OBJECTIVE: The management of patients with brain metastases is typically dependent on their prognosis. Recursive partitioning analysis (RPA) is the most commonly used method for prognosticating survival, but has limitations for patients in the intermediate class. The aims of this study were to ascertain preoperative risk factors associated with survival, develop a preoperative prognostic grading system, and evaluate the utility of this system in predicting survival for RPA class 2 patients. METHODS: Adult patient who underwent intracranial metastatic tumor surgery at an academic tertiary care institution from 1997 to 2011 were retrospectively reviewed. Multivariate proportional hazards regression analysis was used to identify preoperative factors associated with survival. The identified associations were then used to develop a grading system. Survival as a function of time was plotted using the Kaplan-Meier method, and survival rates were compared using log-rank analyses. RESULTS: A total of 421 (59%) of 708 patients were RPA class 2. The preoperative factors found to be associated with poorer survival were: male gender (P < 0.0001), motor deficit (P = 0.0007), cognitive deficit (P = 0.0004), nonsolitary metastases (P = 0.002), and tumor size >2 cm (P = 0.003). Patients having 0-1, 2, and 3-5 of these variables were assigned a preoperative grade of A, B, and C, respectively. Patients with a preoperative grade of A, B, and C had a median survival of 17.0, 10.3, and 7.3 months, respectively. These grades had distinct survival times (P < 0.05). CONCLUSIONS: The present study devised a preoperative grading system that may provide prognostic information for RPA class 2 patients, which may also guide medical and surgical therapies before any intervention is pursued.
OBJECTIVE: The management of patients with brain metastases is typically dependent on their prognosis. Recursive partitioning analysis (RPA) is the most commonly used method for prognosticating survival, but has limitations for patients in the intermediate class. The aims of this study were to ascertain preoperative risk factors associated with survival, develop a preoperative prognostic grading system, and evaluate the utility of this system in predicting survival for RPA class 2 patients. METHODS: Adult patient who underwent intracranial metastatic tumor surgery at an academic tertiary care institution from 1997 to 2011 were retrospectively reviewed. Multivariate proportional hazards regression analysis was used to identify preoperative factors associated with survival. The identified associations were then used to develop a grading system. Survival as a function of time was plotted using the Kaplan-Meier method, and survival rates were compared using log-rank analyses. RESULTS: A total of 421 (59%) of 708 patients were RPA class 2. The preoperative factors found to be associated with poorer survival were: male gender (P < 0.0001), motor deficit (P = 0.0007), cognitive deficit (P = 0.0004), nonsolitary metastases (P = 0.002), and tumor size >2 cm (P = 0.003). Patients having 0-1, 2, and 3-5 of these variables were assigned a preoperative grade of A, B, and C, respectively. Patients with a preoperative grade of A, B, and C had a median survival of 17.0, 10.3, and 7.3 months, respectively. These grades had distinct survival times (P < 0.05). CONCLUSIONS: The present study devised a preoperative grading system that may provide prognostic information for RPA class 2 patients, which may also guide medical and surgical therapies before any intervention is pursued.
Authors: William F Regine; Anna Rogozinska; Richard J Kryscio; Phillip A Tibbs; A Byron Young; Roy A Patchell Journal: Am J Clin Oncol Date: 2004-10 Impact factor: 2.339
Authors: M G Ewend; J A Williams; K Tabassi; B M Tyler; K M Babel; R C Anderson; M L Pinn; D J Brat; H Brem Journal: Cancer Res Date: 1996-11-15 Impact factor: 12.701
Authors: Henry Ruiz-Garcia; Lina Marenco-Hillembrand; Jennifer L Peterson; Katherine Tzou; Timothy D Malouff; Kaisorn L Chaichana; Daniel M Trifiletti; Laura Vallow Journal: Transl Cancer Res Date: 2020-01 Impact factor: 1.241