METHOD: The study applied a quantitative approach based on the cross-sectional survey design and multistage cluster random sampling. A total of 400 women aged 35-69 years, were surveyed at 4 obstetric and gynecologic clinics affiliated to Tehran University of Medical Sciences in Tehran: the participation levels of 86 women who have had a mammogram were analyzed based on their self-efficacy, belief, social influence, and barriers concerning mammography utilization.
RESULTS: Consistent with the study framework, in bivariate analysis, the higher level of women's participation in breast cancer prevention programs was significantly related to more positive belief about mammography (p< .05), greater social influence on mammography (p< .01) and fewer barriers to mammography (p< .01). Self efficacy (p= .114) was not significantly related to the higher level of participation.
CONCLUSION: Results suggest that women's participation levels in breast cancer prevention programs might be associated with the specific psychosocial factors on breast cancer preventive behavior such as mammography screening.
METHODS: RNA was isolated from peripheral whole blood samples (2 x 10 ml) collected from NPC patients/controls (EDTA vacutainer). Gene expression patterns from 99 samples (66 NPC; 33 controls) were assessed using the Affymetrix array. We also collected expression data from 447 patients with other cancers (201 patients) and non-cancer conditions (246 patients). Multivariate logistic regression analysis was used to obtain biomarker signatures differentiating NPC samples from controls and other diseases. Differences were also analysed within a subset (n=28) of a pre-intervention case cohort of patients whom we followed post-treatment.
RESULTS: A blood-based gene expression signature composed of three genes - LDLRAP1, PHF20, and LUC7L3 - is able to differentiate NPC from various other diseases and from unaffected controls with significant accuracy (area under the receiver operating characteristic curve of over 0.90). By subdividing our NPC cohort according to the degree of patient response to treatment we have been able to identify a blood gene signature that may be able to guide the selection of treatment.
CONCLUSION: We have identified a blood-based gene signature that accurately distinguished NPC patients from controls and from patients with other diseases. The genes in the signature, LDLRAP1, PHF20, and LUC7L3, are known to be involved in carcinoma of the head and neck, tumour-associated antigens, and/or cellular signalling. We have also identified blood-based biomarkers that are (potentially) able to predict those patients who are more likely to respond to treatment for NPC. These findings have significant clinical implications for optimizing NPC therapy.