Department of General Surgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210008, China.
Department of General Surgery, Nanjing Drum Tower Hospital Clinical College of Xuzhou Medical University, Nanjing, 210008, Jiangsu, China.
Int J Colorectal Dis. 2024 Jun 3;39(1):84. doi: 10.1007/s00384-024-04653-4.
Lymph node metastasis (LNM) in colorectal cancer (CRC) patients is not only associated with the tumor's local pathological characteristics but also with systemic factors. This study aims to assess the feasibility of using body composition and pathological features to predict LNM in early stage colorectal cancer (eCRC) patients.
A total of 192 patients with T1 CRC who underwent CT scans and surgical resection were retrospectively included in the study. The cross-sectional areas of skeletal muscle, subcutaneous fat, and visceral fat at the L3 vertebral body level in CT scans were measured using Image J software. Logistic regression analysis were conducted to identify the risk factors for LNM. The predictive accuracy and discriminative ability of the indicators were evaluated using receiver operating characteristic (ROC) curves. Delong test was applied to compare area under different ROC curves.
LNM was observed in 32 out of 192 (16.7%) patients with eCRC. Multivariate analysis revealed that the ratio of skeletal muscle area to visceral fat area (SMA/VFA) (OR = 0.021, p = 0.007) and pathological indicators of vascular invasion (OR = 4.074, p = 0.020) were independent risk factors for LNM in eCRC patients. The AUROC for SMA/VFA was determined to be 0.740 (p < 0.001), while for vascular invasion, it was 0.641 (p = 0.012). Integrating both factors into a proposed predictive model resulted in an AUROC of 0.789 (p < 0.001), indicating a substantial improvement in predictive performance compared to relying on a single pathological indicator.
The combination of the SMA/VFA ratio and vascular invasion provides better prediction of LNM in eCRC.
结直肠癌（CRC）患者的淋巴结转移（LNM）不仅与肿瘤的局部病理特征有关，还与全身因素有关。本研究旨在评估使用人体成分和病理特征预测早期结直肠癌（eCRC）患者 LNM 的可行性。
回顾性纳入 192 例接受 CT 扫描和手术切除的 T1 CRC 患者。使用 Image J 软件测量 CT 扫描 L3 椎体水平骨骼肌、皮下脂肪和内脏脂肪的横截面积。采用 logistic 回归分析识别 LNM 的危险因素。使用接收者操作特征（ROC）曲线评估指标的预测准确性和判别能力。采用 Delong 检验比较不同 ROC 曲线下的面积。
192 例 eCRC 患者中 32 例（16.7%）发生 LNM。多因素分析显示，骨骼肌面积与内脏脂肪面积比（SMA/VFA）（OR=0.021，p=0.007）和血管侵犯的病理指标（OR=4.074，p=0.020）是 eCRC 患者发生 LNM 的独立危险因素。SMA/VFA 的 AUROC 为 0.740（p<0.001），而血管侵犯的 AUROC 为 0.641（p=0.012）。将这两个因素整合到一个预测模型中，AUROC 为 0.789（p<0.001），表明与依赖单一病理指标相比，预测性能有了显著提高。
SMA/VFA 比值与血管侵犯相结合可更好地预测 eCRC 患者的 LNM。
