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我们应用法国CIS公司CA-125 IRMA及国产CEA-RIA试剂盒,对卵巢痛及其它在临床诊断上易与卵巢癌相混淆的疾病如:卵巢良性病变、其他妇科恶性肿瘤、结直肠癌及妇科炎症,以探讨血清CA-125与CEA联合检测在卵巢癌的诊断和鉴别诊断上的价值。 对象和方法 一、对象:正常健康妇女47名,均为体检正常者。各类良、恶性肿瘤及妇科炎症均取自本院就诊患者,诊断皆经临床、B超和病理证实。其中42例卵巢癌,29例卵巢良性病变(卵巢囊肿26例,畸胎瘤3例),妇科其他恶性肿瘤19例(输卵管癌3例,宫颈癌10例,子宫内膜癌2例,子宫体癌4例);结直肠癌23例,妇科炎症18例,由静脉取血,分离血清后于-20℃保存备用。 二、方法:CA-125免疫放射试剂盒(CIS Bio International)和CEA放免试剂盒(中国原子能科学研究院),操作按说明书,测量仪器为1470 WIZA RDTM计数仪。两种试剂盒批内CV分别为2.73%,3.46%,批间CV为3.6%和4.27%,CA-125水平用±S表示,以±2S为阳性界值,均值差异分析采用t检验,阳性率差异分析用X~2检验。
We use the French CIS company CA-125 IRMA and domestic CEA-RIA kit for ovarian and other clinical diagnosis of ovarian cancer easily confused with diseases such as: benign ovarian disease, other gynecologic malignancies, colorectal cancer and gynecology Inflammation in order to explore the serum CA-125 and CEA combined detection in the diagnosis and differential diagnosis of ovarian cancer. Objects and methods First, the object: 47 normal and healthy women, who are normal physical examination. Various types of benign and malignant tumors and gynecological inflammation were taken from patients in our hospital, the diagnosis is clinically confirmed by B ultrasound and pathology. Among them, 42 cases of ovarian cancer, 29 cases of benign ovarian lesions (ovarian cyst in 26 cases, teratoma in 3 cases), gynecological other malignant tumors in 19 cases (3 cases of fallopian tube cancer, 10 cases of cervical cancer, 2 cases of endometrial cancer, uterine body Cancer in 4 cases); colorectal cancer in 23 cases, gynecological inflammation in 18 cases, taken from the venous blood, the serum was separated and stored at -20 ℃ for later use. Second, the method: CA-125 immune radioactive kit (CIS Bio International) and CEA radioimmunoassay kit (China Institute of Atomic Energy), according to instructions, measuring instruments for the 1470 WIZA RDTM counter. The intra-assay CVs were 2.73% and 3.46% for both kits, and the inter-assay CV was 3.6% and 4.27% respectively. The CA-125 levels were expressed as ± S and ± 2S as positive cutoffs. Rate difference analysis using X ~ 2 test.