However, it is not clear how they relate to the measures of predictive ability and reclassification, such as the c-statistic and Net Reclassification Improvement (NRI), or how these measures are affected by differences in mean risk between populations when a fixed cutpoint to define high risk is assumed.
We estimated whether differences between the methods were due to differences in the cutpoint (participants were between the cutpoints for the two methods) or due to TEE (TEE would lead to discrepancies even with the same cutpoints).
Similar patterns were also observed by Van Calster and others when they varied the cutpoint and assumed a fixed mean risk; as the cutpoint moved away from mean risk the reclassification measures provided a more optimistic view of the new predictor compared to that provided by the difference in net benefit [ 16].
Furthermore, to examine whether mean differences in cardiometabolic risk factors based upon various excess adiposity cutpoints were present.
Two sources of variation that may lead to differences in classification were explored: the relationship between TEEDLW and TEEGB, and the cutpoints used, which are determined by the within-person variation in rEI and TEE.
We used the quintile cutpoints of the predicted probabilities to compare the net benefits curves of model 1 and model 2 and calculated the differences in the net benefit between the 2 models for the each cutpoint and 95% confidence interval of difference between the 2 models using the rescaled bootstrap method.
For specificity on the FFQ, for men, 64% (9/14) of misclassification was due to differences in the estimate of TEE, and 36% (5/14) was due to differences in the cutpoints; for women, 25% (3/12) was due to TEE, and 75% (9/12) due to the cutpoints.
For sensitivity for the 24HR, in men, 61% (17/28) of misclassification was due to differences in the estimate of TEE, and 39% (11/28) due to differences in the cutpoint; for women 76% (16/21) were misclassified due to differences in the estimate of TEE, and 24% (5/21) were misclassified due to differences in the cutpoint.
This suggests that previous absolute cutpoints based on age or BMI are less likely to account for differences in fitness level that may exist across age or varying body sizes.
