Adult intradural intramedullary astrocytomas: a multicenter analysis

Abstract

Background: Intramedullary tumors constitute approximately 20-30% of all spinal cord tumors and approximately 30-40% of these are astrocytomas. Furthermore, they comprise only about 2-4% of all primary central nervous system (CNS) tumors. Due to their rarity and poor prognosis, large population-based studies are needed to assess the epidemiology and survival risk factors associated with these tumors in the hope of improving outcomes. The authors undertook this retrospective study to explore factors that may influence survival in adult patients with intramedullary astrocytomas.

Methods: Utilizing the Surveillance, Epidemiology, and End Results (SEER) database, a prospective cancer registry, the authors retrospectively assessed survival in histologically confirmed, intramedullary spinal cord astrocytomas in patients 18 years of age and older. Survival was described with Kaplan-Meier curves and multivariate regression analysis was used to assess the association of several variables with survival while controlling for confounding variables.

Results: Analysis by multivariate regression of 131 cases showed that increasing age of diagnosis [hazard ratio (HR) 1.52, 95% CI: 1.17-1.99, P=0.001], WHO grade IV classification (HR 8.85, 95% CI: 2.83-27.69, P<0.001), tumor invasiveness (HR 2.94, 95% CI: 1.00-8.64, P=0.047), and sub-total resection (HR 5.80, 95% CI: 1.20-28.03, P=0.029) were associated with statistically significant decreases in survival.

Conclusions: This study suggest that older age, higher WHO grade, tumor invasiveness as well as sub-total resection were all associated with a worse prognosis.

Keywords: Adult; astrocytoma; intradural; intramedullary; oncology; spinal.

Figure 1

Flowchart for study cohort selection.

Figure 2

Patient, tumor, and treatment characteristics impact on survival. (A) Kaplan-Meier survival analysis of age (18–34, 35–49, 50–64, 65–79, 80+) demonstrating survival probability against time (in months). Number at risk table for age can also be seen below the plot; (B) Kaplan-Meier survival analysis of tumor grade (WHO classification) demonstrating survival probability against time (in months). Number at risk table for tumor grade can also be seen below the plot; (C) Kaplan-Meier survival analysis of chemotherapy demonstrating survival probability against time (in months). Number at risk table for chemotherapy can also be seen below the plot; (D) Kaplan-Meier survival analysis of race demonstrating survival probability against time (in months). Number at risk table for race can also be seen below the plot; (E) Kaplan-Meier survival analysis of tumor extension demonstrating survival probability against time (in months). Number at risk table for tumor extension can also be seen below the plot; (F) Kaplan-Meier survival analysis of tumor size (in millimeters) demonstrating survival probability against time (in months). Number at risk table for tumor size can also be seen below the plot.

Figure 3

Kaplan-Meier survival analysis of surgical intervention demonstrating survival probability against time (in months). Number at risk table for surgical intervention can also be seen below the plot.

Figure 4

The role of radiation on patient survival. (A) Kaplan-Meier survival analysis of radiation treatment demonstrating survival probability against time (in months). Number at risk table for radiation treatment can also be seen below the plot; (B) Kaplan-Meier survival analysis of radiation sequence demonstrating survival probability against time (in months). Number at risk table for radiation sequence can also be seen below the plot.