Spatial analysis of hepatobiliary abnormalities in a population at high-risk of cholangiocarcinoma in Thailand

Cholangiocarcinoma (CCA) is a serious health challenge with low survival prognosis. The liver fluke, Opisthorchis viverrini, plays a role in the aetiology of CCA, through hepatobiliary abnormalities: liver mass (LM), bile duct dilation, and periductal fibrosis (PDF). A population-based CCA screening program, the Cholangiocarcinoma Screening and Care Program, operates in Northeast Thailand. Hepatobiliary abnormalities were identified through ultrasonography. A multivariate zero-inflated, Poisson regression model measured associations between hepatobiliary abnormalities and covariates including age, sex, distance to water resource, and history of O. viverrini infection. Geographic distribution was described using Bayesian spatial analysis methods. Hepatobiliary abnormality prevalence was 38.7%; highest in males aged > 60 years (39.8%). PDF was most prevalent (20.1% of males). The Standardized Morbidity Ratio (SMR) for hepatobiliary abnormalities was highest in the lower and upper parts of the Northeast region.Tis work was supported by Khon Kaen University through CASCAP (Grant no. CASCAP 1/60), the National Research Council of Tailand through the Medical Research Network of the Consortium of Tai Medical Schools (Grant no. MRF.59-076) and National Research Council of Tailand (NRCT/2559-134)

Sex Differences in the Heterogeneous Dynamic Incidence of Oral Cancer: A Comparison between Taiwan and Thailand

Background. This study aims at investigating differences in oral cancer (OC) incidence trends between two populations in Taiwan and Thailand. Methods. We used the population-based cancer registry data from Taiwan (1979-2016) and Khon Kaen (KK), Thailand (1985-2016). We performed joinpoint analyses to detect the trend change points for the OC incidence and to quantify the time trends in both sexes and regions. Age-period-cohort curves were plotted to explain the incidence trends. Results. In Taiwan, the estimated annual increases in OC were approximately 6.0% in males, although the increase slowed after 2009, and 2.6% in females. In KK, the OC incidence steadily decreased by -2.5% per year in females, but there was no obvious change in males. A strong period effect observed in those aged 45-69 years in Taiwanese males resulted in a peak incidence in the middle age group. Decreased period and cohort effects were observed in females in KK. Conclusions. Taiwanese males are the predominant sex affected by OC in Taiwan, and the trend has decelerated since 2009. Age, period, and cohort effects were different between males and females in the two regions

Use of glucometer and fasting blood glucose as screening tools for diabetes mellitus type 2 and glycated haemoglobin as clinical reference in rural community primary care settings of a middle income country

Abstract Background Thailand is considered to be a middle income country, and to control and prevent type 2 diabetes mellitus (T2DM) is one of the main concerns of the Thai Ministry of Public Health (MoPH). Screening for T2DM and care for T2DM patients has been integrated into the primary health care system, especially in rural areas. The intention of this investigation is to link public health research at the academic level with the local health authorities of a district of a north-eastern province of the country. Methods Epidemiological methods were applied to validate the screening tools fasting capillary blood glucose (CBG), measured by glucometer and venous blood for the determination of plasma glucose (VPG), used for screening for T2DM among asymptomatic villagers. For assessing the validity of these two methods glycated haemoglobin (HbA1c) values were determined and used as the ‘clinical reference’. Results All together 669 villagers were investigated. Determinations of CBG and VPG resulted in suspected T2DM cases, with 7.3% when assessed by CBG and 6.4% by VPG using a cutoff point of 7 mmol/L (126 mg/dl). Taking HbA1c determinations with a cutoff point of 7% into account, the proportion of T2DM suspected participants increased to 10.4%. By estimating sensitivity, specificity and the positive predictive value of CBG and VPG against the ‘clinical reference’ of HbA1c, sensitivity below 50% for both screening methods has been observed. The positive predictive value was determined to be 58.5% for CBG and 56.8% for VPG. The specificity of the two screening tests was over 96%. Conclusions The low sensitivity indicates that using fasting CBG or VPG as a screening tool in the field results in a high proportion of diseased individuals remaining undetected. The equally low positive predictive values (below 60%) indicate a high working load for the curative sector in investigating suspected T2DM cases to determine whether they are truly diseased or false positive cases according to the screening method. Further implications of the results and the controversial discussion related to the use of HbA1c as clinical evidence for suffering from T2DM are also discussed.</p

Classification of community-acquired outbreaks for the global transmission of COVID-19: Machine learning and statistical model analysis

Background: As Coronavirus disease 2019 (COVID-19) pandemic led to the unprecedent large-scale repeated surges of epidemics worldwide since the end of 2019, data-driven analysis to look into the duration and case load of each episode of outbreak worldwide has been motivated. Methods: Using open data repository with daily infected, recovered and death cases in the period between March 2020 and April 2021, a descriptive analysis was performed. The susceptible-exposed-infected-recovery model was used to estimate the effective productive number (Rt). The duration taken from Rt > 1 to Rt < 1 and case load were first modelled by using the compound Poisson method. Machine learning analysis using the K-means clustering method was further adopted to classify patterns of community-acquired outbreaks worldwide. Results: The global estimated Rt declined after the first surge of COVID-19 pandemic but there were still two major surges of epidemics occurring in September 2020 and March 2021, respectively, and numerous episodes due to various extents of Nonpharmaceutical Interventions (NPIs). Unsupervised machine learning identified five patterns as “controlled epidemic”, “mutant propagated epidemic”, “propagated epidemic”, “persistent epidemic” and “long persistent epidemic” with the corresponding duration and the logarithm of case load from the lowest (18.6 ± 11.7; 3.4 ± 1.8)) to the highest (258.2 ± 31.9; 11.9 ± 2.4). Countries like Taiwan outside five clusters were classified as no community-acquired outbreak. Conclusion: Data-driven models for the new classification of community-acquired outbreaks are useful for global surveillance of uninterrupted COVID-19 pandemic and provide a timely decision support for the distribution of vaccine and the optimal NPIs from global to local community