Jingjing Yu, Guangtai Song, Jian Yu
Assessment of knowledge, attitude, and practice on early childhood caries among dental undergraduates and residents in China
BMC medical education
health care experiencing drive towards digitisation many countries implementing national health data resources although range cancer risk models exists utility population level risk stratification across cancer types fully explored aimed close gap evaluating pancancer risk models built electronic health records across danish population validation uk biobank retrospective modelling validation study data model development internal validation derived following danish health registries central person registry danish national patient registry death registry cancer registry fulltext medical records secondary care records capital region development data included adults aged 1686 years without previous malignant cancers time period jan 1 1995 dec 31 2014 internal validation period jan 1 2015 april 10 2018 data included adults without previous indication cancer aged 1675 years dec 31 2014 external validation cohort uk biobank included adults without previous indication cancer aged 5075 years used timedependent bayesian cox hazard models built combined medical history danish individuals set 1392 covariates available clinical disease trajectories textmined basic health factors family histories used train predictive models 20 major cancer types models validated cancer incidence 2015 2018 across denmark individuals uk biobank primary outcomes discrimination calibration performance danish registries included 6 732 553 individuals covering 60 million hospital visits 90 million diagnoses total 193 million lifeyears jan 1 1978 april 10 2018 danish registry data covering period jan 1 2015 april 10 2018 used internally validate risk models containing total 4 248 491 individuals remained risk primary malignant cancer diagnosis 67 401 cancer cases recorded external validation evaluated time period uk biobank covering 377 004 individuals 11 486 cancer cases predictive performance models danish data showed good discrimination concordance index 081 sd 008 ranging 066 95 ci 065067 cervix uteri cancer 091 090092 liver cancer performance similar uk biobank direct transfer controlling shifts age distribution concordance index 066 sd 008 ranging 055 95 ci 044066 cervix uteri cancer 078 077079 lung cancer cancer risks associated addition heritable components broad range preceding diagnoses health factors best overall performance seen cancers digestive system oesophageal stomach colorectal liver pancreatic also thyroid kidney uterine cancers data available national electronic health databases used approximate cancer risk factors enable risk predictions cancer types model predictions generalise danish uk healthcare systems emergence multicancer early detection tests electronic health recordbased risk models could supplement screening efforts novo nordisk foundation danish innovation foundation