Development and validation of an individualized nomogram to identify occult peritoneal metastasis in patients with advanced gastric cancer
Development and validation of an individualized nomogram to identify occult peritoneal metastasis in patients with advanced gastric cancer
复制标题
开发和验证个体化列线图以识别晚期胃癌患者隐匿性腹膜转移
DOI：
10.1093/annonc/mdz001
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发表时间：
2019-03-01
影响因子：
50.5
通讯作者：
Ji, J-F
中科院分区：
文献类型：
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作者：
Dong, D.;Tang, L.;Ji, J-F
背景晚期胃癌（AGC）患者的隐性腹膜转移（PM）在计算机断层扫描（CT）上很可能被遗漏。隐匿性pm患者往往发现较晚，甚至手术治疗不当。因此，我们的目标是开发一种放射组学图来术前识别AGC患者的隐匿性pm。患者和方法来自4个中心的554例AGC患者被分为1个训练队列、1个内部验证队列和2个外部验证队列。所有患者的PM状态均先通过CT诊断为阴性，后经腹腔镜确认（PM阳性122例，PM阴性432例）。从266个定量图像特征中建立反映原发肿瘤（RS1）和腹膜区域（RS2）表型的放射组学特征作为PM的预测因子。将RS1、RS2或临床因素纳入PM状态的个体化形态图，并对其预测能力进行评估。结果RS1、RS2、Lauren型是隐匿性PM的显著预测因子（均P < 0.05）。这三个因素的nomogram显示出比单独使用RS1、RS2或临床因素的模型更好的诊断准确性（所有净再分类改善P < 0.05）。训练、内部和两个外部验证队列的曲线下面积分别为0.958[95%可信区间（CI） 0.923-0.993]、0.941 （95% CI 0.904-0.977）、0.928 （95% CI 0.886-0.971）和0.920 （95% CI 0.862-0.978）。分层分析表明，该模态图具有潜在的泛化能力。结论原发性肿瘤及附近腹膜CT表型与隐匿性PM状态有显著相关性。这些CT表型和Lauren型的形态图对隐匿性PM有很好的预测能力，可能对AGC隐匿性PM的早期发现有重要的临床意义。
Abstract Background Occult peritoneal metastasis (PM) in advanced gastric cancer (AGC) patients is highly possible to be missed on computed tomography (CT) images. Patients with occult PMs are subject to late detection or even improper surgical treatment. We therefore aimed to develop a radiomic nomogram to preoperatively identify occult PMs in AGC patients. Patients and methods A total of 554 AGC patients from 4 centers were divided into 1 training, 1 internal validation, and 2 external validation cohorts. All patients’ PM status was firstly diagnosed as negative by CT, but later confirmed by laparoscopy (PM-positive n = 122, PM-negative n = 432). Radiomic signatures reflecting phenotypes of the primary tumor (RS1) and peritoneum region (RS2) were built as predictors of PM from 266 quantitative image features. Individualized nomograms of PM status incorporating RS1, RS2, or clinical factors were developed and evaluated regarding prediction ability. Results RS1, RS2, and Lauren type were significant predictors of occult PM (all P < 0.05). A nomogram of these three factors demonstrated better diagnostic accuracy than the model with RS1, RS2, or clinical factors alone (all net reclassification improvement P < 0.05). The area under curve yielded was 0.958 [95% confidence interval (CI) 0.923–0.993], 0.941 (95% CI 0.904–0.977), 0.928 (95% CI 0.886–0.971), and 0.920 (95% CI 0.862–0.978) for the training, internal, and two external validation cohorts, respectively. Stratification analysis showed that this nomogram had potential generalization ability. Conclusion CT phenotypes of both primary tumor and nearby peritoneum are significantly associated with occult PM status. A nomogram of these CT phenotypes and Lauren type has an excellent prediction ability of occult PM, and may have significant clinical implications on early detection of occult PM for AGC.