Biologic parameters that correlate with the prognosis of human gliomas

Much clinical and biologic data have been processed in the search for useful objective parameters to predict brain tumor behavior. Seventy cases of astrocytic glioma collected by a single clinical team were studied using a full complement of clinical procedures: follow up (7 years), histologic analysis, DNA content estimation, and cell kinetics by flow cytometry. Proliferating cell nuclear antigen (PCNA) was determined by immunocytochemical-coupling flow cytometry (PFC) and also by counting under light microscopy (PIHC). A statistical evaluation was carried out to establish the usefulness of several parameters for glioma prognosis. The cases were histologically classified as 14 low-grade astrocytomas, 20 anaplastic astrocytomas, and 36 glioblastomas multiforme. The survival curve showed significant differences between histologic groups. Diploid populations were more frequent in low-grade astrocytomas, and aneuploid tumors often had increased S-phase and proliferative fractions. The PCNA-labeled index (PCNA-LI) increased with malignancy and correlated with histologic grading (P = 0.01). The PCNA-LI and age segregated low- from high-grade astrocytomas (including anaplastic astrocytoma and glioblastoma multiforme), but none of the variables considered differentiated anaplastic astrocytoma from glioblastoma multiforme. The Cox regression test displayed significant values for age, histologic diagnosis, and PCNA determinations when considered in tandem. Discriminant analysis obtained a function integrating age and specifically PIHC-LI to help in the prognosis of doubtful cases. The results emphasize the importance of parameters integrating different variables in an attempt to provide an accurate prognosis, the most significant being age, histopathologic diagnosis, and the proliferative fraction determined by PCNA.