Volume 69, Issue 3, Supplement , Page S185, 1 November 2007
Low Grade Gliomas: Demographic, Tumor and Treatment Factors Associated With Survival
Article Outline
Purpose/Objective(s)
For patients with low grade glioma (LGG), identifying risk factors that predict outcome has been controversial. We sought to investigate the prognostic significance of various tumor, patient, and treatment factors for survival.
Materials/Methods
Using data from the Surveillance, Epidemiology, and End Results (SEER) Program, we identified 1611 patients with pathologically confirmed LGG diagnosed between 1993 and 2003. Categorical variables investigated including age (<40 vs. ≥40 yrs.), tumor size (<6 cm vs. ≥6 cm), presence of tumor crossing midline (yes vs. no), histology (astrocytoma vs. either oligodendroglioma or mixed glioma), radiotherapy use at diagnosis (yes vs. no), and extent of resection (gross total resection vs. less than total resection). As a measure of quality of healthcare delivery, we obtained information from the 2000 census on income including the median 1999 household income and divided into quartiles.
Results
In multivariate analysis, patient related variables associated with worse survival included age over 40 years (hazard ratio [HR] = 2.1; 95% confidence interval [CI] 1.7–2.5), the presence of bilateral disease (HR = 1.5; CI 1.2–2.0), and astrocytoma histology (HR = 2.0; CI 1.7–2.5). Furthermore, treatment related variables associated with worse survival included the use of radiotherapy (HR = 1.6; CI 1.3–2.1) and failure to achieve gross total resection (HR = 1.6; CI 1.3–1.9). Patients who were in the top quartile for median household income had improved survival (HR = 0.6; CI 0.5–0.8).
Conclusions
For patients who have a LGG, the relationship between prognostic factors and survival is complex. While the use of radiotherapy is controversial, the increase in the mortality hazard associated with radiotherapy likely represents some selection bias we were unable to account for. However, the inequality in radiotherapy use associated with median income likely represents a disparity in health care delivery.
Author Disclosure: B.E. Lally, None; E.G. Shaw, None; J.P.S. Knisely, None; A.W. Blackstock, None; M.C. Robbins, None; A.M. Geiger, None.
PII: S0360-3016(07)01517-9
doi:10.1016/j.ijrobp.2007.07.335
© 2007 Elsevier Inc. All rights reserved.
Volume 69, Issue 3, Supplement , Page S185, 1 November 2007
