50%-60%的个人。高剂量的糖皮质激素和环磷酰胺产生了上级的疗效。基于放射组学的预测模型可可靠地识别糖皮质激素敏感性CTD-ILD患者。短期、大剂量糖皮质激素联合环磷酰胺治疗可作为一种潜在的治疗方法。
The effect of glucocorticoid(s) on connective tissue disease (CTD)-related interstitial lung disease (ILD) is controversial. This multicenter study aimed to identify glucocorticoid-sensitive patients using a radiomics approach. A total of 416 CTD-ILD patients who began glucocorticoid treatment at the discretion of the attending physician, with or without cyclophosphamide, were included in this study. High doses were defined as pulsed intravenous methylprednisolone, an initial dose of 1 mg/kg/day of prednisolone or 0.8 mg/kg/day of methylprednisolone. Low doses were defined as those less than high doses. Radiomics features were manually extracted from primary lung lesions delineated on computed tomography images, and selected by variance, univariate feature selection, and least absolute shrinkage and selection operator regression model. The prediction models were developed using data from 309 patients from two centers and externally validated in 107 patients from four other hospitals. Treatment response in the training and validation groups was 38.5% and 36.4%, respectively. Eleven radiomics features were selected from 1,029 features with predictive value. Random forest models built for radiomics features to predict treatment response yielded a sensitivity of 0.897. The calibration curve of a nomogram demonstrated good agreement between prediction and observation. Decision curve analysis indicated that glucocorticoid was beneficial if the predicted response rate was 50%–60% for an individual. High doses of glucocorticoids and cyclophosphamide yielded superior efficacy. Radiomics-based predictive models reliably identified glucocorticoid-sensitive CTD-ILD patients. Short-term, high-dose glucocorticoid with cyclophosphamide yielded promising results as a potential therapy.