Journal of clinical epidemiology
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Comparative Study
Body mass index compared to dual-energy x-ray absorptiometry: evidence for a spectrum bias.
The objective of this study was to evaluate the accuracy of body mass index (BMI) in the diagnosis of obesity. The relationship of this weight-for-height index to body composition was determined using dual-energy x-ray absorptiometry (DEXA) in 226 Caucasian subjects. BMI-obesity was defined as a BMI greater than 27.8 kg/m2 in males and greater than 27.3 kg/m2 in females. ⋯ When analyzing subgroups of subjects according to weight, sensitivity was higher among heavier subjects than among lighter ones. In both sexes and in all subgroups, the specificity was 100%. The clinical implication of this spectrum bias is that, in men or women weighing less than 80 kg, measures of obesity other than BMI, such as bioelectrical impedance, should be preferred.
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To determine eligibility for a (randomized) clinical trial, measuring the inclusion and exclusion criteria can be extended over a period of time. During this period, known as the selection period, a patient is repeatedly examined at certain time intervals. This study describes an approach for optimizing the efficiency of the selection period. ⋯ As the initial costs per randomization were $1444, there would be a 3.6% (52/1444) savings in recruitment costs under the prediction models, accounting for a savings of more than $450,000. We conclude that the use of data obtained early in a selection period can predict subsequent exclusions, and therefore could increase the efficiency of such a period. The approach could be applied to data obtained in a pilot study as well as data obtained in the beginning of a prolonged intake period.