METHODS: The development data set comprised 138,309 women from 17 case-control studies. PRSs were generated using a clumping and thresholding method, lasso penalized regression, an Empirical Bayes approach, a Bayesian polygenic prediction approach, or linear combinations of multiple PRSs. These PRSs were evaluated in 89,898 women from 3 prospective studies (1592 incident cases).
RESULTS: The best performing PRS (genome-wide set of single-nucleotide variations [formerly single-nucleotide polymorphism]) had a hazard ratio per unit SD of 1.62 (95% CI = 1.46-1.80) and an area under the receiver operating curve of 0.635 (95% CI = 0.622-0.649). Combined Asian and European PRSs (333 single-nucleotide variations) had a hazard ratio per SD of 1.53 (95% CI = 1.37-1.71) and an area under the receiver operating curve of 0.621 (95% CI = 0.608-0.635). The distribution of the latter PRS was different across ethnic subgroups, confirming the importance of population-specific calibration for valid estimation of breast cancer risk.
CONCLUSION: PRSs developed in this study, from association data from multiple ancestries, can enhance risk stratification for women of Asian ancestry.
SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1007/s13197-021-05039-y).
OBJECTIVE: The aim of this proof-of-concept study was to evaluate whether combining population pharmacokinetic and machine learning approaches could provide a more accurate prediction of the clearance of renally eliminated drugs in individual neonates.
METHODS: Six drugs that are primarily eliminated by the kidneys were selected (vancomycin, latamoxef, cefepime, azlocillin, ceftazidime, and amoxicillin) as 'proof of concept' compounds. Individual estimates of clearance obtained from population pharmacokinetic models were used as reference clearances, and diverse machine learning methods and nested cross-validation were adopted and evaluated against these reference clearances. The predictive performance of these combined methods was compared with the performance of two other predictive methods: a covariate-based maturation model and a postmenstrual age and body weight scaling model. Relative error was used to evaluate the different methods.
RESULTS: The extra tree regressor was selected as the best-fit machine learning method. Using the combined method, more than 95% of predictions for all six drugs had a relative error of < 50% and the mean relative error was reduced by an average of 44.3% and 71.3% compared with the other two predictive methods.
CONCLUSION: A combined population pharmacokinetic and machine learning approach provided improved predictions of individual clearances of renally cleared drugs in neonates. For a new patient treated in clinical practice, individual clearance can be predicted a priori using our model code combined with demographic data.
METHODS: We obtained viral hepatitis mortality data from the WHO Mortality Database for six East and Southeast Asian countries between 1987 and 2015. We produced choropleth maps of viral hepatitis mortality rates in 1987 and 2015 in East and Southeast Asia to illustrate geographic variations. We made predictions of mortality rates for each included country until the year 2030 using a series of joinpoint models.
RESULTS: Viral hepatitis mortality rates declined in China (the average annual percent change (AAPC) = -5.1%, 95% CI: -7.5, -2.6), Singapore (AAPC = -5.4%, 95% CI: -7.5, -3.2), and the Philippines (AAPC = -3.4%, 95% CI: -4.9, -1.8). In contrast, Japan, the Republic of Korea, and Malaysia have experienced increasing trends in mortality rates, followed by decreasing trends. Our predictions indicate that all countries will experience slight to moderate downward trends until 2030.
CONCLUSION: Favourable decreasing trends have been noted in East and Southeast Asian countries, which may not only inform the control and management of viral hepatitis in this region but also guide the prevention of viral hepatitis deaths in another region with a similar viral hepatitis epidemic.
METHODS: Data were obtained from 18 countries, or functionally self-governing areas, in the Far East, 17 of which were also included in the original study. An online questionnaire was completed by leading CAP professionals in each country. Questions were expanded in the present study to capture the contents of CAP training.
RESULTS: When compared to data from the original study, there has been progress in CAP training systems in the last 5 years. Specifically, there has been an increase in the number of countries with CAP training programs and national guidelines for the training. In addition, the number of CAP departments/divisions affiliated with academic institutions/universities has increased. Findings from 12 of 18 countries in the present study provide data on clinical contents. All informants of the present study reported the need for more child and adolescent psychiatrists and allied professionals.
CONCLUSION: Despite progress in CAP training systems over the last 5 years, the need for more professionals in child and adolescent mental health care in all the relevant areas in this region have yet to be adequately addressed. Continued national efforts and international collaborations are imperative to developing and sustaining new CAP training systems while facilitating improvements in existing programs.