Published in:
01-06-2015 | Original Article – Clinical Oncology
Charlson comorbidity index: an additional prognostic parameter for preoperative glioblastoma patient stratification
Published in: Journal of Cancer Research and Clinical Oncology | Issue 6/2015
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Purpose
Dismal glioblastoma (GB) patient outcome calls for the elucidation of further reliable predictors of prognosis. Established “biomarkers,” age and functional status, employed in today’s patient stratification have limits in fingerprinting this heterogeneous tumor entity. We aimed at ascertaining additional prognostic factors that may facilitate patient stratification for surgery.
Methods
A retrospective review of 233 consecutive adult patients operated on for newly diagnosed GB at a single tertiary institution over a 5-year period (2006–2011) was conducted. Modern defined outcome associating factors recorded included demographics (preoperative age, gender, signs, symptoms, comorbidity status quantified by the Charlson comorbidity index (CCI), functional status computed by the Karnofsky performance scale (KPS)), tumor characteristics (size, location, isocitrate dehydrogenase mutation, and O-6-methylguanine-DNA methyltransferase promoter methylation status), and treatment parameters (volumetrically quantified extent of resection and adjuvant therapy). Survival analysis was performed by the Kaplan–Maier method. Influence of variables was evaluated using log-rank test.
Results
Median neuroradiographic evidence of tumor progression was 6 months after surgery (range 0–72). The median overall survival was 9.5 months (range 0–72). Age > 65 years, KPS ≤ 70, and CCI > 3 were significantly associated with both poor OS (each p < 0.0001) and PFS (p < 0.0001, p < 0.001 and p < 0.002), respectively. Also, patients older than 65 years significantly had a CCI > 3 (p < 0.0001).
Conclusions
Our data evidence that aside established prognostic parameters (age and KPS) for GB patient outcome, the CCI additionally significantly impacts outcome and may be employed for preoperative patient stratification.