Identifying Better Surgical Candidates among Recursive Partitioning Analysis Class 2 Patients who Underwent Surgery for Intracranial Metastases

Kaisorn L. Chaichana, Shami Acharya, Mariana Flores, Olindi Wijesekera, Daniele Rigamonti, Jon D. Weingart, Alessandro Olivi, Chetan Bettegowda, Gary L. Gallia, Henry Brem, Michael Lim, Alfredo Quinones-Hinojosa

Research output: Contribution to journalReview article

6 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Pages (from-to)e267-e275
JournalWorld Neurosurgery
Volume82
Issue number1-2
DOIs
StatePublished - 2014
Externally publishedYes

Fingerprint

Neoplasm Metastasis
Survival
Tertiary Healthcare
Survival Rate
Regression Analysis
Brain
Neoplasms

Keywords

  • Breast
  • Gastrointestinal
  • Lung
  • Melanoma
  • Metastatic brain tumor
  • Prognosis
  • Recurrence
  • Renal
  • RPA
  • Surgery
  • Survival

ASJC Scopus subject areas

  • Clinical Neurology
  • Surgery

Cite this

Identifying Better Surgical Candidates among Recursive Partitioning Analysis Class 2 Patients who Underwent Surgery for Intracranial Metastases. / Chaichana, Kaisorn L.; Acharya, Shami; Flores, Mariana; Wijesekera, Olindi; Rigamonti, Daniele; Weingart, Jon D.; Olivi, Alessandro; Bettegowda, Chetan; Gallia, Gary L.; Brem, Henry; Lim, Michael; Quinones-Hinojosa, Alfredo.

In: World Neurosurgery, Vol. 82, No. 1-2, 2014, p. e267-e275.

Research output: Contribution to journalReview article

Chaichana, KL, Acharya, S, Flores, M, Wijesekera, O, Rigamonti, D, Weingart, JD, Olivi, A, Bettegowda, C, Gallia, GL, Brem, H, Lim, M & Quinones-Hinojosa, A 2014, 'Identifying Better Surgical Candidates among Recursive Partitioning Analysis Class 2 Patients who Underwent Surgery for Intracranial Metastases', World Neurosurgery, vol. 82, no. 1-2, pp. e267-e275. https://doi.org/10.1016/j.wneu.2013.08.031
Chaichana, Kaisorn L. ; Acharya, Shami ; Flores, Mariana ; Wijesekera, Olindi ; Rigamonti, Daniele ; Weingart, Jon D. ; Olivi, Alessandro ; Bettegowda, Chetan ; Gallia, Gary L. ; Brem, Henry ; Lim, Michael ; Quinones-Hinojosa, Alfredo. / Identifying Better Surgical Candidates among Recursive Partitioning Analysis Class 2 Patients who Underwent Surgery for Intracranial Metastases. In: World Neurosurgery. 2014 ; Vol. 82, No. 1-2. pp. e267-e275.
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title = "Identifying Better Surgical Candidates among Recursive Partitioning Analysis Class 2 Patients who Underwent Surgery for Intracranial Metastases",
abstract = "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.",
keywords = "Breast, Gastrointestinal, Lung, Melanoma, Metastatic brain tumor, Prognosis, Recurrence, Renal, RPA, Surgery, Survival",
author = "Chaichana, {Kaisorn L.} and Shami Acharya and Mariana Flores and Olindi Wijesekera and Daniele Rigamonti and Weingart, {Jon D.} and Alessandro Olivi and Chetan Bettegowda and Gallia, {Gary L.} and Henry Brem and Michael Lim and Alfredo Quinones-Hinojosa",
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T1 - Identifying Better Surgical Candidates among Recursive Partitioning Analysis Class 2 Patients who Underwent Surgery for Intracranial Metastases

AU - Chaichana, Kaisorn L.

AU - Acharya, Shami

AU - Flores, Mariana

AU - Wijesekera, Olindi

AU - Rigamonti, Daniele

AU - Weingart, Jon D.

AU - Olivi, Alessandro

AU - Bettegowda, Chetan

AU - Gallia, Gary L.

AU - Brem, Henry

AU - Lim, Michael

AU - Quinones-Hinojosa, Alfredo

PY - 2014

Y1 - 2014

N2 - 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.

AB - 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.

KW - Breast

KW - Gastrointestinal

KW - Lung

KW - Melanoma

KW - Metastatic brain tumor

KW - Prognosis

KW - Recurrence

KW - Renal

KW - RPA

KW - Surgery

KW - Survival

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DO - 10.1016/j.wneu.2013.08.031

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