ABSTRACT
Validation and comparison of Breast Graded Prognostic Assessment scores in patients with breast cancer and brain metastases (AU)
Subject(s)
Humans , Female , Middle Aged , Breast Neoplasms/mortality , Breast Neoplasms/pathology , Brain Neoplasms/mortality , Brain Neoplasms/secondary , Neoplasm Staging , Prognosis , Quality of Life , Kaplan-Meier Estimate , Confidence IntervalsABSTRACT
PURPOSE: Brain metastases (BM) occur in 15-35% of patients with metastatic breast cancer, conferring poor prognosis and impairing quality of life. Clinical scores have been developed to classify patients according to their prognosis. We aimed to check the utility of the Breast Graded Prognostic Assessment (B-GPA) and its modified version (mB-GPA) and compare them in routine clinical practice. METHODS: This is an ambispective study including all patients with breast cancer BM treated in a single cancer comprehensive center. We analyzed the overall survival (OS) from BM diagnosis until death. The Kaplan-Meier method and Cox proportional hazard regression model were used in the analyses. ROC curves were performed to compare both scores. RESULTS: We included 169 patients; median age was 50 years. HER2-positive and triple negative patients were 33.7% and 20.7%, respectively. At the last follow-up, 90% of the patients had died. Median OS was 12 months (95% confidence interval 8.0-16.0 months). OS was worse in patients with > 3 BM and in patients with triple negative subtype. CONCLUSIONS: In our series, we confirm that B-GPA and mB-GPA scores correlated with prognosis. ROC curves showed that B-GPA and mB-GPA have similar prognostic capabilities, slightly in favor of mB-GPA.
Subject(s)
Brain Neoplasms/mortality , Brain Neoplasms/secondary , Breast Neoplasms/mortality , Breast Neoplasms/chemistry , Breast Neoplasms/classification , Breast Neoplasms/pathology , Confidence Intervals , Female , Humans , Kaplan-Meier Estimate , Middle Aged , Prognosis , Proportional Hazards Models , Quality of Life , ROC Curve , Receptor, ErbB-2 , Triple Negative Breast Neoplasms/mortality , Triple Negative Breast Neoplasms/pathologyABSTRACT
Widely spread naming inconsistencies in neuroscience pose a vexing obstacle to effective communication within and across areas of expertise. This problem is particularly acute when identifying neuron types and their properties. Hippocampome.org is a web-accessible neuroinformatics resource that organizes existing data about essential properties of all known neuron types in the rodent hippocampal formation. Hippocampome.org links evidence supporting the assignment of a property to a type with direct pointers to quotes and figures. Mining this knowledge from peer-reviewed reports reveals the troubling extent of terminological ambiguity and undefined terms. Examples span simple cases of using multiple synonyms and acronyms for the same molecular biomarkers (or other property) to more complex cases of neuronal naming. New publications often use different terms without mapping them to previous terms. As a result, neurons of the same type are assigned disparate names, while neurons of different types are bestowed the same name. Furthermore, non-unique properties are frequently used as names, and several neuron types are not named at all. In order to alleviate this nomenclature confusion regarding hippocampal neuron types and properties, we introduce a new functionality of Hippocampome.org: a fully searchable, curated catalog of human and machine-readable definitions, each linked to the corresponding neuron and property terms. Furthermore, we extend our robust approach to providing each neuron type with an informative name and unique identifier by mapping all encountered synonyms and homonyms.
ABSTRACT
In the last few years, several imaging methods, such as magnetic resonance imaging (MRI) and computed tomography, have been used to investigate the degree of blood-brain barrier (BBB) permeability in patients with neurological diseases including multiple sclerosis, ischemic stroke, and brain tumors. One promising MRI method for assessing the BBB permeability of patients with neurological diseases in vivo is T1-weighted dynamic contrast-enhanced (DCE)-MRI. Here we review the technical issues involved in DCE-MRI in the study of human brain tumors. In the first part of this paper, theoretical models for the DCE-MRI analysis will be described, including the Toft-Kety models, the adiabatic approximation to the tissue homogeneity model and the two-compartment exchange model. These models can be used to estimate important kinetic parameters related to BBB permeability. In the second part of this paper, details of the data acquisition, issues related to the arterial input function, and procedures for DCE-MRI image analysis are illustrated.
