Department of Oncology, Qingdao Central Hospital, Qingdao, China.
Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Jinan, China.
Thorac Cancer. 2021 Dec;12(23):3110-3120. doi: 10.1111/1759-7714.14115. Epub 2021 Oct 14.
The current study aimed to comprehensively analyze the clinical prognostic factors of malignant esophageal fistula (MEF). Furthermore, this study sought to establish and validate prognostic nomograms incorporating radiomics and clinical factors to predict overall survival and median survival after fistula for patients with MEF.
The records of 76 patients with MEF were retrospectively analyzed. A stepwise Cox proportional hazards regression model was employed to screen independent prognostic factors and develop clinical nomograms. Radiomic features were extracted from prefistula CT images and post fistula CT images. Least absolute shrinkage and selection operator (LASSO) regression and Cox regression algorithm was used to filter radiomic features and avoid overfitting. Radiomic signature was a linear combination of optimal features and corresponding coefficients. The joint prognostic nomograms was constructed by radiomic signatures and clinical features. All models were validated by Harrell's concordance index (C-index), caliberation and bootstrap validation.
For overall survival, age, prealbumin, KPS and interval between diagnosis of esophageal cancer and fistula were identified as independent prognostic factors and incorporated into the clinical nomogram. Age, prealbumin, serum albumin, KPS and neutrophil proportion were selected for the clinical nomogram of post fistula survival. The C-index of overall survival nomogram was 0.719 (95% CI: 0.645-0.793) and that was 0.722 (95% CI: 0.653-0.791) in the post fistula survival nomogram. The radiomic signature developed by radiomic features of prefistula CT showed a significant correlation with both overall survival and post fistula survival. The C-index of joint nomogarm for overall survival and post fistula survival was 0.831 (95% CI: 0.757-0.905) and 0.77 (95% CI: 0.686-0.854), respectively. The calibration curve showed the joint nomograms outperformed the clinical ones.
The study presents nomograms incorporating independent clinical risk factors and radiomic signature to predict the prognosis of MEF. This prognostic classification system has the potential to guide therapeutic decisions for patients with malignant esophageal fistulas.
本研究旨在全面分析恶性食管瘘（MEF）的临床预后因素。此外，本研究旨在建立并验证纳入放射组学和临床因素的预后列线图，以预测 MEF 患者的总生存和瘘后中位生存时间。
回顾性分析了 76 例 MEF 患者的记录。采用逐步 Cox 比例风险回归模型筛选独立的预后因素，并建立临床列线图。从瘘前 CT 图像和瘘后 CT 图像中提取放射组学特征。采用最小绝对收缩和选择算子（LASSO）回归和 Cox 回归算法筛选放射组学特征并避免过度拟合。放射组学特征是最优特征及其对应的系数的线性组合。通过放射组学特征和临床特征构建联合预后列线图。所有模型均通过 Harrell 一致性指数（C 指数）、校准和 bootstrap 验证进行验证。
对于总生存，年龄、前白蛋白、KPS 和食管癌诊断与瘘之间的间隔被确定为独立的预后因素，并纳入临床列线图。年龄、前白蛋白、血清白蛋白、KPS 和中性粒细胞比例被纳入瘘后生存的临床列线图。总生存列线图的 C 指数为 0.719（95%CI：0.645-0.793），瘘后生存列线图的 C 指数为 0.722（95%CI：0.653-0.791）。由瘘前 CT 放射组学特征建立的放射组学特征与总生存和瘘后生存均显著相关。总生存和瘘后生存联合列线图的 C 指数分别为 0.831（95%CI：0.757-0.905）和 0.77（95%CI：0.686-0.854）。校准曲线显示联合列线图优于临床列线图。
本研究提出了一种纳入独立临床危险因素和放射组学特征的列线图，以预测 MEF 的预后。这种预后分类系统有可能为恶性食管瘘患者的治疗决策提供指导。
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