Objective: To investigate the effects of the Finnish nationwide selenium (Se) fertilization programme on the Se status of the population. Design and subjects: Serum Se concentrations from 1985±1992 from 1568 healthy children and young adults in southwestern Finland were determined using direct electrothermal atomic absorption spectrometry. Results: The mean concentration in young adults increased from 1.04 mmol/L in 1985 to 1.59 mmol/L in 1990. Children younger than 15 y had lower concentrations than adults, with an increase from 0.87 mmol/L in 1985 to 1.31 mmol/L in 1990. The younger the children, the lower the Se concentrations tended to be. At the age of about seven months no signi®cant difference was noted between breast-fed and formula-fed infants. From 1991, when the amount of Se added to fertilizers was reduced and less foreign high-Se cereal was imported, the Se concentrations decreased in all age groups. Conclusions: The nationwide Se supplementation programme has succeeded in elevating the Se intake and the serum Se concentrations in the Finnish population. Sponsorship: Supported by the Juho Vainio Foundation and the Sigrid Juselius Foundation, Finland.

Background: Predictive models for the risk of hepatocellular carcinoma (HCC) are often appropriate for average-risk population but not tailored for a personalized prediction model for individual risk of hepatocellular carcinoma (HCC), namely personalized prediction model. Aim: The objective of this study is to build up an individually tailored predictive model for HCC by using a Bayesian clinical reasoning algorithm to stratify risk groups of the underlying population. Methods: Data were derived from a community-based screening cohort consisting of 98,552 subjects between 1999 and 2007. Information on HBV and HCV infection status, liver function test, AFT, family history of liver cancer, demographic characteristics, lifestyle variables and relevant biomarkers were collected. The occurrence of HCC was ascertained by the linkage of the nationwide cancer registry till the end of 2007. Bayesian clinical reasoning model was adopted by constructing the basic model taken as the prior model for average-risk subject. We then updated the basic model by sequentially incorporating other risk factors for HCC encrypted in the likelihood ratio to form posterior probability that was used for predicting individual risk of HCC. Results: By dint of Bayesian clinical reasoning model with a step-by-step update of the risk of HCC for the sequentially obtained information, a 57-year-old man was predicted to yield 0.69% of HCC risk with the prior model. After history-taking of having hepatitis B carrier (likelihood ratio [LR]: 3.65), family history (LR: 1.43), and no alcohol drinking (LR: 0.89), the posterior risk for HCC was enhanced up to 3.13%. After further biochemical examination, the updated risk of HCC for a man [the following biomarkers [ALT = 30 IU/L (LR: 0.78), AST = 56 IU/L (LR: 8.99), platelets = (203 × /μL) (unit cube of ten) (LR: 0.55)] was increase to 11.07%. Conclusion: We proposed a individually tailored prediction model for HCC by incorporating routine information with a sequential Bayesian clinical reasoning approach.