PURPOSE: Recursive partitioning analysis (RPA) is a prognostic index capable of predicting survival in patients with brain metastases. Histology of the primary tumour has only recently been introduced among the factors that could potentially affect the prognosis of these patients. The main purpose of this study was to analyse the impact of RPA in correlation with histology of the primary tumour in patients with brain metastases treated with hypofractionated radiotherapy. MATERIALS AND METHODS: A total of 382 patients were treated at the Department of Radiotherapy of Brescia University, and RPA classes were retrospectively assigned to all patients. Univariate and multivariate analyses were then performed to verify the role of the single prognostic variables, for the entire group and for each prognostic class, as well as in correlation with histology of the primary tumour. RESULTS: Most patients were classified as RPA prognostic class 2 (48%). The majority of patients was treated with a total dose of 30 Gy delivered in ten fractions, whereas the dose of 20 Gy in four or five fractions was primarily used in patients classified as RPA class 3. At univariate analysis, the main variable correlating with overall survival (OS) was RPA class (p=0.000). Uni- and multivariate analysis performed on RPA class 1 patients only confirmed the role of general performance status, number of metastases and total radiotherapy dose for predicting OS. In the group with the worst prognosis (RPA class 3), none of the variables had a statistically significant role in improving OS. Tumour histology and radiotherapy dose influence OS, even in RPA class 1 and 2 patients. CONCLUSIONS: This analysis confirms that RPA prognostic class is the factor that most predicts survival. Primary tumour histology helps determine prognosis, especially in RPA prognostic classes 1 and 2. As regards RPA class 3, no factor influences survival prognosis.
PURPOSE: Recursive partitioning analysis (RPA) is a prognostic index capable of predicting survival in patients with brain metastases. Histology of the primary tumour has only recently been introduced among the factors that could potentially affect the prognosis of these patients. The main purpose of this study was to analyse the impact of RPA in correlation with histology of the primary tumour in patients with brain metastases treated with hypofractionated radiotherapy. MATERIALS AND METHODS: A total of 382 patients were treated at the Department of Radiotherapy of Brescia University, and RPA classes were retrospectively assigned to all patients. Univariate and multivariate analyses were then performed to verify the role of the single prognostic variables, for the entire group and for each prognostic class, as well as in correlation with histology of the primary tumour. RESULTS: Most patients were classified as RPA prognostic class 2 (48%). The majority of patients was treated with a total dose of 30 Gy delivered in ten fractions, whereas the dose of 20 Gy in four or five fractions was primarily used in patients classified as RPA class 3. At univariate analysis, the main variable correlating with overall survival (OS) was RPA class (p=0.000). Uni- and multivariate analysis performed on RPA class 1 patients only confirmed the role of general performance status, number of metastases and total radiotherapy dose for predicting OS. In the group with the worst prognosis (RPA class 3), none of the variables had a statistically significant role in improving OS. Tumour histology and radiotherapy dose influence OS, even in RPA class 1 and 2 patients. CONCLUSIONS: This analysis confirms that RPA prognostic class is the factor that most predicts survival. Primary tumour histology helps determine prognosis, especially in RPA prognostic classes 1 and 2. As regards RPA class 3, no factor influences survival prognosis.
Authors: Paul W Sperduto; Brian Berkey; Laurie E Gaspar; Minesh Mehta; Walter Curran Journal: Int J Radiat Oncol Biol Phys Date: 2007-10-10 Impact factor: 7.038
Authors: K J Murray; C Scott; H M Greenberg; B Emami; M Seider; N L Vora; C Olson; A Whitton; B Movsas; W Curran Journal: Int J Radiat Oncol Biol Phys Date: 1997-10-01 Impact factor: 7.038
Authors: E M Noordijk; C J Vecht; H Haaxma-Reiche; G W Padberg; J H Voormolen; F H Hoekstra; J T Tans; N Lambooij; J A Metsaars; A R Wattendorff Journal: Int J Radiat Oncol Biol Phys Date: 1994-07-01 Impact factor: 7.038
Authors: Elisa Y Saito; Gustavo A Viani; Robson Ferrigno; Ricardo A Nakamura; Paulo E Novaes; Cassio A Pellizzon; Ricardo C Fogaroli; Maria A Conte; Joao V Salvajoli Journal: Radiat Oncol Date: 2006-06-29 Impact factor: 3.481
Authors: Michela Buglione; Sara Pedretti; Stefano Gipponi; Luciano Buttolo; Paolo Panciani; Pietro Luigi Poliani; Roberto Liserre; Paolo Borghetti; Ludovica Pegurri; Loredana Costa; Luca Triggiani; Nadia Pasinetti; Paolo Ghirardelli; Sara Pandini; Alessandro Padovani; Stefano Maria Magrini Journal: Radiol Med Date: 2015-04-28 Impact factor: 3.469