Multivariate analysis of prognostic variables in patients with metastatic testicular cancer.

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.