Department of Gastrointestinal Surgery, Renmin Hospital of Wuhan University, Wuhan, 430060 Hu Bei Province, China.
Dis Markers. 2020 Dec 9;2020:1418978. doi: 10.1155/2020/1418978. eCollection 2020.
In patients with gastric cancer (GC), peritoneal metastasis is an indication of the end stage and often indicates a poor outcome. The diagnosis of peritoneal metastasis, especially occult peritoneal metastasis (OPM), remains a challenge for surgeons. This study was designed to explore the relationship between OPM and clinicopathological characteristics and preoperative hematological parameters in patients with GC and to develop a nomogram to predict the probability of OPM before surgery.
A total of 672 patients with GC from our center were included, including 583 OPM-negative and 89 OPM-positive patients. These patients were divided into training and validation groups based on when they received treatment. OPM was diagnosed during surgery in patients without any signs of metastasis through imaging examination. Predictive factors were screened by least absolute shrinkage and selection operator logistic regression of all 18 characteristics. The nomogram of OPM was constructed based on these filtered variables. The discriminative and calibration performance of the model were simultaneously evaluated.
A total of six variables, including tumor size, degree of differentiation, depth of invasion, Glasgow prognosis score, and plasma levels of CA125 and fibrinogen, were selected for integration into the final predictive nomogram. The area under curve (AUC) of the nomogram with six factors was 0.906 (95% confidence interval (CI): 0.872-0.941) and 0.889 (95% CI: 0.795-0.984) in the training and validation groups, respectively. Calibration plots of the nomogram in the two sets revealed a good consistency between predicted and actual probabilities. Decision curve analysis showed that the nomogram had a positive net benefit among all threshold probabilities between 0% and 82%. This nomogram was superior to models incorporating only clinicopathologic or hematologic features.
Both clinicopathological and preoperative hematological parameters are significantly associated with OPM. The nomogram constructed with six factors could be used to calculate the probability of OPM and identify the high-risk population in GC. This may be helpful for early detection of OPM in patients with GC.
在胃癌（GC）患者中，腹膜转移是终末期的表现，通常预示着预后不良。腹膜转移的诊断，特别是隐匿性腹膜转移（OPM），仍然是外科医生面临的挑战。本研究旨在探讨 OPM 与 GC 患者临床病理特征和术前血液学参数之间的关系，并建立一个术前预测 OPM 概率的列线图。
本研究共纳入了来自我们中心的 672 例 GC 患者，其中 583 例为 OPM 阴性，89 例为 OPM 阳性。这些患者根据治疗时间分为训练组和验证组。OPM 是通过对无任何转移迹象的患者进行影像学检查时在手术中诊断出来的。通过 18 项特征的最小绝对收缩和选择算子逻辑回归筛选预测因素。基于这些筛选出的变量构建 OPM 的列线图。同时评估模型的判别和校准性能。
共筛选出包括肿瘤大小、分化程度、浸润深度、格拉斯哥预后评分以及血浆 CA125 和纤维蛋白原水平在内的 6 个变量，整合到最终的预测列线图中。包含 6 个因素的列线图在训练组和验证组的曲线下面积（AUC）分别为 0.906（95%置信区间（CI）：0.872-0.941）和 0.889（95%CI：0.795-0.984）。两组列线图的校准图显示预测概率与实际概率之间具有良好的一致性。决策曲线分析表明，在 0%至 82%的所有阈值概率下，该列线图具有正的净获益。与仅包含临床病理或血液学特征的模型相比，该列线图具有优势。
临床病理和术前血液学参数均与 OPM 显著相关。基于 6 个因素构建的列线图可用于计算 OPM 的概率并识别 GC 中的高危人群。这可能有助于早期发现 GC 中的 OPM。
