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A Nomogram Based on Clinicopathologic Features and Preoperative Hematology Parameters to Predict Occult Peritoneal Metastasis of Gastric Cancer: A Single-Center Retrospective Study
Disease Markers ( IF 3.464 ) Pub Date : 2020-12-10 , DOI: 10.1155/2020/1418978
Chao Yang 1 , Yujie Yang 1 , Xiaodong Huang 1 , HuaLi Li 1 , Huangrong Cheng 1 , Shilun Tong 1 , Yongbin Zheng 1
Affiliation  

Background. 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. Methods. 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. Results. 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. Conclusion. 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.

中文翻译:

基于临床病理学特征和术前血液学参数预测胃癌隐匿性腹膜转移的列线图:单中心回顾性研究

背景。在胃癌 (GC) 患者中,腹膜转移是终末期的标志,通常表明预后不佳。腹膜转移的诊断,尤其是隐匿性腹膜转移(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,并开发列线图来预测术前 OPM 的概率。方法。本中心共纳入 672 例 GC 患者,其中 OPM 阴性 583 例,OPM 阳性 89 例。这些患者根据接受治疗的时间分为训练组和验证组。影像学检查无任何转移迹象的患者在手术过程中诊断为 OPM。通过所有 18 个特征的最小绝对收缩和选择算子逻辑回归筛选预测因素。OPM 的列线图是基于这些过滤变量构建的。同时评估模型的判别和校准性能。结果。总共选择了六个变量,包括肿瘤大小、分化程度、侵袭深度、格拉斯哥预后评分以及血浆 CA125 和纤维蛋白原水平,用于整合到最终的预测列线图中。在训练组和验证组中,具有六个因素的列线图的曲线下面积 (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了预测概率和实际概率之间的良好一致性。决策曲线分析表明,列线图在 0% 到 82% 之间的所有阈值概率中具有正的净收益。该列线图优于仅包含临床病理学或血液学特征的模型。结论。临床病理学和术前血液学参数均与 OPM 显着相关。由六个因素构建的列线图可用于计算 OPM 的概率并识别 GC 的高危人群。这可能有助于早期发现 GC 患者的 OPM。
更新日期:2020-12-10
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