Dataset related to article "Predictive value of clinical and radiomic features for radiation therapy response in patients with lymph node-positive head and neck cancer"

Abstract Background: Prediction of survival and radiation therapy response is challenging in head and neck cancer with metastatic lymph nodes (LNs). Here we developed novel radiomics- and clinical-based predictive models. Methods: Volumes of interest of LNs were employed for radiomic features extraction. Radiomic and clinical features were investigated for their predictive value relatively to locoregional failure (LRF), progression-free survival (PFS), and overall survival (OS) and used to build multivariate models. Results: Hundred and six subjects were suitable for final analysis. Univariate analysis identified two radiomic features significantly predictive for LRF, and five radiomic features plus two clinical features significantly predictive for both PFS and OS. The area under the curve of receiver operating characteristic curve combining clinical and radiomic predictors for PFS and OS resulted 0.71 (95%CI: 0.60-0.83) and 0.77 (95%CI: 0.64-0.89). Conclusions: Radiomic and clinical features resulted to be independent predictive factors, but external independent validation is mandatory to support these findin### 摘要 背景：伴转移性淋巴结（lymph nodes, LNs）的头颈部癌患者的生存预测与放疗应答评估颇具挑战。本研究构建了基于放射组学与临床信息的新型预测模型。 方法：本研究对淋巴结感兴趣体积开展放射组学特征提取。针对局部区域复发（locoregional failure, LRF）、无进展生存期（progression-free survival, PFS）及总生存期（overall survival, OS），探究放射组学特征与临床特征的预测价值，并以此构建多变量预测模型。 结果：最终共有106例受试者纳入最终分析。单因素分析显示，2项放射组学特征可显著预测局部区域复发；另有5项放射组学特征及2项临床特征可同时显著预测无进展生存期与总生存期。联合临床与放射组学预测因子的受试者工作特征曲线（receiver operating characteristic curve, ROC曲线）下面积，针对无进展生存期与总生存期分别为0.71（95%置信区间：0.60~0.83）与0.77（95%置信区间：0.64~0.89）。 结论：放射组学特征与临床特征均为独立预测因子，但仍需开展外部独立验证以佐证本研究发现。