Department of Radiology, Anhui Chest Hospital, Hefei, China.
Clinical College of Chest, Anhui Medical University, Hefei, China.
Cancer Imaging. 2022 Sep 5;22(1):46. doi: 10.1186/s40644-022-00483-1.
To establish a nomogram for predicting the risk of adenocarcinomas in patients with subsolid nodules (SSNs) according to the 2021 WHO classification.
A total of 656 patients who underwent SSNs resection were retrospectively enrolled. Among them, 407 patients were assigned to the derivation cohort and 249 patients were assigned to the validation cohort. Univariate and multi-variate logistic regression algorithms were utilized to identity independent risk factors of adenocarcinomas. A nomogram based on the risk factors was generated to predict the risk of adenocarcinomas. The discrimination ability of the nomogram was evaluated using the concordance index (C-index), its performance was calibrated using a calibration curve, and its clinical significance was evaluated using decision curves and clinical impact curves.
Lesion size, mean CT value, vascular change and lobulation were identified as independent risk factors for adenocarcinomas. The C-index of the nomogram was 0.867 (95% CI, 0.833-0.901) in derivation cohort and 0.877 (95% CI, 0.836-0.917) in validation cohort. The calibration curve showed good agreement between the predicted and actual risks. Analysis of the decision curves and clinical impact curves revealed that the nomogram had a high standardized net benefit.
A nomogram for predicting the risk of adenocarcinomas in patients with SSNs was established in light of the 2021 WHO classification. The developed model can be adopted as a pre-operation tool to improve the surgical management of patients.
根据 2021 年世卫组织分类，建立预测亚实性结节（SSNs）患者腺癌风险的列线图。
回顾性纳入 656 例接受 SSNs 切除术的患者。其中，407 例患者被分配到推导队列，249 例患者被分配到验证队列。利用单变量和多变量逻辑回归算法确定腺癌的独立危险因素。根据危险因素生成列线图以预测腺癌的风险。通过一致性指数（C-index）评估列线图的区分能力，通过校准曲线评估其性能，通过决策曲线和临床影响曲线评估其临床意义。
病变大小、平均 CT 值、血管变化和分叶被确定为腺癌的独立危险因素。该列线图在推导队列中的 C-index 为 0.867（95%CI，0.833-0.901），在验证队列中的 C-index 为 0.877（95%CI，0.836-0.917）。校准曲线显示预测风险与实际风险之间具有良好的一致性。决策曲线和临床影响曲线的分析表明，该列线图具有较高的标准化净获益。
根据 2021 年世卫组织分类，建立了预测 SSNs 患者腺癌风险的列线图。该模型可作为术前工具，用于改善患者的手术管理。
