Validation of recursive partitioning analysis classification in patients with brain metastases from non-small cell lung cancer treated with short-course accelerated radiotherapy

Abstract

Aims: To study various prognostic factors affecting outcome and to validate Radiation Therapy Oncology Group recursive partitioning analysis (RPA) class in non-small cell lung cancer (NSCLC) with brain metastases treated with short-course accelerated radiotherapy (SCAR).

Materials and methods: The case records of 100 patients with NSCLC consecutively treated at Tata Memorial Hospital from August 2006 to August 2009 were studied for various patient, tumour and treatment-related prognostic factors. Patients received whole-brain radiotherapy to a dose of 20 Gy/five fractions over 1 week (n=90) or 30 Gy/10 fractions over 2 weeks (n=10). The Kaplan-Meier estimate was used for survival analysis in SPSS v15.

Results: The median overall survival was 4.0 months (range 0.5-30.0 months). The 6-, 12-, 18- and 24-month survival rates were 35.8, 18.0, 9.3 and 6.2%, respectively. Of the various prognostic factors, RPA class (II versus III, P value=0.023), Karnofsky performance score (<70 versus ≥70, P value=0.039) and the use of systemic therapy (yes versus no, P value=0.00) emerged as significant on univariate analysis. RPA classification effectively separated the patient population into prognostically distinct subgroups. The median overall survival for RPA class II and RPA class III was 6 and 4 months, respectively. The use of systemic therapy prolonged overall survival by 6 months (3 months versus 9 months).

Conclusion: The SCAR regimen is an effective and resource-sparing palliative strategy for brain metastases in NSCLC. The results validate the usefulness of RPA classification in this specific subset of patients treated with SCAR.