Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Introduction: Low level of vitamin D (VD) has been linked with a higher risk of cancers. The aim of this study was to assess the prevalence of low VD in patients with breast cancer in a predominantly Mexican Hispanic/Latino patient population, a fast growing and relatively understudied population.

Materials/methods: We sought to evaluate the serum VD levels in breast cancer patients diagnosed at the Texas Tech University Breast Cancer Center in El Paso, TX, between May 2013 and May2014 via a retrospective chart review of the Electronic Medical Records.

Results: We identified a total of 83 consecutive breast cancer patients with available VD levels. Mean age 57 yr, 94% were Hispanics. VD was insufficient (<30 ng/ml) in 86% of patients (95% CI: 0.76-0.92) and it was deficient (<20 ng/ml) in 39% (95% CI: 0.28-0.50).

Conclusion: VD deficiency is widely prevalent in Hispanic/Latino patients with breast cancer. This is quite alarming in view of possible increased risk of cancer with low VD and potentially worse cancer outcomes. This calls for increased efforts to screen for, diagnose, and treat VD deficiency in this patient population. Further pharmacogenomics studies are warranted to explore the underlying etiology of VD deficiency in this paradoxically sunny region.

Download full-text PDF

Source
http://dx.doi.org/10.1080/01635581.2017.1339812DOI Listing

Publication Analysis

Top Keywords

breast cancer
20
prevalence low
8
patients breast
8
cancer patients
8
breast
5
cancer
5
low vitamin
4
patients
4
vitamin patients
4
cancer hispanic
4

Similar Publications

Purpose: Breast cancer remains a significant public health challenge globally, as well as in India, where it is the most frequently diagnosed cancer in females. Significant disparities in incidence, mortality, and access to health care across India's sociodemographically diverse population highlight the need for increased awareness, policy reform, and research.

Design: This review consolidates data from national cancer registries, global cancer databases, and institutional findings from a tertiary care center to examine the epidemiology, clinical challenges, and management gaps specific to India.

View Article and Find Full Text PDF

ObjectiveTo study the implications of implementing artificial intelligence (AI) as a decision support tool in the Norwegian breast cancer screening program concerning cost-effectiveness and time savings for radiologists.MethodsIn a decision tree model using recent data from AI vendors and the Cancer Registry of Norway, and assuming equal effectiveness of radiologists plus AI compared to standard practice, we simulated costs, effects and radiologist person-years over the next 20 years under different scenarios: 1) Assuming a €1 additional running cost of AI instead of the €3 assumed in the base case, 2) varying the AI-score thresholds for single vs. double readings, 3) varying the consensus and recall rates, and 4) reductions in the interval cancer rate compared to standard practice.

View Article and Find Full Text PDF

Background: Among childhood cancer survivors, germline rare variants in autosomal dominant cancer susceptibility genes (AD CSGs) could increase subsequent neoplasm (SNs) risks, but risks for rarer SNs and by age at onset are not well understood.

Methods: We pooled the Childhood Cancer Survivor Study and St Jude Lifetime Cohort (median follow-up = 29.7 years, range 7.

View Article and Find Full Text PDF

MicroRNAs (miRNAs) are critical regulators of gene expression in cancer biology, yet their spatial dynamics within tumor microenvironments (TMEs) remain underexplored due to technical limitations in current spatial transcriptomics (ST) technologies. To address this gap, we present STmiR, a novel XGBoost-based framework for spatially resolved miRNA activity prediction. STmiR integrates bulk RNA-seq data (TCGA and CCLE) with spatial transcriptomics profiles to model nonlinear miRNA-mRNA interactions, achieving high predictive accuracy (Spearman's ρ > 0.

View Article and Find Full Text PDF

Objective: This study employs integrated network toxicology and molecular docking to investigate the molecular basis underlying 4-nonylphenol (4-NP)-mediated enhancement of breast cancer susceptibility.

Methods: We integrated data from multiple databases, including ChEMBL, STITCH, Swiss Target Prediction, GeneCards, OMIM and TTD. Core compound-disease-associated target genes were identified through Protein-Protein Interaction (PPI) network analysis.

View Article and Find Full Text PDF