Nasopharyngeal carcinoma (NPC) is originated from the epithelial cells of nasopharynx, Epstein–Barr virus (EBV)‐associated and has the highest incidence and mortality rates in Southeast Asia. Late presentation is a common issue and early detection could be the key to reduce the disease burden. Sensitivity of plasma EBV DNA, an established NPC biomarker, for Stage I NPC is controversial. Most newly reported NPC biomarkers have neither been externally validated nor compared to the established ones. This causes difficulty in planning for cost‐effective early detection strategies. Our study systematically evaluated six established and four new biomarkers in NPC cases, population controls and hospital controls. We showed that BamHI‐W 76 bp remains the most sensitive plasma biomarker, with 96.7% (29/30), 96.7% (58/60) and 97.4% (226/232) sensitivity to detect Stage I, early stage and all NPC, respectively. Its specificity was 94.2% (113/120) against population controls and 90.4% (113/125) against hospital controls. Diagnostic accuracy of BamHI‐W 121 bp and ebv‐miR‐BART7‐3p were validated. Hsa‐miR‐29a‐3p and hsa‐miR‐103a‐3p were not, possibly due to lower number of advanced stage NPC cases included in this subset. Decision tree modeling suggested that combination of BamHI‐W 76 bp and VCA IgA or EA IgG may increase the specificity or sensitivity to detect NPC. EBNA1 99 bp could identify NPC patients with poor prognosis in early and advanced stage NPC. Our findings provided evidence for improvement in NPC screening strategies, covering considerations of opportunistic screening, combining biomarkers to increase sensitivity or specificity and testing biomarkers from single sampled specimen to avoid logistic problems of resampling.
Purpose This scoping review was completed to explore the role and impact of having a return-to-work (RTW) coordinator when dealing with individuals with common mental ill-health conditions. Methods Peer reviewed articles published in English between 2000 and 2018 were considered. Our research team reviewed all articles to determine if an analytic focus on RTW coordinator and mental ill-health was present; consensus on inclusion was reached for all articles. Data were extracted for all relevant articles and synthesized for outcomes of interest. Results Our search of six databases yielded 1798 unique articles; 5 articles were found to be relevant. The searched yielded only quantitative studies. Of those, we found that studies grouped mental ill-health conditions together, did not consider quality of life, and used different titles to describe RTW coordinators. Included articles described roles of RTW coordinators but did not include information on their strategies and actions. Included articles suggest that RTW interventions for mental ill-health that utilize a RTW coordinator may result in delayed time to RTW. Conclusions Our limited findings suggest that interventions for mental ill-health that employ RTW coordinators may be more time consuming than conventional approaches and may not increase RTW rate or worker's self-efficacy for RTW. Research on this topic with long-term outcomes and varied research designs (including qualitative) is needed, as well as studies that clearly define RTW coordinator roles and strategies, delineate results by mental health condition, and address the impact of RTW coordinators on workers' quality of life.
Background: This study aims to determine the hazard ratio of having any complication from diabetes mellitus, and the associations between comorbidities and risk of having any complications from diabetes mellitus among diabetic patients who have attended government primary care clinics. Methods: Secondary data were retrieved from the Malaysian National Diabetic Registry which included all patients who received care. The data from the study on the socio-demographic, diabetes complications, clinical and treatment characteristics were analyzed using descriptive statistics. Cox regression was performed to estimate the hazard ratio for comorbidities, tobacco use, duration of diabetes and socio-demography characteristics upon time to diabetic complications. Results: Adjusted for other covariates, increase number of comorbidities contributed the highest hazard ratio risk: 1 comorbid (aHR:
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