Prediction of the parameters of whole body cholesterol metabolism in humans.

Total body turnover of cholesterol was studied in 54 subjects by fitting a three-pool mathematical model to plasma decay curves of 32--49 weeks duration following [14C]cholesterol injection. Fifteen subjects were normal, 10 hypercholesterolemic, 21 hypertriglyceridemic, and 8 had both hypercholesterolemia and hypertriglyceridemia; 21 had a familial form of hyperlipidemia. In every subject in this heterogeneous population, the three-pool model gave the best fit for the data. An extensive search was conducted for relationships between model parameters and physiological variables (body size, serum lipid levels, age, and sex). Both linear and nonlinear relationships, and those involving interactions between pairs of variables, were explored. Fifty different forms of the model parameters and 53 forms of the physiological variables were examined. To guard against declaring statistical significance when none was present, subjects were first randomly divided into two matched groups. In the first (hypothesis-generating) group of 36 subjects, more than 100,000 regression equations were considered for each form of the model parameters. Twenty-one highly significant equations were found that were then tested in the second group (hypothesis-testing, 18 subjects). Eighteen of the 21 equations were found to be significant; of these, 6 were selected that accounted for a large part of the observed variation in the four model parameters for which equations were found (production rate (PR), and the sizes of pool 1, pool 3, and total exchangeable body cholesterol). The major determinant of cholesterol PR was body weight alone (r = 0.80). No function of serum lipid levels significantly influenced PR. Both body weight and serum cholesterol level entered into the equations for cholesterol mass. Age influenced the size of pool 3. Serum triglyceride level only had an effect on the size of pool 1. Since these equations were generated in one group of subjects and tested in another, they can be considered a confirmed set of predictive equations.

RCT Entities:   Population Interventions Outcomes