Department of Radiology, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang, China.
Depatment of Radiology and Pathology, Hubei Province Clinical Research Center of Parkinson's Disease, Xiangyang Key Laboratory of Movement Disorders, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang, Hubei Province, China.
Technol Cancer Res Treat. 2023 Jan-Dec;22:15330338231207006. doi: 10.1177/15330338231207006.
Tongue squamous cell carcinoma (TSCC) is one of the most common and poor prognosis head and neck tumors. The purpose of this study is to establish a model for predicting TSCC prognosis based on clinical and MR radiomics data and to develop a nomogram. A retrospective analysis was performed on the clinical and imaging data of 211 patients with pathologically confirmed TSCC who underwent radical surgery at xx hospital from February 2011 to January 2020. Patients were divided into a study group (recurrence, metastasis, and death, = 76) and a control group (normal survival, = 135) according to 1 to 6 years of follow-up. A training set and a test set were established based on a ratio of 7:3 and a time point. In the training set, 3 prediction models (clinical data model, imaging model, and combined model) were established based on the MR radiomics score (Radscore) combined with clinical features. The predictive performance of these models was compared using the Delong curve, and the clinical net benefit of the model was tested using the decision curve. Then, the external validation of the model was performed in the test set, and a nomogram for predicting TSCC prognosis was developed. Univariate analysis confirmed that betel nut consumption, spicy hot pot or pickled food, unclean oral sex, drug use, platelet/lymphocyte ratio (PLR), neutrophil/lymphocyte ratio (NLR), depth of invasion (DOI), low differentiation, clinical stage, and Radscore were factors that affected TSCC prognosis ( < .05). In the test set, the combined model based on these factors had the highest predictive performance for TSCC prognosis (area under curve (AUC) AUC: 0.870, 95% CI [0.761-0.942]), which was significantly higher than the clinical model (AUC: 0.730, 95% CI [0.602-0.835], = .033) and imaging model (AUC: 0.765, 95% CI [0.640-0.863], = .074). The decision curve also confirmed the higher clinical net benefit of the combined model, and these results were validated in the test set. The nomogram developed based on the combined model received good evaluation in clinical application. MR-LASSO extracted texture parameters can help improve the performance of TSCC prognosis models. The combined model and nomogram provide support for postoperative clinical treatment management of TSCC.
舌鳞状细胞癌 (TSCC) 是最常见和预后不良的头颈部肿瘤之一。本研究旨在基于临床和 MR 放射组学数据建立 TSCC 预后预测模型，并开发列线图。
对 2011 年 2 月至 2020 年 1 月在 xx 医院接受根治性手术的 211 例经病理证实的 TSCC 患者的临床和影像学数据进行回顾性分析。根据 1 至 6 年的随访，患者分为研究组（复发、转移和死亡，n=76）和对照组（正常存活，n=135）。基于 7:3 的比例和时间点建立训练集和测试集。在训练集中，基于 MR 放射组学评分（Radscore）结合临床特征，建立了 3 个预测模型（临床数据模型、影像学模型和联合模型）。使用 Delong 曲线比较这些模型的预测性能，并使用决策曲线测试模型的临床净收益。然后，在测试集中对模型进行外部验证，并开发预测 TSCC 预后的列线图。
单因素分析证实，嚼槟榔、吃辛辣火锅或腌制食品、不清洁的口交、吸毒、血小板/淋巴细胞比值（PLR）、中性粒细胞/淋巴细胞比值（NLR）、浸润深度（DOI）、低分化、临床分期和 Radscore 是影响 TSCC 预后的因素（<0.05）。在测试集中，基于这些因素的联合模型对 TSCC 预后的预测性能最高（曲线下面积（AUC）AUC：0.870，95%置信区间[0.761-0.942]），明显高于临床模型（AUC：0.730，95%置信区间[0.602-0.835]，=0.033）和影像学模型（AUC：0.765，95%置信区间[0.640-0.863]，=0.074）。决策曲线还证实了联合模型具有更高的临床净收益，这些结果在测试集中得到验证。基于联合模型开发的列线图在临床应用中得到了很好的评价。
MR-LASSO 提取的纹理参数有助于提高 TSCC 预后模型的性能。联合模型和列线图为 TSCC 术后临床治疗管理提供了支持。
