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CT-Based Radiomics Nomogram for Prediction of Progression-Free Survival in Locoregionally Advanced Nasopharyngeal Carcinoma
Cancer Management and Research ( IF 2.5 ) Pub Date : 2021-09-03 , DOI: 10.2147/cmar.s325373 Chang Yan 1 , De-Song Shen 1 , Xiao-Bo Chen 2 , Dan-Ke Su 3 , Zhong-Guo Liang 1 , Kai-Hua Chen 1 , Ling Li 1 , Xia Liang 1 , Hai Liao 3 , Xiao-Dong Zhu 1, 4
Cancer Management and Research ( IF 2.5 ) Pub Date : 2021-09-03 , DOI: 10.2147/cmar.s325373 Chang Yan 1 , De-Song Shen 1 , Xiao-Bo Chen 2 , Dan-Ke Su 3 , Zhong-Guo Liang 1 , Kai-Hua Chen 1 , Ling Li 1 , Xia Liang 1 , Hai Liao 3 , Xiao-Dong Zhu 1, 4
Affiliation
Purpose: We aimed to construct of a nomogram to predict progression-free survival (PFS) in locoregionally advanced nasopharyngeal carcinoma (LA-NPC) with risk stratification using computed tomography (CT) radiomics features and clinical factors.
Patients and Methods: A total of 311 patients diagnosed with LA-NPC (stage III–IVa) at our hospital between 2010 and 2014 were included. The region of interest (ROI) of the primary nasopharyngeal mass was manually outlined. Independent sample t-test and LASSO-logistic regression were used for selecting the most predictive radiomics features of PFS, and to generate a radiomics signature. A nomogram was built with clinical factors and radiomics features, and the risk stratification model was tested accordingly.
Results: In total, 20 radiomics features most associated with prognosis were selected. The radiomics nomogram, which integrated the radiomics signature and significant clinical factors, showed excellent performance in predicting PFS, with C-index of 0.873 (95% CI: 0.803∼ 0.943), which was better than that of the clinical nomogram (C-index, 0.729, 95% CI: 0.620∼ 0.838) as well as of the TNM staging system (C-index, 0.689, 95% CI: 0.592– 0.787) in validation cohort. The calibration curves and the decision curve analysis (DCA) plot obtained suggested satisfying accuracy and clinical utility of the model. The risk stratification tool was able to predict differences in prognosis of patients in different risk categories (p< 0.001).
Conclusion: CT-based radiomics features, an in particular, radiomics nomograms, have the potential to become an accurate and reliable tool for assisting with prognosis prediction of LA-NPC.
Keywords: computed tomography, locoregionally advanced nasopharyngeal carcinoma, radiomics, nomogram
中文翻译：
基于 CT 的放射组学列线图预测局部晚期鼻咽癌无进展生存期
目的：我们旨在构建列线图来预测局部晚期鼻咽癌 (LA-NPC) 的无进展生存期 (PFS)，并使用计算机断层扫描 (CT) 影像组学特征和临床因素进行风险分层。
患者与方法：共纳入 2010 年至 2014 年间在我院诊断为 LA-NPC（III-IVa 期）的 311 例患者。手动勾勒出原发性鼻咽肿块的感兴趣区域 (ROI)。独立样本t检验和 LASSO 逻辑回归用于选择 PFS 最具预测性的放射组学特征，并生成放射组学特征。建立了具有临床因素和放射组学特征的列线图，并相应地测试了风险分层模型。
结果：总共选择了 20 个与预后最相关的放射组学特征。综合放射组学特征和重要临床因素的放射组学列线图在预测 PFS 方面表现出优异的性能，C-index 为 0.873（95% CI：0.803∼0.943），优于临床列线图（C-index , 0.729, 95% CI: 0.620∼0.838) 以及验证队列中的 TNM 分期系统 (C-index, 0.689, 95% CI: 0.592-0.787)。获得的校准曲线和决策曲线分析（DCA）图表明该模型的准确性和临床实用性令人满意。风险分层工具能够预测不同风险类别患者的预后差异（p < 0.001）。
结论：基于 CT 的放射组学特征，特别是放射组学列线图，有可能成为辅助 LA-NPC 预后预测的准确可靠的工具。
关键词：计算机断层扫描，局部晚期鼻咽癌，放射组学，列线图
更新日期：2021-09-02
Patients and Methods: A total of 311 patients diagnosed with LA-NPC (stage III–IVa) at our hospital between 2010 and 2014 were included. The region of interest (ROI) of the primary nasopharyngeal mass was manually outlined. Independent sample t-test and LASSO-logistic regression were used for selecting the most predictive radiomics features of PFS, and to generate a radiomics signature. A nomogram was built with clinical factors and radiomics features, and the risk stratification model was tested accordingly.
Results: In total, 20 radiomics features most associated with prognosis were selected. The radiomics nomogram, which integrated the radiomics signature and significant clinical factors, showed excellent performance in predicting PFS, with C-index of 0.873 (95% CI: 0.803∼ 0.943), which was better than that of the clinical nomogram (C-index, 0.729, 95% CI: 0.620∼ 0.838) as well as of the TNM staging system (C-index, 0.689, 95% CI: 0.592– 0.787) in validation cohort. The calibration curves and the decision curve analysis (DCA) plot obtained suggested satisfying accuracy and clinical utility of the model. The risk stratification tool was able to predict differences in prognosis of patients in different risk categories (p< 0.001).
Conclusion: CT-based radiomics features, an in particular, radiomics nomograms, have the potential to become an accurate and reliable tool for assisting with prognosis prediction of LA-NPC.
Keywords: computed tomography, locoregionally advanced nasopharyngeal carcinoma, radiomics, nomogram
中文翻译：
基于 CT 的放射组学列线图预测局部晚期鼻咽癌无进展生存期
目的：我们旨在构建列线图来预测局部晚期鼻咽癌 (LA-NPC) 的无进展生存期 (PFS)，并使用计算机断层扫描 (CT) 影像组学特征和临床因素进行风险分层。
患者与方法：共纳入 2010 年至 2014 年间在我院诊断为 LA-NPC（III-IVa 期）的 311 例患者。手动勾勒出原发性鼻咽肿块的感兴趣区域 (ROI)。独立样本t检验和 LASSO 逻辑回归用于选择 PFS 最具预测性的放射组学特征，并生成放射组学特征。建立了具有临床因素和放射组学特征的列线图，并相应地测试了风险分层模型。
结果：总共选择了 20 个与预后最相关的放射组学特征。综合放射组学特征和重要临床因素的放射组学列线图在预测 PFS 方面表现出优异的性能，C-index 为 0.873（95% CI：0.803∼0.943），优于临床列线图（C-index , 0.729, 95% CI: 0.620∼0.838) 以及验证队列中的 TNM 分期系统 (C-index, 0.689, 95% CI: 0.592-0.787)。获得的校准曲线和决策曲线分析（DCA）图表明该模型的准确性和临床实用性令人满意。风险分层工具能够预测不同风险类别患者的预后差异（p < 0.001）。
结论：基于 CT 的放射组学特征，特别是放射组学列线图，有可能成为辅助 LA-NPC 预后预测的准确可靠的工具。
关键词：计算机断层扫描，局部晚期鼻咽癌，放射组学，列线图
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