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. 2015 Jan;56(1):151-8.
doi: 10.1093/jrr/rru092. Epub 2014 Oct 25.

Treatment outcomes using CyberKnife for brain metastases from lung cancer

Affiliations

Treatment outcomes using CyberKnife for brain metastases from lung cancer

Keisuke Tamari et al. J Radiat Res. 2015 Jan.

Abstract

We investigated the clinical outcomes following treatment using stereotactic radiosurgery (SRS) and fractionated stereotactic radiotherapy (SRT) for brain metastases from lung cancer. A total of 67 patients with 109 brain metastases from lung cancer treated using CyberKnife between 1998 and 2011 were retrospectively analyzed. SRS (median dose, 24 Gy) was used to treat 79 lesions, and 3-fraction SRT (median dose, 30 Gy) was used to treat 30 lesions. The median follow-up time was 9.4 months (range, 0.4-125 months). The 1-year local control rate was 83.3%, and the 1-year distant brain failure rate was 30.1%. The median survival time was 13.1 months, and the 1- and 3-year overall survival (OS) rates were 54.8% and 25.9%, respectively. On multivariate analysis, three factors were found to be statistically significant predictors of OS: (i) presence of uncontrolled primary disease [hazard ratio (HR) = 3.04; P = 0.002]; (ii) Brinkman index (BI) ≥ 1000 (HR = 2.75; P = 0.007); and (iii) pulmonary metastases (HR = 3.54; P = 0.009). Radionecrosis and worsening of neurocognitive function after radiosurgery were observed in 5 (7%) and 3 (4%) patients, respectively. Our results indicated that SRS/SRT for brain metastases from lung cancer was effective. Uncontrolled primary disease, high BI, and pulmonary metastases at treatment were significant risk factors for OS.

Keywords: CyberKnife; brain metastases; lung cancer; stereotactic radiosurgery.

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Figures

Fig. 1.
Fig. 1.
Local control and distant brain failure.
Fig. 2.
Fig. 2.
Overall survival. (a) Overall survival and Kaplan–Meier survival curves for prognostic factors. (b) Survival curves by primary disease control. (c) Survival curves by pulmonary metastases. (d) Survival curves by Brinkman index.

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