Nottingham Prognostic Index is an Applicable Prognostic Tool in Non-Metastatic Triple-Negative Breast Cancer

Introduction: Triple-negative breast cancer (TNBC) is characterized by a poor prognosis due to high mortality and early relapse, requiring the study of its prognostic factors. Tumor size, histological grade and lymph node status represent important parameters that are widely studied in breast cancer, and are retained as prognostic factors by several international guidelines. The Nottingham team combined these parameters into a prognostic score called the Nottingham prognostic index (NPI). In this study, we investigated the influence of NPI on outcomes in non metastatic TNBC. Methodology: This retrospective cohort study included all female patients with non metastatic TNBC who received treatment at the Regional Oncology Center Hassan II Oujda - Morocco, between January 2009 and December 2011. The prognostic impact of the NPI on the survival curves at 5 years was studied using multivariate Cox proportional hazards models. Results: The analysis of the data involved 98 patients, 39 patients (39.8%) were classed in the poor prognosis group with a NPI > 5.4. The Overall survival (OS) and Disease free survival (DFS) rates at 5 years, in this group, were 70 and 55.6 % respectively. After adjusting for clinic-pathological variables, a NPI > 5.4 was associated with mortality (HR: 2.598, 95% CI: 1.423 ­ 4.744, p = 0.002) and disease progression (HR: 2.512, CI to 95%: 1.496 ­ 4.219, p <0.001) in patients with non-metastatic TNBC. Conclusion: This retrospective cohort analysis showed that NPI was an independent prognostic factor for OS and DFS at 5 years in women with non metastatic TNBC. Once validated, the impact of this score on survival outcomes could be considered in the clinical management of TNBC.

Bottom-up and top-down brain functional connectivity underlying comprehension of everyday visual action.

How can the components of visual comprehension be characterized as brain activity? Making sense of a dynamic visual world involves perceiving streams of activity as discrete units such as eating breakfast or walking the dog. In order to parse activity into distinct events, the brain relies on both the perceptual (bottom-up) data available in the stimulus as well as on expectations about the course of the activity based on previous experience with, or knowledge about, similar types of activity (top-down data). Using fMRI, we examined the contribution of bottom-up and top-down processing to the comprehension of action streams by contrasting familiar action sequences with those having exactly the same perceptual detection and motor responses (yoked control), but no visual action familiarity. New methods incorporating structural equation modeling of the data yielded distinct patterns of interactivity among brain areas as a function of the degree to which bottom-up and top-down data were available.