Hyeseon Yun, Eun Kyoung Choi
Association between smartphone overdependence and mental health in South Korean adolescents: a secondary data analysis
Child health nursing research
metabolomics increasingly applied towards identification biomarkers disease diagnosis prognosis risk prediction unfortunately among many published metabolomic studies focusing biomarker discovery little consistency relatively little rigor researchers select assess report candidate biomarkers particular studies report measure sensitivity specificity provide receiver operator characteristic roc curves associated confidence intervals even fewer studies explicitly describe release biomarker model used generate roc curves surprising given biomarker studies biomedical fields roc curve analysis generally considered standard method performance assessment ultimate goal biomarker discovery translation biomarkers clinical practice clear metabolomics community needs start speaking language terms biomarker analysis reportingespecially wants see metabolite markers routinely used clinic tutorial first introduce concept roc curves describe use single biomarker analysis clinical chemistry includes construction roc curves understanding meaning area roc curves auc partial auc well calculation confidence intervals second part tutorial focuses biomarker analyses within context metabolomics section describes different statistical machine learning strategies used create multimetabolite biomarker models explains models assessed using roc curves third part tutorial discuss common issues potential pitfalls associated different analysis methods provide readers list nine recommendations biomarker analysis reporting help readers test visualize explore concepts presented tutorial also introduce webbased tool called roccet roc curve explorer tester httpwwwroccetca roccet originally developed teaching aid also serve training testing resource assist metabolomics researchers build biomarker models conduct range common roc curve analyses biomarker studies