%0 DATA
%A Reza, Yavari
%A Erin, McEntee
%A Michael, McEntee
%A Michael, Brines
%D 2013
%T The receiver operating characteristics of a nominal logistical regression using DXA-derived body composition as independent variables to estimate the probability of DM2 or either DM2 or MS in the full DXA population (IG + CV) show that a large percentage of the diseased individuals can be identified without a high cost of a false positive diagnosis.
%U https://plos.figshare.com/articles/_The_receiver_operating_characteristics_of_a_nominal_logistical_regression_using_DXA_derived_body_composition_as_independent_variables_to_estimate_the_probability_of_DM2_or_either_DM2_or_MS_in_the_full_DXA_population_IG_CV_show_that_a_large_percentage_of_/409387
%R 10.1371/journal.pone.0024017.g004
%2 https://plos.figshare.com/ndownloader/files/739031
%K characteristics
%K nominal
%K logistical
%K regression
%K dxa-derived
%K variables
%K probability
%K dm2
%K ms
%K dxa
%K diseased
%K individuals
%X A) The steep slope of the initial portion of the curve to the inflection point (*) indicates that a high proportion of individuals with DM2 can be identifying using DXA-derived FM and TF. Area under the curve is 0.78 with a standard error of 0.05 (24 subjects with DM2 and 327 without; p<0.0001). The 95% confidence interval is 0.68 to 0.88. [Regression equation: risk of DM2 = 1/(1+e^{−z}), where z = 1.94−0.53(TF)+0.28(FM).] B) Similarly, the ROC for the detection of either DM2 or MS also shows inflection points, consistent with sensitive detection of subjects with disease. The AUC is 0.71±0.03 (103 subjects with disease, 238 without; p<0.0001). The 95% confidence interval for the AUC is 0.64 to 0.77. [Regression equation: k = 2.32−0.24(TF)+0.09(FM)].