TY - JOUR
T1 - Accumulating Data to Optimally Predict Obesity Treatment (ADOPT)
T2 - Recommendations from the Biological Domain
AU - Rosenbaum, Michael
AU - Agurs-Collins, Tanya
AU - Bray, Molly S.
AU - Hall, Kevin D.
AU - Hopkins, Mark
AU - Laughlin, Maren
AU - MacLean, Paul S.
AU - Maruvada, Padma
AU - Savage, Cary R.
AU - Small, Dana M.
AU - Stoeckel, Luke
N1 - Funding Information:
Funding agencies: The ADOPT Core Measures Working Group was supported by intramural funding from the following National Institutes of Health: The National Heart, Lung, and Blood Institute, the National Cancer Institute, and the Office of Disease Prevention. The Grid-Enabled Measures Database (GEM) is supported and administered by the National Cancer Institute. Disclosure: The authors declared no conflict of interest. The views expressed in this paper are those of the authors and do not necessarily represent the positions of the NIH, the DHHS, or the Federal Government. Received: 17 January 2018; Accepted: 12 February 2018; Published online 23 March 2018. doi:10.1002/oby.22156
Publisher Copyright:
© 2018 The Obesity Society
PY - 2018/4
Y1 - 2018/4
N2 - Background: The responses to behavioral, pharmacological, or surgical obesity treatments are highly individualized. The Accumulating Data to Optimally Predict obesity Treatment (ADOPT) project provides a framework for how obesity researchers, working collectively, can generate the evidence base needed to guide the development of tailored, and potentially more effective, strategies for obesity treatment. Objectives: The objective of the ADOPT biological domain subgroup is to create a list of high-priority biological measures for weight-loss studies that will advance the understanding of individual variability in response to adult obesity treatments. This list includes measures of body composition, energy homeostasis (energy intake and output), brain structure and function, and biomarkers, as well as biobanking procedures, which could feasibly be included in most, if not all, studies of obesity treatment. The recommended high-priority measures are selected to balance needs for sensitivity, specificity, and/or comprehensiveness with feasibility to achieve a commonality of usage and increase the breadth and impact of obesity research. Significance: The accumulation of data on key biological factors, along with behavioral, psychosocial, and environmental factors, can generate a more precise description of the interplay and synergy among them and their impact on treatment responses, which can ultimately inform the design and delivery of effective, tailored obesity treatments.
AB - Background: The responses to behavioral, pharmacological, or surgical obesity treatments are highly individualized. The Accumulating Data to Optimally Predict obesity Treatment (ADOPT) project provides a framework for how obesity researchers, working collectively, can generate the evidence base needed to guide the development of tailored, and potentially more effective, strategies for obesity treatment. Objectives: The objective of the ADOPT biological domain subgroup is to create a list of high-priority biological measures for weight-loss studies that will advance the understanding of individual variability in response to adult obesity treatments. This list includes measures of body composition, energy homeostasis (energy intake and output), brain structure and function, and biomarkers, as well as biobanking procedures, which could feasibly be included in most, if not all, studies of obesity treatment. The recommended high-priority measures are selected to balance needs for sensitivity, specificity, and/or comprehensiveness with feasibility to achieve a commonality of usage and increase the breadth and impact of obesity research. Significance: The accumulation of data on key biological factors, along with behavioral, psychosocial, and environmental factors, can generate a more precise description of the interplay and synergy among them and their impact on treatment responses, which can ultimately inform the design and delivery of effective, tailored obesity treatments.
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U2 - 10.1002/oby.22156
DO - 10.1002/oby.22156
M3 - Article
C2 - 29575784
AN - SCOPUS:85044415615
SN - 1930-7381
VL - 26
SP - S25-S34
JO - Obesity
JF - Obesity
ER -