Douglas Noble|Rohini Mathur|Tom Dent|Catherine Meads|Trisha Greenhalgh
Risk models and scores for type 2 diabetes: systematic review
Barts Health NHS Trust|Barts Health NHS Trust|PHG Foundation|Barts Health NHS Trust|Barts Health NHS Trust
evaluate current risk models scores type 2 diabetes inform selection implementation practicesystematic review using standard quantitative realist mainly qualitative methodology inclusion criteria papers language describing development external validation models scores predict risk adult developing type 2 diabetesmedline premedline embase cochrane databases searched included studies citation tracked google scholar identify followon studies usability impactdata extracted statistical properties models details internal external validation use risk scores beyond studies developed quantitative data tabulated compare model components statistical properties qualitative data analysed thematically identify mechanisms use risk model score might improve patient outcomes8864 titles scanned 115 full text papers considered 43 papers included final sample described prospective development validation 145 risk prediction models scores 94 studied detail tested 688 million participants followed 28 years heterogeneity primary studies precluded metaanalysis risk models scores robust statistical properties example good discrimination calibration externally validated different population genetic markers added nothing models clinical sociodemographic factors authors described score simple easily implemented although specific intended users circumstances ten mechanisms identified measuring diabetes risk might improve outcomes followon studies applied risk score part intervention aimed reducing actual risk people sparsemuch work done develop diabetes risk models scores rarely used require tests routinely available developed without specific user clear use mind encouragingly recent research begun tackle usability impact diabetes risk scores two promising areas research interventions prompt lay people check diabetes risk use risk scores population datasets identify high risk hotspots targeted public health interventions