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盆腔MRI联合SCC-Ag对宫颈癌淋巴结转移的预测价值 被引量:4

Predictive Value of Pelvic MRI Combined with SCC-Ag on Lymphatic Metastasis in Cervical Cancer
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摘要 目的分析宫颈癌淋巴转移患者的临床病理特点,联合盆腔MRI淋巴增大情况及SCC-Ag对宫颈癌患者淋巴结转移情况进行评估,并分析其预测价值。方法回顾性分析124例宫颈癌患者的资料,并根据结果建立预测模型。结果间质浸润深度、治疗前后血清SCC-Ag变化值、盆腔MRI淋巴结增大情况、D2-40、Ki67是宫颈癌淋巴结转移的独立危险因素(P<0.05)。预测模型建立为:L=SCC-Ag变化值+7.127×盆腔MRI显示淋巴结增大+5.386×D2-40+5.135×间质浸润深度+19.457×Ki67;预测敏感度为78.6%,特异性为79.2%。结论对于L≥20.8261的宫颈癌患者应提高警惕,给予个体化的新辅助治疗,并保证足够的手术范围。该模型对患者术前淋巴结转移具有一定的预测价值。 Objective To discuss the clinicopathological characteristics of cervical cancer patients with lymphatic metastasis,to evaluate lymph node metastasis in cervical cancer patients by combining pelvic MRI enlarged lymph nodes and SCC-Ag,and to analyze the prognostic value of the model.Methods We retrospectively analyzed the data of 124 patients with cervical cancer.The predictive model was established based on the result.Results The depth of interstitial infiltration,serum SCC-Ag change value before and after treatment,lymph node enlargement showed by pelvic MRI,D2-40 and Ki67 were independent risk factors for lymph node metastasis of cervical cancer(P<0.05).The prediction model of lymph node metastasis:L=the serum SCC-Ag change value+7.127×lymph node enlargement showed by pelvic MRI+5.386×D2-40+5.135×the depth of interstitial infiltration+19.457×Ki67;the sensitivity was 78.6%and specificity was 79.2%.Conclusion The cervical cancer patients with L≥20.8261 should be noticed.Doctors should give them individualized neoadjuvant treatment,and ensure adequate surgical scope.The above lymphatic prediction model has predictive value for preoperative lymph node metastasis.
作者 巨宇叶 苏芮 王晓慧 JU Yuye;SU Rui;WANG Xiaohui(The First School of Clinical Medicine,Lanzhou University,Lanzhou 730000,China;Department of Obstetrics and Gynecology,Lanzhou University First Hospital,Lanzhou 730000,China)
出处 《肿瘤防治研究》 CAS CSCD 2022年第5期448-452,共5页 Cancer Research on Prevention and Treatment
关键词 宫颈肿瘤 淋巴转移 鳞状上皮细胞癌抗原 磁共振成像 预测 Cervical cancer Lymphatic metastasis Squamous cell carcinoma-related antigen Magnetic resonance imaging Predictive
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