Quantification of Lean Bodyweight

AbstractBackground: Lean bodyweight (LBW) has been recommended for scaling drug doses. However, the current methods for predicting LBW are inconsistent at extremes of size and could be misleading with respect to interpreting weight-based regimens. Objective: The objective of the present study was to develop a semi-mechanistic model to predict fat-free mass (FFM) from subject characteristics in a population that includes extremes of size. FFM is considered to closely approximate LBW. There are several reference methods for assessing FFM, whereas there are no reference standards for LBW. Patients and methods: A total of 373 patients (168 male, 205 female) were included in the study. These data arose from two populations. Population A (index dataset) contained anthropometric characteristics, FFM estimated by dual-energy x-ray absorptiometry (DXA — a reference method) and bioelectrical impedance analysis (BIA) data. Population B (test dataset) contained the same anthropometric measures and FFM data as population A, but excluded BIA data. The patients in population A had a wide range of age (18–82 years), bodyweight (40.7–216.5kg) and BMI values (17.1–69.9 kg/m2). Patients in population B had BMI values of 18.7–38.4 kg/m2. A two-stage semi-mechanistic model to predict FFM was developed from the demographics from population A. For stage 1 a model was developed to predict impedance and for stage 2 a model that incorporated predicted impedance was used to predict FFM. These two models were combined to provide an overall model to predict FFM from patient characteristics. The developed model for FFM was externally evaluated by predicting into population B. Results: The semi-mechanistic model to predict impedance incorporated sex, height and bodyweight. The developed model provides a good predictor of impedance for both males and females (r2 = 0.78, mean error [ME] = 2.30 × 10−3, root mean square error [RMSE] = 51.56 [approximately 10% of mean]). The final model for FFM incorporated sex, height and bodyweight. The developed model for FFM provided good predictive performance for both males and females (r2 = 0.93, ME = −0.77, RMSE = 3.33 [approximately 6% of mean]). In addition, the model accurately predicted the FFM of subjects in population B (r2 = 0.85, ME = −0.04, RMSE = 4.39 [approximately 7% of mean]). Conclusions: A semi-mechanistic model has been developed to predict FFM (and therefore LBW) from easily accessible patient characteristics. This model has been prospectively evaluated and shown to have good predictive performance.

[1]  J. Garrow,et al.  Quetelet's index (W/H2) as a measure of fatness. , 1985, International journal of obesity.

[2]  C. Kirkpatrick,et al.  A Standard Weight Descriptor for Dose Adjustment in the Obese Patient , 2004, Clinical pharmacokinetics.

[3]  F. Pi‐Sunyer,et al.  Obesity: criteria and classification* , 2000, Proceedings of the Nutrition Society.

[4]  S. Heymsfield,et al.  Human Body Composition , 1996 .

[5]  N. Wulfsohn,et al.  Succinylcholine dosage based on lean body mass , 1972, Canadian Anaesthetists' Society journal.

[6]  P. Kopelman Obesity as a medical problem , 2000, Nature.

[7]  G. Cheymol Effects of Obesity on Pharmacokinetics , 2000 .

[8]  R A Boileau,et al.  Skinfold equations for estimation of body fatness in children and youth. , 1988, Human biology.

[9]  P. Katzmarzyk,et al.  Validity of the body mass index as an indicator of the risk and presence of overweight in adolescents. , 1999, The American journal of clinical nutrition.

[10]  Stephen B Duffull,et al.  Development of a dosing strategy for enoxaparin in obese patients. , 2003, British journal of clinical pharmacology.

[11]  W. P. T. James,et al.  Research on obesity. , 1977, Nutrition reviews.

[12]  A. Sarría,et al.  Skinfold thickness measurements are better predictors of body fat percentage than body mass index in male Spanish children and adolescents , 1998, European Journal of Clinical Nutrition.

[13]  J. Durnin,et al.  A comparison of the fat-free mass of young adults estimated by anthropometry, body density and total body potassium content. , 1972, Clinical science.

[14]  S. Heymsfield,et al.  Appendicular skeletal muscle mass: measurement by dual-photon absorptiometry. , 1990, The American journal of clinical nutrition.

[15]  D. Morgan,et al.  Lean Body Mass as a Predictor of Drug Dosage , 1994, Clinical pharmacokinetics.

[16]  Timothy G. Lohman,et al.  Advances in Body Composition Assessment , 1992 .

[17]  Sarubbi Fa,et al.  Amikacin Serum Concentrations: Prediction of Levels and Dosage Guidelines , 1978 .

[18]  H C Lukaski,et al.  Validation of tetrapolar bioelectrical impedance method to assess human body composition. , 1986, Journal of applied physiology.

[19]  H. Akaike A new look at the statistical model identification , 1974 .

[20]  R. Hume,et al.  The relation of total body potassium to height, weight, and age in normal adults , 1972, Journal of clinical pathology.

[21]  J. Yudkin Book Review: Obesity: A Report of the Royal College of Physicians , 1983, Journal of the Royal College of Physicians of London.

[22]  K. Ellis Human body composition: in vivo methods. , 2000, Physiological reviews.

[23]  S. Duffull,et al.  Caution when lean body weight is used as a size descriptor for obese subjects. , 2002, Clinical pharmacology and therapeutics.

[24]  C. Pichard,et al.  Single prediction equation for bioelectrical impedance analysis in adults aged 20--94 years. , 2001, Nutrition.

[25]  M. G. Henriksen,et al.  In vivo measurement of human body composition by dual-energy X-ray absorptiometry (DXA). , 2003, The European journal of surgery = Acta chirurgica.

[26]  S. Yanovski,et al.  Bioelectrical impedance analysis in body composition measurement : proceedings of a National Institutes of Health Technology Assessment Conference held in Bethesda, MD, December 12-14, 1994 , 1996 .

[27]  S. Duffull,et al.  What is the best size descriptor to use for pharmacokinetic studies in the obese? , 2004, British journal of clinical pharmacology.

[28]  H C Lukaski,et al.  Assessment of fat-free mass using bioelectrical impedance measurements of the human body. , 1985, The American journal of clinical nutrition.

[29]  G. Bray,et al.  Skinfold thickness measurements in obese subjects. , 1990, The American journal of clinical nutrition.

[30]  R. Hume,et al.  Relationship between total body water and surface area in normal and obese subjects , 1971, Journal of clinical pathology.

[31]  S B Heymsfield,et al.  Dual-energy X-ray absorptiometry body composition model: review of physical concepts. , 1996, The American journal of physiology.

[32]  G. Blake,et al.  Technical principles of dual energy x-ray absorptiometry. , 1997, Seminars in nuclear medicine.

[33]  W. Hannan,et al.  Prediction of fat and fat-free mass in male athletes using dual X-ray absorptiometry as the reference method , 2000, Journal of sports sciences.

[34]  Lewis B. Sheiner,et al.  Some suggestions for measuring predictive performance , 1981, Journal of Pharmacokinetics and Biopharmaceutics.