去脂体重：健康成年人预测方程的建立与验证。
Lean body mass: the development and validation of prediction equations in healthy adults.
机构信息
Aged and Extended Care Services, Level 8B Main Building, The Queen Elizabeth Hospital, Central Adelaide Local Health Network, 21 Woodville Road, 5011 Woodville South, SA, Australia.
出版信息
BMC Pharmacol Toxicol. 2013 Oct 14;14:53. doi: 10.1186/2050-6511-14-53.
BACKGROUND
There is a loss of lean body mass (LBM) with increasing age. A low LBM has been associated with increased adverse effects from prescribed medications such as chemotherapy. Accurate assessment of LBM may allow for more accurate drug prescribing. The aims of this study were to develop new prediction equations (PEs) for LBM with anthropometric and biochemical variables from a development cohort and then validate the best performing PEs in validation cohorts.
METHODS
PEs were developed in a cohort of 188 healthy subjects and then validated in a convenience cohort of 52 healthy subjects. The best performing anthropometric PE was then compared to published anthropometric PEs in an older (age≥50 years) cohort of 2287 people. Best subset regression analysis was used to derive PEs. Correlation, Bland-Altman and Sheiner & Beal methods were used to validate and compare the PEs against dual X-ray absorptiometry (DXA)-derived LBM.
RESULTS
The PE which included biochemistry variables performed only marginally better than the anthropometric PE. The anthropometric PE on average over-estimated LBM by 0.74 kg in the combined cohort. Across gender (male vs. female), body mass index (<22, 22-<27, 27-<30 and ≥30 kg/m2) and age groups (50-64, 65-79 and ≥80 years), the maximum mean over-estimation of the anthropometric PE was 1.36 kg.
CONCLUSIONS
A new anthropometric PE has been developed that offers an alternative for clinicians when access to DXA is limited. Further research is required to determine the clinical utility and if it will improve the safety of medication use.
背景
随着年龄的增长，人体会流失瘦体重（LBM）。瘦体重低与化疗等处方药的不良反应增加有关。准确评估瘦体重可能有助于更准确地开具药物。本研究旨在开发新的预测方程（PEs），以根据发展队列中的人体测量学和生化变量来预测 LBM，然后在验证队列中验证表现最佳的 PEs。
方法
在一个 188 名健康受试者的队列中开发 PEs，然后在一个 52 名健康受试者的便利队列中验证。然后，将表现最佳的人体测量学 PE 与 2287 名年龄≥50 岁的老年人队列中的已发表的人体测量学 PEs 进行比较。最佳子集回归分析用于推导 PEs。使用相关性、Bland-Altman 和 Sheiner & Beal 方法来验证和比较 PEs 与双能 X 线吸收法（DXA）衍生的 LBM。
结果
包含生化变量的 PE 仅略优于人体测量学 PE。在联合队列中，人体测量学 PE 平均高估 LBM 0.74 公斤。在性别（男性与女性）、体重指数（<22、22-<27、27-<30 和≥30 kg/m2）和年龄组（50-64、65-79 和≥80 岁）中，人体测量学 PE 的最大平均高估值为 1.36 公斤。
结论
已经开发出一种新的人体测量学 PE，为 DXA 有限时的临床医生提供了一种替代方法。需要进一步研究以确定其临床实用性以及是否会提高药物使用的安全性。
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