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Journal of Diabetes Research
Volume 2015 (2015), Article ID 157201, 9 pages
Review Article

Effects of Glucagon-Like Peptide-1 Receptor Agonists on Weight Loss in Patients with Type 2 Diabetes: A Systematic Review and Network Meta-Analysis

1Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, 38 Xueyuan Road, Haidian District, Beijing 100191, China
2Department of Preventive Medicine, College of Medicine, Shihezi University, Shihezi 832002, China
3Department of Physiology, Capital Medical University, Beijing 100069, China
4Department of Statistics, Graduate School of Arts and Sciences, Columbia University, New York, NY 10027, USA
5Department of Orthopedics, Tianjin Fifth Central Hospital, Tianjin 300450, China
6Shantou-Oxford Clinical Research Unit, Shantou University Medical College, Shantou 515041, China
7Department of Endocrinology and Metabolism, People’s Hospital, Peking University, Beijing 100044, China

Received 18 September 2014; Revised 12 December 2014; Accepted 22 December 2014

Academic Editor: Mitsuhiko Noda

Copyright © 2015 Feng Sun et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Supplementary Material

Supplementary Table 1: The overall quality of total 51 studies was rated according to JADAD scale. The proportion of appropriate description of randomization, allocation concealment, blinding and dropout were 78.43% (40/51), 50.98% (26/51), 52.94% (27/51) and 88.24% (45/51) respectively. Additionally, 90.20% (46/51) trials were used intention-to-treat analysis.

Supplementary Table 2: Statistical inconsistency between direct and indirect comparisons was generally low for weight control. Most loops (90.70%, 39/43) of 27 triangular loops and 16 quadratic loops were consistent.

Supplementary Figure 1: Probabilities for each treatment can be plotted in absolute rankograms or cumulative rankograms. A simple numerical summary supplying the graphical display of cumulative ranking used to estimate the surface under the cumulative line for each treatment. Larger SUCRA means the drug has lower ranking.

Supplementary Figure 2: The forest plots for inconsistence check showed that most loops’ 95%CIs included 0, meaning the direct estimate of the summary effect was not different from the indirect estimate.

  1. Supplementary Materials