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基于计算机断层扫描的放射组学列线图预测局部晚期胃癌新辅助化疗的治疗反应:一种治疗预测评分。

Computed tomography-based radiomics nomogram for predicting therapeutic response to neoadjuvant chemotherapy in locally advanced gastric cancer : A scale for treatment predicting.

机构信息

Department of Gastrointestinal Surgery, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China.

School of Basic Medical Sciences, Wenzhou Medical University, Wenzhou, Zhejiang, China.

出版信息

Clin Transl Oncol. 2024 Aug;26(8):1944-1955. doi: 10.1007/s12094-024-03417-4. Epub 2024 Mar 11.

Abstract

BACKGROUND AND OBJECTIVE

Neoadjuvant chemotherapy results in various responses when used to treat locally advanced gastric cancer, we aimed to develop and validate a predictive model of the response to neoadjuvant chemotherapy in patients with gastric cancer.

METHODS

A total of 128 patients with locally advanced gastric cancer who underwent pre-treatment computed tomography (CT) scanning followed by neoadjuvant chemoradiotherapy were included (training cohort: n = 64; validation cohort: n = 64). We built a radiomics score combined with laboratory parameters to create a nomogram for predicting the efficacy of neoadjuvant chemotherapy and calculating scores for risk factors.

RESULTS

The radiomics score system demonstrated good stability and prediction performance for the response to neoadjuvant chemotherapy, with the area under the curve of the training and validation cohorts being 0.8 and 0.64, respectively. The radiomics score proved to be an independent risk factor affecting the efficacy of neoadjuvant chemotherapy. In addition to the radiomics score, four other risk factors were included in the nomogram, namely the platelet-to-lymphocyte ratio, total bilirubin, ALT/AST, and CA199. The model had a C-index of 0.8.

CONCLUSIONS

Our results indicated that radiomics features could be potential biomarkers for the early prediction of the response to neoadjuvant treatment.

摘要

背景与目的

新辅助化疗用于治疗局部晚期胃癌时会产生各种反应,我们旨在开发和验证一种用于预测胃癌患者新辅助化疗反应的模型。

方法

共纳入 128 例接受术前计算机断层扫描(CT)扫描后行新辅助放化疗的局部晚期胃癌患者(训练队列:n=64;验证队列:n=64)。我们构建了一个放射组学评分系统,结合实验室参数,创建了一个预测新辅助化疗疗效和计算危险因素评分的列线图。

结果

放射组学评分系统对新辅助化疗的反应具有良好的稳定性和预测性能,训练队列和验证队列的曲线下面积分别为 0.8 和 0.64。放射组学评分被证明是影响新辅助化疗疗效的独立危险因素。除了放射组学评分外,列线图还纳入了血小板与淋巴细胞比值、总胆红素、ALT/AST 和 CA199 这四个其他危险因素。该模型的 C 指数为 0.8。

结论

我们的研究结果表明,放射组学特征可能是新辅助治疗反应早期预测的潜在生物标志物。

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