一种放射组学预后评分系统,用于预测IV期非小细胞肺癌患者接受铂类化疗的无进展生存期。

Lan He, Zhenhui Li, Xin Chen, Yanqi Huang, Lixu Yan, Changhong Liang, Zaiyi Liu
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引用次数: 7

摘要

目的:开发并验证放射组学预后评分系统(RPSS),用于预测IV期非小细胞肺癌(NSCLC)患者接受铂类化疗的无进展生存期(PFS)。方法:在这项回顾性研究中,4个独立的IV期非小细胞肺癌患者接受铂类化疗,用于模型构建和验证(发现:n=159;内部验证:n=156;外部验证:n=81,突变验证:n=64)。首先,从每位患者的术前CT图像中提取了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,用于预测PFS。结果:建立的放射组学特征包括16个特征,在所有队列中对高危和低风险进展到化疗的患者进行分类时具有良好的区分能力。本研究建立了放射组学预后评分系统RPSS,可方便地实现IV期NSCLC铂类化疗患者PFS概率的个体化预测,有望指导IV期NSCLC的个体化前治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A radiomics prognostic scoring system for predicting progression-free survival in patients with stage IV non-small cell lung cancer treated with platinum-based chemotherapy.

A radiomics prognostic scoring system for predicting progression-free survival in patients with stage IV non-small cell lung cancer treated with platinum-based chemotherapy.

A radiomics prognostic scoring system for predicting progression-free survival in patients with stage IV non-small cell lung cancer treated with platinum-based chemotherapy.

A radiomics prognostic scoring system for predicting progression-free survival in patients with stage IV non-small cell lung cancer treated with platinum-based chemotherapy.

Objective: 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.

Methods: 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.

Results: 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).

Conclusions: 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.

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