非增强CT上长短轴直径的Δ平均值与可切除非小细胞肺癌新辅助免疫治疗的主要病理反应相关
ΔAverage of long and short axis diameter on non-contrast CT is associated with major pathological response to neoadjuvant immunotherapy in resectable non-small cell lung cancer.
作者
作者单位
- Department of Radiology, Mianyang Central Hospital, Mianyang, China.
- Department of Respiratory and Critical Care, Xuanwu Hospital, Capital Medical University, Beijing, China.
- Medical School of Chinese People's Liberation Army General Hospital, Beijing, China.
- Department of Radiology, Affiliated Zhongshan Hospital of Dalian University, Dalian, China.
- Department of Respiratory and Critical Care, Emergency and Critical Care Medical Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
- Department of Respiratory and Critical Care, Affiliated Hospital of Shandong Second Medical University, Weifang, China.
- Department of Radiology, Affiliated Zhongshan Hospital of Dalian University, Dalian, China. cjr.wujianlin@vip.163.com.
- Department of Respiratory and Critical Care, Xuanwu Hospital, Capital Medical University, Beijing, China. xuexinying@xwhosp.org.
摘要
中文
非小细胞肺癌的新辅助免疫治疗显示出异质性疗效，实体瘤疗效评价标准1.1版（RECIST 1.1）无法准确预测病理反应。目的是探索与预测新辅助免疫治疗疗效相关的计算机断层扫描（CT）参数，并比较其与RECIST 1.1的性能。这项多中心回顾性研究纳入了2018年9月至2023年7月期间接受新辅助免疫治疗的48名可切除I-IIIB期非小细胞肺癌患者。在治疗前后测量了CT密度参数（CT值和相对CT值）和形态学特征（平均直径、体积、表面积）。主要病理反应（≤10%残留肿瘤细胞）作为参考标准。采用受试者工作特征曲线分析和逻辑回归评估参数性能。Δ平均直径对主要病理反应表现出最高的预测准确性（曲线下面积0.83，p<0.001），敏感性76%，特异性84%，总准确度79.2%，数值上高于实体瘤疗效评价标准1.1版（72.9%），但未进行正式的优效性统计检验。在探索性多变量分析中，它是唯一保留与主要病理反应独立关联的参数（比值比11.91，95%置信区间1.52-93.11，p=0.018）。Δ平均直径是预测新辅助免疫治疗病理反应的有前景的影像生物标志物。在该队列中，它显示出数值上高于RECIST 1.1的准确性；然而，这些发现是假设生成的，在临床实施前需要内部和外部验证。问题:可切除非小细胞肺癌的新辅助免疫治疗显示异质性疗效，RECIST 1.1无法预测主要病理反应，需要可靠的生物标志物。发现:Δ平均直径与主要病理反应相关（AUC=0.83），显示出数值上高于RECIST 1.1的准确性，并代表一个探索性的独立预测因子。临床相关性:这个简单的CT参数有望识别非完全缓解者的治疗疗效，有助于个性化治疗决策，并在无需复杂影像组学或昂贵正电子发射断层扫描的情况下提高免疫治疗评估的准确性。
English
Neoadjuvant immunotherapy for non-small cell lung cancer shows heterogeneous efficacy, and Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1) fails to accurately predict pathological response. The objective was to explore computed tomography parameters associated with neoadjuvant immunotherapy efficacy and compare their performance with RECIST 1.1. This multicenter retrospective study included 48 patients with resectable stage I-IIIB non-small cell lung cancer who received neoadjuvant immunotherapy between September 2018 and July 2023. Computed tomography density parameters (computed tomography value and relative computed tomography value) and morphological characteristics (mean diameter, volume, surface area) were measured before and after treatment. Major pathological response (≤ 10% residual tumor cells) served as the reference standard. Receiver operating characteristic analysis and logistic regression evaluated parameter performance. ΔMean diameter demonstrated the highest predictive accuracy for major pathological response (area under the curve 0.83, p < 0.001), with 76% sensitivity, 84% specificity, and 79.2% overall accuracy, with numerically higher accuracy than Response Evaluation Criteria in Solid Tumors version 1.1 (72.9%), though no formal statistical test for superiority was conducted. In exploratory multivariable analysis, it was the only parameter retaining independent association with major pathological response (odds ratio 11.91, 95% confidence interval 1.52-93.11, p = 0.018). ΔMean diameter is a promising imaging biomarker for predicting pathological response to neoadjuvant immunotherapy. In this cohort, it showed numerically higher accuracy than RECIST 1.1; however, these findings are hypothesis-generating and require both internal and external validation before clinical implementation. Question Neoadjuvant immunotherapy for resectable non-small cell lung cancer shows heterogeneous efficacy, and RECIST 1.1 fails to predict major pathological response, requiring reliable biomarkers. Findings ΔMean diameter was associated with major pathological response (AUC = 0.83), showed numerically higher accuracy than RECIST 1.1, and represented an exploratory independent predictor. Clinical relevance This simple computed tomography parameter shows promise for identifying treatment efficacy in non-complete responders, aids personalized therapy decisions, and improves the accuracy of immunotherapy evaluation without complex radiomics or costly positron emission tomography.
分类与指标
- 研究类型
- 临床研究
- 病种
- 肺癌
- JCR 分区
- Q1
- 影响因子
- 6.0
- 新锐分区
- 2区