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

Abstract

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.

Characteristics and Outcomes of Patients With Breast Cancer With Leptomeningeal Metastasis

“…Improvement in breast cancer treatment including HER2-targeted therapy, may have improved the outcome of patients with LM over time. We hypothesize that receptor subytpe may be an important prognostic factor for LM patients, similarly to what has been reported for patients with brain metastases [5–7]. …”

Onco-metabolism: defining the prognostic significance of obesity and diabetes in women with brain metastases from breast cancer

“…On multivariate analysis, both BMI and diabetes were independent risk factors for death. As expected, triple negative breast cancer patients overall had a worse prognosis, which has been corroborated in previous data [2, 4, 18]. Further, BMI was negatively correlated with OS in all three molecular subtypes of breast cancer: triple negative ( p = 0.009), HR+ ( p = 0.013), and HER2+ ( p = 0.045).…”

“…BMBC portends a poor prognosis despite advances in radiation therapy [2, 18, 22, 23]. Obesity has been implicated as a risk factor for metastases and overall poor prognoses and its resultant metabolic dysregulation may promote radioresistance [24, 25].…”

“…Additionally, OS was determined for each tumor subtype including triple negative, HER2+, and HR+ triple negative. To determine the relative prognostic indices between the two groups, breast cancer disease-specific graded prognostic assessments (GPA) and modified breast-GPA, two validated models for predicting survival in patients with BMBC were calculated as previously described [18, 19]. …”

Mystery of the brain metastatic disease in breast cancer patients: improved patient stratification, disease prediction and targeted prevention on the horizon?

“…Multi-parametric models assessing BM risks are currently under consideration [12]. Further, the multi-parametric prognostic tools for the optimised BM treatment algorithms, disease and therapy monitoring are under development [69][70][71]. The above proposed measures may substantially increase the quality of life of the predisposed individuals and affected patients by increasing the efficacy and reducing the overall costs of the healthcare in the area.…”