Literature DB >> 20644085

Scale to predict survival after surgery for recurrent glioblastoma multiforme.

John K Park1, Tiffany Hodges, Leopold Arko, Michael Shen, Donna Dello Iacono, Adrian McNabb, Nancy Olsen Bailey, Teri Nguyen Kreisl, Fabio M Iwamoto, Joohee Sul, Sungyoung Auh, Grace E Park, Howard A Fine, Peter McL Black.   

Abstract

PURPOSE: Despite initial treatment with surgical resection, radiotherapy, and chemotherapy, glioblastoma multiforme (GBM) virtually always recurs. Surgery is sometimes recommended to treat recurrence. In this study, we sought to devise a preoperative scale that predicts survival after surgery for recurrent glioblastoma multiforme. PATIENTS AND METHODS: The preoperative clinical and radiographic data of 34 patients who underwent re-operation of recurrent GBM tumors were analyzed using Kaplan-Meier survival analysis and Cox proportional hazards regression modeling. The factors associated with decreased postoperative survival (P < .05) were used to devise a prognostic scale which was validated with a separate cohort of 109 patients.
RESULTS: The factors associated with poor postoperative survival were: tumor involvement of prespecified eloquent/critical brain regions (P = .021), Karnofsky performance status (KPS) < or = 80 (P = .030), and tumor volume > or = 50 cm(3) (P = .048). An additive scale (range, 0 to 3 points) comprised of these three variables distinguishes patients with good (0 points), intermediate (1 to 2 points), and poor (3 points) postoperative survival (median survival, 10.8, 4.5, and 1.0 months, respectively; P < .001). The scale identified three statistically distinct groups within the validation cohort as well (median survival, 9.2, 6.3, and 1.9 months, respectively; P < .001).
CONCLUSION: We devised and validated a preoperative scale that identifies patients likely to have poor, intermediate, and good relative outcomes after surgical resection of a recurrent GBM tumor. Application of this simple scale may be useful in counseling patients regarding their treatment options and in designing clinical trials.

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Year:  2010        PMID: 20644085      PMCID: PMC2940401          DOI: 10.1200/JCO.2010.30.0582

Source DB:  PubMed          Journal:  J Clin Oncol        ISSN: 0732-183X            Impact factor:   44.544


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