Ruf C G, Sachs S, Khalili-Harbi N, Isbarn H, Wagner W, Matthies C, Meineke V, Fisch M, Chun F K, Abend M
Department of Urology, Federal Armed Forces Hospital, 22049, Hamburg, Germany,
World J Urol. 2014 Oct;32(5):1205-11. doi: 10.1007/s00345-013-1194-0. Epub 2013 Oct 29.
To examine the significance of 90 biomarkers for predicting metastatic status in non-seminomatous germ cell tumors (NSGCT). By predicting metastatic status, it may be possible to eliminate unnecessary therapeutic or diagnostic efforts.
We investigated 552 males who were diagnosed with non-metastatic (n = 273) and metastatic (n = 279) NSGCT between 2000 and 2011. The sample included cancers of different histologies: embryonal cell carcinoma (n = 131), teratoma (n = 55), and mixed histology (n = 366). We collected and analyzed more than 90 parameters via logistic regression: demographic characteristics, medical history, histopathological parameters, and levels of tumor markers and hormones.
Testis histology (p = 0.004), clinical symptoms (p = 0.0005), tumor length (p = 0.005), infiltration of the rete testis (p = 0.008), invasion of lymphatic (pL1) and blood vessels (pV1) (p < 0.0001), and levels of enzymes such as LDH, βHCG, AFP, and FSH (p values as small as <0.0001) were associated with metastatic status. With one model, we identified 14 out of 76 (18.4 %) metastatic NSGCT cases with 93-100 % certainty (positive predictive value) at 99 % specificity by the peripheral blood levels of LDH (day of operation) in combination with FSH measurements (1 day after operation). A second model included pV, tumor length, and FSH (1 day after operation). It identified 25 out of 90 (27.8 %) non-metastatic NSGCT with approximately 90 % certainty (negative predictive value) at 94-98 % sensitivity.
No single parameter was able to discriminate metastatic from non-metastatic NSGCT, but combinations of parameters in two predictive models accurately identified the metastatic status in 23 % of the cases in our sample.
研究90种生物标志物对预测非精原性生殖细胞肿瘤（NSGCT）转移状态的意义。通过预测转移状态，有可能避免不必要的治疗或诊断措施。
我们调查了2000年至2011年间被诊断为非转移性（n = 273）和转移性（n = 279）NSGCT的552名男性。样本包括不同组织学类型的癌症：胚胎性癌（n = 131）、畸胎瘤（n = 55）和混合组织学类型（n = 366）。我们通过逻辑回归收集并分析了90多个参数：人口统计学特征、病史、组织病理学参数以及肿瘤标志物和激素水平。
睾丸组织学（p = 0.004）、临床症状（p = 0.0005）、肿瘤长度（p = 0.005）、睾丸网浸润（p = 0.008）、淋巴管（pL1）和血管浸润（pV1）（p < 0.0001）以及乳酸脱氢酶（LDH）、β人绒毛膜促性腺激素（βHCG）、甲胎蛋白（AFP）和促卵泡激素（FSH）等酶的水平（p值小至<0.0001）与转移状态相关。在一个模型中，通过手术当天外周血LDH水平与术后1天FSH测量值相结合，我们以99%的特异性、93% - 100%的确定性（阳性预测值）识别出76例转移性NSGCT病例中的14例（18.4%）。第二个模型包括pV、肿瘤长度和术后1天的FSH。它以94% - 98%的敏感性、约90%的确定性（阴性预测值）识别出90例非转移性NSGCT病例中的25例（27.8%）。
没有单一参数能够区分转移性和非转移性NSGCT，但两个预测模型中的参数组合在我们样本中23%的病例中准确识别出了转移状态。
