He Lan, Li Zhenhui, Chen Xin, Huang Yanqi, Yan Lixu, Liang Changhong, Liu Zaiyi
Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China.
Department of Radiology, the Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming 650118, China.
Chin J Cancer Res. 2021 Oct 31;33(5):592-605. doi: 10.21147/j.issn.1000-9604.2021.05.06.
To develop and validate a radiomics prognostic scoring system (RPSS) for prediction of progression-free survival (PFS) in patients with stage IV non-small cell lung cancer (NSCLC) treated with platinum-based chemotherapy.
In this retrospective study, four independent cohorts of stage IV NSCLC patients treated with platinum-based chemotherapy were included for model construction and validation (Discovery: n=159; Internal validation: n=156; External validation: n=81, Mutation validation: n=64). First, a total of 1,182 three-dimensional radiomics features were extracted from pre-treatment computed tomography (CT) images of each patient. Then, a radiomics signature was constructed using the least absolute shrinkage and selection operator method (LASSO) penalized Cox regression analysis. Finally, an individualized prognostic scoring system incorporating radiomics signature and clinicopathologic risk factors was proposed for PFS prediction.
The established radiomics signature consisting of 16 features showed good discrimination for classifying patients with high-risk and low-risk progression to chemotherapy in all cohorts (All P<0.05). On the multivariable analysis, independent factors for PFS were radiomics signature, performance status (PS), and N stage, which were all selected into construction of RPSS. The RPSS showed significant prognostic performance for predicting PFS in discovery [C-index: 0.772, 95% confidence interval (95% CI): 0.765-0.779], internal validation (C-index: 0.738, 95% CI: 0.730-0.746), external validation (C-index: 0.750, 95% CI: 0.734-0.765), and mutation validation (C-index: 0.739, 95% CI: 0.720-0.758). Decision curve analysis revealed that RPSS significantly outperformed the clinicopathologic-based model in terms of clinical usefulness (All P<0.05).
This study established a radiomics prognostic scoring system as RPSS that can be conveniently used to achieve individualized prediction of PFS probability for stage IV NSCLC patients treated with platinum-based chemotherapy, which holds promise for guiding personalized pre-therapy of stage IV NSCLC.
开发并验证一种放射组学预后评分系统（RPSS），用于预测接受铂类化疗的IV期非小细胞肺癌（NSCLC）患者的无进展生存期（PFS）。
在这项回顾性研究中，纳入了四个接受铂类化疗的IV期NSCLC患者独立队列，用于模型构建和验证（发现队列：n = 159；内部验证队列：n = 156；外部验证队列：n = 81；突变验证队列：n = 64）。首先，从每位患者的治疗前计算机断层扫描（CT）图像中提取总共1182个三维放射组学特征。然后，使用最小绝对收缩和选择算子方法（LASSO）惩罚Cox回归分析构建放射组学特征。最后，提出了一种结合放射组学特征和临床病理危险因素的个体化预后评分系统，用于PFS预测。
所建立的由16个特征组成的放射组学特征在所有队列中对化疗高风险和低风险进展患者的分类具有良好的区分能力（所有P<0.05）。在多变量分析中，PFS的独立因素为放射组学特征、体能状态（PS）和N分期，这些均被纳入RPSS的构建。RPSS在发现队列[C指数：0.772，95%置信区间（95%CI）：0.765 - 0.779]、内部验证队列（C指数：0.738，95%CI：0.730 - 0.746）、外部验证队列（C指数：0.750，95%CI：0.734 - 0.765）和突变验证队列（C指数：0.739，95%CI：0.720 - 0.758）中对PFS的预测具有显著的预后性能。决策曲线分析显示，RPSS在临床实用性方面显著优于基于临床病理的模型（所有P<0.05）。
本研究建立了一种放射组学预后评分系统即RPSS，可方便地用于实现对接受铂类化疗的IV期NSCLC患者PFS概率的个体化预测，这为指导IV期NSCLC的个性化治疗前评估提供了前景。
