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纳入定量 PET 图像特征的食管癌预后模型的外部验证。

External validation of a prognostic model incorporating quantitative PET image features in oesophageal cancer.

机构信息

Division of Cancer & Genetics, School of Medicine, Cardiff University, UK.

Department of Radiation Oncology (MAASTRO Clinic), GROW School for Oncology and Development Biology, Maastricht University Medical Centre, The Netherlands.

出版信息

Radiother Oncol. 2019 Apr;133:205-212. doi: 10.1016/j.radonc.2018.10.033. Epub 2018 Nov 10.

Abstract

AIM

Enhanced prognostic models are required to improve risk stratification of patients with oesophageal cancer so treatment decisions can be optimised. The primary aim was to externally validate a published prognostic model incorporating PET image features. Transferability of the model was compared using only clinical variables.

METHODS

This was a Transparent Reporting of a multivariate prediction model for Individual Prognosis Or Diagnosis (TRIPOD) type 3 study. The model was validated against patients treated with neoadjuvant chemoradiotherapy according to the Neoadjuvant chemoradiotherapy plus surgery versus surgery alone for oesophageal or junctional cancer (CROSS) trial regimen using pre- and post-harmonised image features. The Kaplan-Meier method with log-rank significance tests assessed risk strata discrimination. A Cox proportional hazards model assessed model calibration. Primary outcome was overall survival (OS).

RESULTS

Between 2010 and 2015, 449 patients were included in the development (n = 302), internal validation (n = 101) and external validation (n = 46) cohorts. No statistically significant difference in OS between patient quartiles was demonstrated in prognostic models incorporating PET image features (X = 1.42, df = 3, p = 0.70) or exclusively clinical variables (age, disease stage and treatment; X = 1.19, df = 3, p = 0.75). The calibration slope β of both models was not significantly different from unity (p = 0.29 and 0.29, respectively). Risk groups defined using only clinical variables suggested differences in OS, although these were not statistically significant (X = 0.71, df = 2, p = 0.70).

CONCLUSION

The prognostic model did not enable significant discrimination between the validation risk groups, but a second model with exclusively clinical variables suggested some transferable prognostic ability. PET harmonisation did not significantly change the results of model validation.

摘要

目的

需要增强预后模型以改善食管癌患者的风险分层,从而优化治疗决策。主要目的是外部验证包含 PET 图像特征的已发表预后模型。仅使用临床变量比较模型的可转移性。

方法

这是一项符合透明报告多变量预测模型个体预后或诊断(TRIPOD)类型 3 研究的研究。根据 Neoadjuvant chemoradiotherapy plus surgery versus surgery alone for oesophageal or junctional cancer(CROSS)试验方案,使用预处理和后处理的图像特征,使用新辅助放化疗治疗的患者对该模型进行验证。Kaplan-Meier 方法和对数秩检验评估风险分层的区分度。Cox 比例风险模型评估模型校准。主要结局是总生存(OS)。

结果

2010 年至 2015 年间,449 例患者被纳入开发(n=302)、内部验证(n=101)和外部验证(n=46)队列。在包含 PET 图像特征的预后模型(X=1.42,df=3,p=0.70)或仅包含临床变量(年龄、疾病阶段和治疗;X=1.19,df=3,p=0.75)中,没有显示出 OS 与患者四分位区间之间存在统计学显著差异。两个模型的校准斜率β均与 1 无显著差异(p=0.29 和 0.29,分别)。仅使用临床变量定义的风险组提示 OS 存在差异,但无统计学意义(X=0.71,df=2,p=0.70)。

结论

该预后模型未能在验证风险组之间实现显著区分,但具有仅临床变量的第二个模型提示具有一定的可转移预后能力。PET 协调并未显著改变模型验证的结果。

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