Nekulová M, Simícková M, Pecen L, Eben K, Vermousek I, Stratil P, Cernoch M, Lang B
Masaryk Memorial Cancer Institute, Brno, Czech Republic.
Neoplasma. 1994;41(2):113-8.
A mathematical model of prediction of progression was tested in patients with breast cancer employing long-term monitoring of tumor markers CEA, CA 15-3, MCA and TPA, erythrocyte sedimentation rate (FW), and the enzymes gamma-glutamyl transferase (GGT), alkaline phosphatase (ALP) and lactate dehydrogenase (LD) in serum. At the same time, specificity, sensitivity, lead time and positive predictive value were evaluated along with false positivity for all these parameters and their combinations. A model was proposed for the follow-up of patients with breast cancer after the completion of basic therapy.
在乳腺癌患者中测试了一种疾病进展预测的数学模型,该模型采用对肿瘤标志物癌胚抗原(CEA)、糖类抗原15-3(CA 15-3)、巨细胞抗体(MCA)和组织多肽抗原(TPA)、红细胞沉降率(FW)以及血清中的γ-谷氨酰转移酶(GGT)、碱性磷酸酶(ALP)和乳酸脱氢酶(LD)进行长期监测。同时,评估了所有这些参数及其组合的特异性、敏感性、提前期和阳性预测值以及假阳性率。提出了一种在乳腺癌患者完成基础治疗后的随访模型。