Environmental heavy metal as a potential risk factor for the progression of oral potentially malignant disorders in central Taiwan.

OBJECTIVE: Oral cancer (OC) is a leading cause of death from cancer in men between the ages of 25 and 44 years in Taiwan. The overall 5-year survival rates for the four OC stages (I-IV) in Taiwan are approximately 70%, 30%, 20%, and 10%, respectively, indicating the importance of the early diagnosis of oral potentially malignant disorders (OPMDs). Previous studies indicated an association between the OC incidence and certain environmental heavy metal concentrations. If these associations do exist for OC, they may also be observed for OPMD. The purpose of this study is to explore the association between the development of OPMD to OC and environmental heavy metals. Oral submucous fibrosis (OSF) and oral leukoplakia (OL) are two major types of OPMD in Taiwan. MATERIALS AND METHODS: A retrospective cohort study was conducted by Changhua Christian Hospital, the sole medical center in Changhua County, where 2725 male adult patients diagnosed with either OSF or OL between 2000 and 2014 were recruited. Data were analyzed by Cox regression and adjusted for smoking and betel-quid chewing. RESULTS AND DISCUSSION: OPMD patients who resided in areas with high nickel concentrations (polluted levels) exhibited hazard ratios of 1.8-2 for OC relative to those who lived in areas with low nickel levels (P<0.01). Meanwhile, smokers with OPMDs had a hazard ratio of 2.8-2.9 relative to non-smokers. Betel-quid chewers had a 2.2-2.3 hazard ratio relative to non-chewers. Smoking, betel-quid chewing, and environmental nickel exposure are associated with an increased risk of OC development in OPMD patients. This study provides valuable findings on the environmental effects of heavy metals on human health. Enhanced surveillance of the condition of OPMD patients who have been exposed to high nickel concentrations may be crucial for OC prevention.

Re-assess Vector Indices Threshold as an Early Warning Tool for Predicting Dengue Epidemic in a Dengue Non-endemic Country.

BACKGROUND: Despite dengue dynamics being driven by complex interactions between human hosts, mosquito vectors and viruses that are influenced by climate factors, an operational model that will enable health authorities to anticipate the outbreak risk in a dengue non-endemic area has not been developed. The objectives of this study were to evaluate the temporal relationship between meteorological variables, entomological surveillance indices and confirmed dengue cases; and to establish the threshold for entomological surveillance indices including three mosquito larval indices [Breteau (BI), Container (CI) and House indices (HI)] and one adult index (AI) as an early warning tool for dengue epidemic. METHODOLOGY/PRINCIPAL FINDINGS: Epidemiological, entomological and meteorological data were analyzed from 2005 to 2012 in Kaohsiung City, Taiwan. The successive waves of dengue outbreaks with different magnitudes were recorded in Kaohsiung City, and involved a dominant serotype during each epidemic. The annual indigenous dengue cases usually started from May to June and reached a peak in October to November. Vector data from 2005-2012 showed that the peak of the adult mosquito population was followed by a peak in the corresponding dengue activity with a lag period of 1-2 months. Therefore, we focused the analysis on the data from May to December and the high risk district, where the inspection of the immature and mature mosquitoes was carried out on a weekly basis and about 97.9% dengue cases occurred. The two-stage model was utilized here to estimate the risk and time-lag effect of annual dengue outbreaks in Taiwan. First, Poisson regression was used to select the optimal subset of variables and time-lags for predicting the number of dengue cases, and the final results of the multivariate analysis were selected based on the smallest AIC value. Next, each vector index models with selected variables were subjected to multiple logistic regression models to examine the accuracy of predicting the occurrence of dengue cases. The results suggested that Model-AI, BI, CI and HI predicted the occurrence of dengue cases with 83.8, 87.8, 88.3 and 88.4% accuracy, respectively. The predicting threshold based on individual Model-AI, BI, CI and HI was 0.97, 1.16, 1.79 and 0.997, respectively. CONCLUSION/SIGNIFICANCE: There was little evidence of quantifiable association among vector indices, meteorological factors and dengue transmission that could reliably be used for outbreak prediction. Our study here provided the proof-of-concept of how to search for the optimal model and determine the threshold for dengue epidemics. Since those factors used for prediction varied, depending on the ecology and herd immunity level under different geological areas, different thresholds may be developed for different countries using a similar structure of the two-stage model.

Progression of precancerous lesions to oral cancer: results based on the Taiwan National Health Insurance Database.

BACKGROUND: Oral cancer (OC) is the leading cause of death from cancer in men between the ages of 25 and 44 in Taiwan. The survival rate for the last stage of OC is <20% while that for the earliest stage is >75%, which suggests the importance of the diagnosis of oral precancerous lesions (OPLs) in reducing OC mortality. The aim of this study was to analyze the time to OC event after OPL diagnosis, and to suggest the surveillance period necessary according to OPL type. MATERIALS AND METHODS: This was a retrospective cohort study based on 1.0 million people randomly selected from the Taiwan National Health Insurance Database, which provided data on 3058 adult male patients aged ≥20 years who were diagnosed with OPL for the first time between 1996 and 2009. The patient population was divided into two groups according to the type of lesion: oral submucous fibrosis (OSF) or oral leukoplakia (OLE). Age-standardized incidence rate (ASIR) and hazards rate (HR) were then estimated. RESULTS: The ASIR for OPL showed an increasing trend over the study period, the main contributor to this being OSF. The OSF group demonstrated a higher OC incidence rate than the OLE group. CONCLUSION: Patients with both OLE and OSF carry a higher risk for OC than those with either OLE or OSF alone, and they may also experience malignant transformation at an earlier date (mostly within 5 years). The 5- and 10-year OC rate for both OLE and OSF was found to be 5% and around 10%, respectively. However, 10 years after the diagnosis of OPL, OSF carries a higher risk of developing into OC than OLE.