Dataset related to article "Risk-group Classification by Recursive Partitioning Analysis of Patients Affected by Oligometastatic Renal Cancer Treated with Stereotactic Radiotherapy"

This record contains raw data related to article "Risk-group Classification by Recursive Partitioning Analysis of Patients Affected by Oligometastatic Renal Cancer Treated with Stereotactic Radiotherapy"
 Abstract
Aims: Due to the absence of consensus on metastases-directed treatment in kidney cancer, we conducted an analysis of patients treated with stereotactic radiotherapy (SRT) on cranial or extracranial metastases to classify them in survival class risk according to pre-treatment characteristics.
Materials and methods: We included oligometastatic kidney cancer patients treated with SRT on up to five metastases. Concomitant systemic treatment was allowed. End points included overall survival and the binary classification tree approach with recursive partitioning analysis was applied to stratify patients into overall survival risk groups.
Results: In total, 129 patients were treated on 242 metastases. The brain was the most common site (34.71%), followed by lung (25.62%). With a median follow-up of 19.4 months, 1- and 3-year overall survival were 82.62 and 55.11%. The recursive partitioning analysis identified four prognostic classes. Class 1 included patients aged ≤ 65 years treated on extracranial metastases, with 3-year overall survival of 82.66%. Class 2 included patients aged > 65 years, without history of metastatic bone disease, treated on extracranial metastases, with a 3-year overall survival of 67.91%. Patients aged > 65 years and a history of bone disease, treated on extracranial metastases, were classified as class 3, with a 3-year overall survival of 37.50%. Class 4 included patients treated on brain metastases, with a 3-year overall survival of 9.70%.
Conclusion: We produced a stratification model that can predict survival of oligometastatic kidney cancer patients treated with metastases-directed SRT. Site of disease, patient's age and presence of bone disease can help clinicians in the decision-making process.