Identification of prognostic subgroups among patients with metastatic ‘IGCCCG poor-prognosis’ germ-cell cancer: An explorative analysis using cart modeling

Abstract

The IGCCCG classification has identified three prognostic groups of patients with metastatic germ-cell tumors. 'Poor prognosis' is based on primary tumor localization, the presence of visceral metastases, and/or high tumor-marker levels. The overall survival rate of these patients is about 45%-55%. The present analysis attempts to identify subsets of patients with a more or less favorable outcome among the 'poor-prognosis' group. We retrospectively explored prognostic subgroups in 332 patients with 'IGCCCG' poor-risk GCT using the classification-and-regression-tree model (CART). The following variables were included: primary tumor localization, presence of visceral or lung metastases, presence of an abdominal tumor, number of metastatic sites, serum levels of beta-HCG, AFP and LDH. All patients had been treated with cisplatin-etoposide-based chemotherapy within controlled clinical trials between 1984 and 1997. gonadal/retroperitoneal (G/R) primary tumor 260 patients (78%), mediastinal primary tumor 72 patients (22%), visceral metastases 205 patients (62%) including 33 patients with CNS metastases, lung metastases 247 patients (74%), abdominal tumor 241 patients (72%), elevated AFP, beta-HCG or LDH levels 235 (71%), 253 (76%) and 275 (83%) of patients, respectively. Patients with primary mediastinal disease plus lung metastases exhibited the worst two-year PFS (28%), whereas patients with a primary G/R tumor and without visceral metastases showed the highest chance of two-year PFS (75%). The latter group of patients without visceral metastases and with a primary G/R tumor also had the most favourable two-year OS (84%). In contrast, patients with a primary mediastinal tumor and visceral metastases displayed the worst two-year OS (49%). Different prognostic subsets of patients can be identified among the group of 'poor-prognosis' GCT patients. The CART analysis model results in a hierarchy of prognostic factors which may allow to more precisely estimate the individual patient's prognosis. Identifying subgroups of 'very poor-prognosis' among 'poor-prognosis' patients may allow to test for new treatment strategies in selected subgroups.