Li Shao-Qing, Zhang Ke-Cheng, Li Ji-Yang, Liang Wen-Quan, Gao Yun-He, Qiao Zhi, Xi Hong-Qing, Chen Lin
Department of General Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing 100853, China.
World J Clin Cases. 2020 Oct 6;8(19):4331-4341. doi: 10.12998/wjcc.v8.i19.4331.
Ovarian metastasis is a special type of distant metastasis unique to female patients with gastric cancer. The pathogenesis of ovarian metastasis is incompletely understood, and the treatment options are controversial. Few studies have predicted the risk of ovarian metastasis. It is not clear which type of gastric cancer is more likely to metastasize to the ovary. A prediction model based on risk factors is needed to improve the rate of detection and diagnosis.
To analyze risk factors of ovarian metastasis in female patients with gastric cancer and establish a nomogram to predict the probability of occurrence based on different clinicopathological features.
A retrospective cohort of 1696 female patients with gastric cancer between January 2006 and December 2017 were included in a single center, and patients with distant metastasis other than ovary and peritoneum metastasis were excluded. Potential risk factors for ovarian metastasis were analyzed using univariate and multivariable logistic regression. Independent risk factors were chosen to construct a nomogram which received internal validation.
Ovarian metastasis occurred in 83 of 1696 female patients. Univariate analysis showed that age, Lauren type, whether the primary lesion contained signet-ring cells, vascular tumor emboli, T stage, N stage, the expression of estrogen receptor, the expression of progesterone receptor, serum carbohydrate antigen 125 and the neutrophil-to-lymphocyte ratio were risk factors for ovarian metastasis of gastric cancer (all < 0.05). Multivariate analysis showed that age ≤ 50 years, Lauren typing of non-intestinal, gastric cancer lesions containing signet-ring cell components, N stage > N2, positive expression of estrogen receptor, serum carbohydrate antigen 125 > 35 U/mL, and a neutrophil-to-lymphocyte ratio > 2.16 were independent risk factors (all < 0.05). The independent risk factors were constructed into a nomogram model using R language software. The consistency index after continuous correction was 0.840 [95% confidence interval: (0.774-0.906)]. After the internal self-sampling (Bootstrap) test, the calibration curve of the model was obtained with an average absolute error of 0.007. The receiver operating characteristic curve of the obtained model was drawn. The area under the curve was 0.867, the maximal Youden index was 0.613, the corresponding sensitivity was 0.794, and the specificity was 0.819.
The nomogram model performed well in the prediction of ovarian metastasis. Attention should be paid to the possibility of ovarian metastasis in high-risk populations during re-examination, to ensure early detection and treatment.
卵巢转移是女性胃癌患者特有的一种特殊类型的远处转移。卵巢转移的发病机制尚未完全明确，治疗方案存在争议。很少有研究预测卵巢转移的风险。目前尚不清楚哪种类型的胃癌更容易转移至卵巢。需要一种基于风险因素的预测模型来提高检出率和诊断率。
分析女性胃癌患者卵巢转移的风险因素，并建立一种列线图，根据不同的临床病理特征预测其发生概率。
纳入2006年1月至2017年12月在单中心就诊的1696例女性胃癌患者的回顾性队列，排除有卵巢和腹膜以外远处转移的患者。采用单因素和多因素logistic回归分析卵巢转移的潜在风险因素。选择独立风险因素构建列线图并进行内部验证。
1696例女性患者中83例发生卵巢转移。单因素分析显示，年龄、Lauren分型、原发灶是否含印戒细胞、血管肿瘤栓子、T分期、N分期、雌激素受体表达、孕激素受体表达、血清糖类抗原125及中性粒细胞与淋巴细胞比值是胃癌卵巢转移的风险因素（均P<0.05）。多因素分析显示，年龄≤50岁、非肠型Lauren分型、含印戒细胞成分的胃癌病灶、N分期>N2、雌激素受体阳性表达、血清糖类抗原125>35 U/mL及中性粒细胞与淋巴细胞比值>2.16是独立风险因素（均P<0.05）。使用R语言软件将独立风险因素构建成列线图模型。连续校正后的一致性指数为0.840[95%置信区间：(0.774 - 0.906)]。经过内部自助抽样（Bootstrap）检验，得到模型的校准曲线，平均绝对误差为0.007。绘制所得模型的受试者工作特征曲线。曲线下面积为0.867，最大约登指数为0.613，相应的灵敏度为0.794，特异度为0.819。
列线图模型在预测卵巢转移方面表现良好。复查时应关注高危人群发生卵巢转移的可能性，以确保早期发现和治疗。
