Trial Outcomes & Findings for A Study to Measure Energy Expenditure and Food Intake in Participants With Obesity Using Tirzepatide (NCT NCT04081337)

A Study to Measure Energy Expenditure and Food Intake in Participants With Obesity Using Tirzepatide

SMR was measured using whole-room indirect calorimetry (respiratory chamber). Change from Baseline to Week 18 in SMR was evaluated. Least square (LS) mean was determined by analysis of covariance (ANCOVA) model with Baseline, Treatment, Change from Baseline to Week 18 in Fat-Free Mass, Change from baseline to Week 18 in Fat Mass and Random Error as variables.

Ad libitum lunch and dinner were provided. The sum of the caloric breakdown (carbohydrates, protein, and fats) was calculated from the respective nutritional information of the food items. LS mean was determined by ANCOVA model with Baseline, Treatment and Random Error as variables.

24 hour energy expenditure was measured in a respiratory chamber. LS mean was determined by ANCOVA model with Baseline, Treatment, Change from Baseline to Week 18 in Fat-Free Mass, Change from baseline to Week 18 in Fat Mass and Random Error as variables.

Respiratory quotient was calculated as the ratio of carbon dioxide production to oxygen consumption as measured in a metabolic chamber for 24 continuous hours. Ratio of total carbon dioxide production (VCO2)/total oxygen consumption (VO2), from baseline to Week 18 was evaluated. 24-hour RQ = total VCO2 \[Liter/24hour\] / total VO2 \[Liter/24hour\]. LS mean was determined by ANCOVA model with Baseline, Treatment and Random Error as variables.

Sleep RQ is defined as the ratio of VCO2 to VO2 during sleep time points. Change from baseline to Week 18 in sleep RQ is presented. LS mean was determined by ANCOVA model with Baseline, Treatment and Random Error as variables.

RQ\<0.80 is defined as the cut point for high lipid oxidation of RQ; lipid oxidation will be calculated and corrected for protein oxidation; the total number of minutes with RQ \<0.80, termed "lipid oxidation duration," during each 23-hour measurement period will be recorded; protein oxidation will be determined from urine nitrogen that will be collected during 2 periods for each calorimeter day. LS mean was determined by ANCOVA model with Baseline, Treatment and Random Error as variables.

Change from Baseline to Week 18 in Fat, Protein, and Carbohydrate Oxidation is presented. * Protein Oxidation = 6.25\*\[urinary nitrogen\] * Fat Oxidation = 1.689\*\[total oxygen consumption (VO2)\] - 1.689\*\[total carbon dioxide production (VCO2)\] - 0.324\*\[protein oxidation\] * Carbohydrate Oxidation = 4.113\*\[VCO2\] - 2.907\*\[VO2\] - 0.375\*\[protein oxidation\]. Adjusted oxidation is calculated using the formula, Adjusted oxidation rate (g/day) = oxidation rate (g/day) / 24-hour Energy Expenditure) x 1000 (kcal/day). LS mean was determined by ANCOVA model with Baseline, Treatment and Random Error as variables.

Change from baseline in BW through Week 18 in participants were presented. LS mean was determined by mixed measures repeated model (MMRM) model with Baseline, Treatment, Time, Treatment\*Time, Participant and Random Error as variables.

Change from baseline to Week 18 in body fat free mass is presented. Body fat free mass was measured using dual energy X-ray absorptiometry (DXA) measurements. LS mean was determined by ANCOVA model with Baseline, Treatment and Random Error as variables.

Change from baseline to Week 18 in body fat mass is presented. Body fat mass was measured using DXA measurements. LS mean was determined by ANCOVA model with Baseline, Treatment and Random Error as variables.

The total body fat mass was measured in kilograms (kg) using DXA scanning. Change from baseline to week 18 in percentage of body fat mass is reported. LS mean was determined by ANCOVA model with Baseline, Treatment and Random Error as variables.

Change in Lipid Metabolism Parameters from baseline (week 0) to week 18 is evaluated. Triglyceride, Very low density lipoprotein (VLDL), High density lipoprotein (HDL) cholesterol and free fatty acids values were reported. Results below presents Area under the Curve (AUC) during standardized mixed-meal tolerance test (sMMTT). LS mean was determined by ANCOVA model with Baseline, Treatment and Random Error as variables.

Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) is a test that uses a simultaneous fasting blood glucose test and fasting insulin test to accurately estimate the degree of insulin resistance (IR) and β-cell function (the cells of the pancreas that produce insulin). HOMA-IR= \[Fasting glucose (mmol/L) x (fasting insulin (picomoles per liter {pmol/L})/6)\] / 22.5. LS mean was determined by ANCOVA model with Baseline, Treatment and Random Error as variables.

Insulin sensitivity was measured from insulin and glucose levels obtained following standard meal challenge using a modification of the Matsuda index. This was calculated based on data obtained from a 75 g oral glucose tolerance test, as follows: 10,000 divided by the square root of {(fasting glucose X fasting insulin) (total area under the glucose response curve (AUC) 0-4hr)) X total insulin AUC(0-4hr )}. A Matsuda index of \<2.5 indicates whole body insulin resistance. A lower Matsuda Index indicates the worst disease state. An increase in the Matsuda Index indicates an improvement in insulin sensitivity (best). A positive change from Baseline indicates improvement and a negative change from Baseline indicates a worsening. Stumvoll and oral glucose insulin sensitivity indexes were also used for measuring the insulin Sensitivity. LS mean was determined by ANCOVA model with Baseline, Treatment and Random Error as variables.

Total AUC from time zero to 4 hours after start of the meal \[AUC0-4 hours\]) during sMMTT was evaluated. LS mean was determined by ANCOVA model with Baseline, Treatment and Random Error as variables.

HbA1c is a form of hemoglobin which is measured primarily to identify the average plasma glucose concentration over prolonged periods of time. LS mean was determined by ANCOVA model with Baseline, Treatment, Time, Treatment\*Time, Participant and Random Error as variables.