Update of NIST half-life results corrected for ionization chamber source-holder instability

As reported at the ICRM 2011, it was discovered that the source holder used for calibrations in the NIST 4πγ ionization chamber (IC) was not stable. This has affected a large number of half-life measurement results previously reported and used in compilations of nuclear data. Corrections have been made on all of the half-life data based on the assumption that the changes to the ionization chamber response were gradual. The corrections are energy dependent and therefore radionuclide specific. This presentation will review our results and present the recommended changes in half-life values and/or uncertainties.     

Prediction impact curve is a new measure integrating intervention effects in the evaluation of risk models

ObjectiveWe propose a new measure of assessing the performance of risk models, the area under the prediction impact curve (auPIC), which quantifies the performance of risk models in terms of their average health impact in the population.Study Design and SettingUsing simulated data, we explain how the prediction impact curve (PIC) estimates the percentage of events prevented when a risk model is used to assign high-risk individuals to an intervention. We apply the PIC to the Atherosclerosis Risk in Communities (ARIC) Study to illustrate its application toward prevention of coronary heart disease.ResultsWe estimated that if the ARIC cohort received statins at baseline, 5% of events would be prevented when the risk model was evaluated at a cutoff threshold of 20% predicted risk compared to 1% when individuals were assigned to the intervention without the use of a model. By calculating the auPIC, we estimated that an average of 15% of events would be prevented when considering performance across the entire interval.ConclusionWe conclude that the PIC is a clinically meaningful measure for quantifying the expected health impact of risk models that supplements existing measures of model performance.