Multivariate analysis of prognostic variables in patients with metastatic testicular cancer.
Multivariate analysis of prognostic variables in patients with metastatic testicular cancer.
复制标题
DOI：
--
复制
发表时间：
1983-07
期刊：
影响因子：
11.2
通讯作者：
G. Bosl;N. Geller;C. Cirrincione;N. Vogelzang;B. Kennedy;W. Whitmore;D. Vugrin;H. Scher;J. Nisselbaum;Robert B. Golbery
中科院分区：
文献类型：
--
作者：
G. Bosl;N. Geller;C. Cirrincione;N. Vogelzang;B. Kennedy;W. Whitmore;D. Vugrin;H. Scher;J. Nisselbaum;Robert B. Golbery
由于目前的治疗方案，大多数转移性睾丸癌患者实现了完全缓解。然而，未能实现完全缓解的患者预后非常差，几乎所有人都死于自己的疾病。采用1975年9月至1981年2月间在纪念医院接受治疗的171例转移性睾丸癌患者的资料，对与预后相关的几个临床变量进行多因素Logistic回归分析。确定了一个数学模型，该模型正确地预测了94%的完全缓解和83%的所有结果。有统计学意义的变量是血清乳酸脱氢酶(p<0.001)和绒毛膜促性腺激素(p<0.001)的对数和转移部位总数(p<0.001)。该模型在明尼苏达大学医院治疗的49名转移性睾丸癌患者中进行了测试，它正确地预测了86%的完全缓解和84%的结果。在睾丸癌等高度可治愈的疾病中，数学建模可能使临床研究人员能够预测到那些最不可能表现良好的患者。对于这样的患者，替代治疗策略将是合适的。
A majority of patients with metastatic testicular cancer achieve a complete remission as a result of current treatment programs. However, patients who fail to achieve a complete remission have a very poor prognosis, and nearly all die of their disease. A multivariate logistic regression analysis of several clinical variables associated with prognosis was performed using data from 171 patients treated for metastatic testicular cancer at Memorial Hospital between September 1975 and February 1981. A mathematical model was identified which correctly predicted 94% of complete remissions and 83% of all outcomes. The variables achieving statistical significance were the logarithm of the serum values of lactate dehydrogenase (p less than 0.001) and human chorionic gonadotropin (p less than 0.001) and the total number of sites of metastasis (p less than 0.001). The model was tested against 49 patients with metastatic testicular cancer treated at the University of Minnesota Hospitals, and it correctly predicted 86% of complete remissions and 84% of all outcomes. In a highly curable disease such as testicular cancer, mathematical modeling may enable the clinical investigator to anticipate those patients who are least likely to do well. Alternate treatment strategies would be appropriate for such patients.