Department of Radiation Oncology, Cancer Hospital of Shantou University Medical College, Shantou City, China.
Department of Oncology, CRUK/MRC Oxford Institute for Radiation Oncology, University of Oxford, Oxford, UK.
Radiat Oncol. 2021 Jan 12;16(1):8. doi: 10.1186/s13014-020-01699-w.
This study aimed to evaluate the predictive potential of contrast-enhanced computed tomography (CT)-based imaging biomarkers (IBMs) for the treatment outcomes of patients with oesophageal squamous cell carcinoma (OSCC) after definitive concurrent chemoradiotherapy (CCRT).
Altogether, 154 patients with OSCC who underwent definitive CCRT were included in this retrospective study. All patients were randomised to the training cohort (n = 99) or the validation cohort (n = 55). Pre-treatment contrast-enhanced CT scans were obtained for all patients and used for the extraction of IBMs. An IBM score, was constructed by using the least absolute shrinkage and selection operator with Cox regression analysis, which was equal to the log-partial hazard of the Cox model in the training cohort and tested in the validation cohort. IBM nomograms were built based on IBM scores for individualised survival estimation. Finally, a decision curve analysis was performed to estimate the clinical usefulness of the nomograms.
Altogether, 96 IBMs were extracted from each contrast-enhanced CT scan. IBM scores were constructed from 11 CT-based IBMs for overall survival (OS) and 8 IBMs for progression-free survival (PFS), using the LASSO-Cox regression method in the training cohort. Multivariate analysis revealed that IBM score was an independent prognostic factor correlated with OS and PFS. In the training cohort, the C-indices of IBM scores were 0.734 (95% CI 0.664-0.804) and 0.658 (95% CI 0.587-0.729) for OS and PFS, respectively. In the validation cohort, C-indices were 0.672 (95% CI 0.578-0.766) and 0.666 (95% CI 0.574-0.758) for OS and PFS, respectively. Kaplan-Meier survival analysis showed a significant difference between risk subgroups in the training and validation cohorts. Decision curve analysis confirmed the clinical usefulness of the IBM score.
The IBM score based on pre-treatment contrast-enhanced CT could predict the OS and PFS for patients with OSCC after definitive CCRT. Further multicentre studies with larger sample sizes are warranted.
本研究旨在评估增强 CT 成像生物标志物（IBMs）对接受根治性同步放化疗（CCRT）的食管鳞癌（OSCC）患者治疗结局的预测潜力。
本回顾性研究共纳入 154 例接受根治性 CCRT 的 OSCC 患者。所有患者均被随机分为训练队列（n=99）或验证队列（n=55）。所有患者均行增强 CT 扫描，用于提取 IBM。采用最小绝对值收缩和选择算子（LASSO）与 Cox 回归分析构建 IBM 评分，该评分在训练队列中等于 Cox 模型的对数偏风险，在验证队列中进行验证。基于 IBM 评分构建个体化生存估计的 IBM 列线图。最后，采用决策曲线分析评估列线图的临床实用性。
从每个增强 CT 扫描中提取了 96 个 IBM。采用 LASSO-Cox 回归方法，在训练队列中，从 11 个基于 CT 的 IBM 中构建了总生存（OS）和 8 个 IBM 构建无进展生存（PFS）的 IBM 评分。多变量分析显示，IBM 评分是与 OS 和 PFS 相关的独立预后因素。在训练队列中，IBM 评分的 C 指数分别为 OS 和 PFS 的 0.734（95%CI 0.664-0.804）和 0.658（95%CI 0.587-0.729）。在验证队列中，C 指数分别为 OS 和 PFS 的 0.672（95%CI 0.578-0.766）和 0.666（95%CI 0.574-0.758）。Kaplan-Meier 生存分析显示，在训练和验证队列中，风险亚组之间存在显著差异。决策曲线分析证实了 IBM 评分的临床实用性。
基于治疗前增强 CT 的 IBM 评分可预测接受根治性 CCRT 的 OSCC 患者的 OS 和 PFS。需要进一步开展更大样本量的多中心研究。
