Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Clin Lung Cancer. 2019 Nov;20(6):e638-e651. doi: 10.1016/j.cllc.2019.05.005. Epub 2019 May 11.
The purpose of the study was to investigate the potential of a radiomic signature developed in a general non-small-cell lung cancer (NSCLC) cohort for predicting the overall survival of anaplastic lymphoma kinase (ALK)-positive (ALK) patients with different treatment types.
After test-retest in the Reference Image Database to Evaluate Therapy Response data set, 132 features (intraclass correlation coefficient > 0.9) were selected in the least absolute shrinkage and selection operator Cox regression model with a leave-one-out cross-validation. The NSCLC radiomics collection from The Cancer Imaging Archive was randomly divided into a training set (n = 254) and a validation set (n = 63) to develop a general radiomic signature for NSCLC. In our ALK set, 35 patients received targeted therapy and 19 patients received nontargeted therapy. The developed signature was tested later in this ALK set. Performance of the signature was evaluated with the concordance index (C-index) and stratification analysis.
The general signature had good performance (C-index > 0.6; log rank P < .05) in the NSCLC radiomics collection. It includes 5 features: Geom_va_ratio, W_GLCM_Std, W_GLCM_DV, W_GLCM_IM2, and W_his_mean. Its accuracy of predicting overall survival in the ALK set achieved 0.649 (95% confidence interval [CI], 0.640-0.658). Nonetheless, impaired performance was observed in the targeted therapy group (C-index = 0.573; 95% CI, 0.556-0.589) whereas significantly improved performance was observed in the nontargeted therapy group (C-index = 0.832; 95% CI, 0.832-0.852). Stratification analysis also showed that the general signature could only identify high- and low-risk patients in the nontargeted therapy group (log rank P = .00028).
This preliminary study suggests that the applicability of a general signature to ALK patients is limited. The general radiomic signature seems to be only applicable to ALK patients who had received nontargeted therapy, which indicates that developing special radiomics signatures for patients treated with tyrosine kinase inhibitors might be necessary.
本研究的目的是探讨在一般非小细胞肺癌（NSCLC）队列中开发的放射组学特征是否可用于预测不同治疗类型的间变性淋巴瘤激酶（ALK）阳性（ALK）患者的总生存期。
在参考图像数据库中进行测试-再测试以评估治疗反应数据集中，采用内部相关系数> 0.9 的最小绝对值收缩和选择算子 Cox 回归模型选择 132 个特征（留一交叉验证）。从癌症成像档案中随机抽取 NSCLC 放射组学集，分为训练集（n = 254）和验证集（n = 63），以开发用于 NSCLC 的一般放射组学特征。在我们的 ALK 组中，35 名患者接受了靶向治疗，19 名患者接受了非靶向治疗。后来在这个 ALK 组中测试了开发的特征。使用一致性指数（C-index）和分层分析评估特征的性能。
一般特征在 NSCLC 放射组学集中具有良好的性能（C-index> 0.6；对数秩 P <.05）。它包括 5 个特征：Geom_va_ratio、W_GLCM_Std、W_GLCM_DV、W_GLCM_IM2 和 W_his_mean。其在 ALK 组中预测总生存期的准确性为 0.649（95%置信区间[CI]，0.640-0.658）。然而，在靶向治疗组中观察到性能受损（C-index = 0.573；95%CI，0.556-0.589），而在非靶向治疗组中观察到显著改善的性能（C-index = 0.832；95%CI，0.832-0.852）。分层分析还表明，一般特征只能在非靶向治疗组中识别高风险和低风险患者（对数秩 P =.00028）。
这项初步研究表明，一般特征在 ALK 患者中的适用性有限。一般放射组学特征似乎仅适用于接受非靶向治疗的 ALK 患者，这表明为接受酪氨酸激酶抑制剂治疗的患者开发特殊的放射组学特征可能是必要的。
