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1000
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Abstract/Summary
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Background!#!Current guidelines for the treatment of anaplastic astrocytoma (AA) recommend maximal safe resection followed by radiotherapy and chemotherapy. Despite this multimodal treatment approach, patients have a limited life expectancy. In the present study, we identified variables associated with overall survival (OS) and constructed a model score to predict the OS of patients with AA at the time of their primary diagnosis.!##!Methods!#!We retrospectively evaluated 108 patients with newly diagnosed AA. The patient and tumor characteristics were analyzed for their impact on OS. Variables significantly associated with OS on multivariable analysis were included in our score. The final algorithm was based on the 36-month survival rates corresponding to each characteristic.!##!Results!#!On univariate analysis, age, Karnofsky performance status, isocitrate dehydrogenase status, and extent of resection were significantly associated with OS. On multivariable analysis all four variables remained significant and were consequently incorporated in the score. The total score ranges from 20 to 33 points. We designated three prognostic groups: A (20-25), B (26-29), and C (30-33 points) with 36-month OS rates of 23%, 71%, and 100%, respectively. The OS rate at 5 years was 8% in group A, 61% in group B and 88% in group C.!##!Conclusions!#!Our model score predicts the OS of patients newly diagnosed with AA and distinguishes patients with a poor survival prognosis from those with a greater life expectancy. Independent and prospective validation is needed. The upcoming changes of the WHO classification of brain tumors as well as the practice changing results from the CATNON trial will most likely require adaption of the score.
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1000
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Hinweis
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DeepGreen-ID: 95f05e0aa40d43ef8921c26c322241eb ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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