scholarly journals Does Graded Prognostic Assessment outperform Recursive Partitioning Analysis in patients with moderate prognosis brain metastases?

CNS Oncology ◽  
2016 ◽  
Vol 5 (2) ◽  
pp. 69-76 ◽  
Author(s):  
Neil C Estabrook ◽  
Stephen T Lutz ◽  
Cynthia S Johnson ◽  
Simon S Lo ◽  
Mark A Henderson
Keyword(s):  
Brain Metastases ◽  
Recursive Partitioning ◽  
Recursive Partitioning Analysis ◽  
Prognostic Assessment ◽  
Graded Prognostic Assessment

scholarly journals MANFAAT SKORING PROGNOSTIK DALAM PENENTUAN TATA LAKSANA KASUS METASTASIS OTAK

2019 ◽  
Vol 36 (2) ◽  
Author(s):  
Yunni Diansari
Keyword(s):  
Radiation Therapy ◽  
Brain Metastases ◽  
Recursive Partitioning ◽  
Recursive Partitioning Analysis ◽  
Prognostic Scores ◽  
Prognostic Assessment ◽  
Whole Brain Radiation ◽  
Graded Prognostic Assessment ◽  
Brain Radiation ◽  
Score Index

 CLINICAL UTILITY OF PROGNOSTIC SCORES TO GUIDE THE MANAGEMENT OF BRAIN METASTASESABSTRACTMetastatic brain tumors are the most common intracranial neoplasms in adults and associated with significant morbidity and mortality. The current therapeutic options include surgery, whole brain radiation therapy (WBRT), stereotactic radiation (SRS), systemic therapy and symptom management only. The goals of brain metastasis management are giving longer survival, if possible the improvement in neurologic deficit and a better quality of life. Prognostic scores, a useful tool for BM patients, as an estimation of a patient’s prognosis can guide the tailored treatment for these patients. A more aggressive approaches is recommended in patients with good performance state with and controlled systemic disease. While palliative management is focused to patients on terminal state or with other comorbid disease. A number of prognostic scoring systems for BM patients have been proposed are Recursive Partitioning Analysis (RPA), the Score Index for Radiosurgery (SIR), the Basic Score for Brain Metastases (BSBM) and the Graded Prognostic Assessment (GPA). Recursive Partitioning Analysis and GPA are able to be implemented in brain metastatic patient in Indonesia.Keyword: Brain metastatic, prognostic scores, survival rateABSTRAKTumor otak metastasis merupakan tumor intrakranial yang paling sering dijumpai dan menyebabkan morbiditas serta mortalitas yang bermakna. Pilihan tata laksana terdiri dari tindakan bedah, whole brain radiation therapy (WBRT), sterotactic radiosurgery (SRS), terapi sistemik atau tata laksana simtomatik saja. Tujuan tata laksana pada pasien dengan metastasis otak adalah memperpanjang survival jika memungkinkan dengan mengontrol defisit neurologis dan memberikan kualitas hidup yang baik. Skoring prognostik merupakan metode yang bermanfaat pada kasus metastasis otak, karena dengan dapat memperkirakan prognosis pasien maka dapat menentukan pilihan tata laksana yang tepat. Tata laksana agresif direkomendasikan pada penderita dengan status performance yang baik dan penyakit sistemik yang terkontrol. Adapun tata laksana paliatif ditujukan pada pasien dengan kondisi terminal atau ada komorbid lain yang menyertai. Beberapa skoring prognostik telah diajukan seperti, Recursive Partitioning Analysis (RPA), Score Index for Radiosurgery (SIR), Basic Score for Brain Metastases (BSBM), dan Graded Prognostic Assessment (GPA). Recursive Partitioning Analysis dan GPA merupakan pilihan yang dapat diterapkan pada populasi pasien metastasis otak di Indonesia.Kata kunci:  Metastasis otak, skoring prognostik, survival rate 

scholarly journals Validation and Development of a Modified Breast Graded Prognostic Assessment As a Tool for Survival in Patients With Breast Cancer and Brain Metastases

2015 ◽  
Vol 33 (20) ◽  
pp. 2239-2245 ◽  
Author(s):  
Ishwaria M. Subbiah ◽  
Xiudong Lei ◽  
Jeffrey S. Weinberg ◽  
Erik P. Sulman ◽  
Mariana Chavez-MacGregor ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Brain Metastases ◽  
Recursive Partitioning ◽  
Prognostic Significance ◽  
Multivariable Analysis ◽  
Recursive Partitioning Analysis ◽  
Clinical Variable ◽  
Karnofsky Performance Score ◽  
Prognostic Assessment ◽  
Graded Prognostic Assessment

Purpose Several indices have been developed to predict overall survival (OS) in patients with breast cancer with brain metastases, including the breast graded prognostic assessment (breast-GPA), comprising age, tumor subtype, and Karnofsky performance score. However, number of brain metastases—a highly relevant clinical variable—is less often incorporated into the final model. We sought to validate the existing breast-GPA in an independent larger cohort and refine it integrating number of brain metastases. Patients and Methods Data were retrospectively gathered from a prospectively maintained institutional database. Patients with newly diagnosed brain metastases from 1996 to 2013 were identified. After validating the breast-GPA, multivariable Cox regression and recursive partitioning analysis led to the development of the modified breast-GPA. The performances of the breast-GPA and modified breast-GPA were compared using the concordance index. Results In our cohort of 1,552 patients, the breast-GPA was validated as a prognostic tool for OS (P < .001). In multivariable analysis of the breast-GPA and number of brain metastases (> three v ≤ three), both were independent predictors of OS. We therefore developed the modified breast-GPA integrating a fourth clinical parameter. Recursive partitioning analysis reinforced the prognostic significance of these four factors. Concordance indices were 0.78 (95% CI, 0.77 to 0.80) and 0.84 (95% CI, 0.83 to 0.85) for the breast-GPA and modified breast-GPA, respectively (P < .001). Conclusion The modified breast-GPA incorporates four simple clinical parameters of high prognostic significance. This index has an immediate role in the clinic as a formative part of the clinician's discussion of prognosis and direction of care and as a potential patient selection tool for clinical trials.

scholarly journals Validation of recursive partitioning analysis, graded prognostic assessment and basic score for brain metastases as prognostic indices among patients with brain metastases treated with radiotherapy in Indonesia

2019 ◽  
Vol 19 (2) ◽  
pp. 145-149
Author(s):  
Soehartati A. Gondhowiardjo ◽  
Renindra A. Aman ◽  
Arry Setyawan ◽  
Handoko ◽  
Irwan Ramli
Keyword(s):  
Brain Metastases ◽  
Recursive Partitioning ◽  
Whole Brain Radiotherapy ◽  
Scoring Systems ◽  
Recursive Partitioning Analysis ◽  
Prognostic Assessment ◽  
Graded Prognostic Assessment ◽  
Class 1 ◽  
Study Population ◽  
Scoring Tools

AbstractIntroduction:Metastatic brain disease is still a major contributor to cancer treatment failure. Various treatments have improved in the recent decades, which allow for better control of brain metastatic lesions. Various prognostic scoring tools have been developed and used worldwide to stratify patients with brain metastases to determine who will benefit most from aggressive treatment. The three most commonly used prognostic scoring tools are recursive partitioning analysis (RPA), basic score for brain metastases (BSBM) and graded prognostic assessment (GPA). The aim of this study is to validate these scoring tools using an Indonesian cancer patient population.Method:A retrospective analysis of all patients presenting with brain metastases from January 2012 until December 2014, through using hospital medical records, was conducted. All patients receiving whole brain radiotherapy during this period were included in this study. A follow-up with a telephone call was carried out to determine the patient’s health and survival status. Uncontactable patients were excluded from the analysis. Survival analysis was carried out by stratifying patients based on the three prognostic scoring systems.Result:A total of 80 patients were eligible to be included in the study, with 18 excluded due to being uncontactable. The remaining 62 patients’ data were analysed and stratified with all three scoring systems. The RPA was found to confer better stratification than BSBM and GPA in our study population.Conclusion:GPA was non-prognostic in our study population and BSBM was less prognostic, especially in the middle group, class 1 and class 2. Those BSBM class 1 and class 2 did not provide good prognostic stratification in our study population, whereas RPA was proven to be the best in stratifying patients’ prognosis with brain metastases in our study population.

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