The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Combination of direct and indirect evidence in mixed treatment comparisons
Abstract
Mixed treatment comparison (MTC) meta‐analysis is a generalization of standard pairwise meta‐analysis for A vs B trials, to data structures that include, for example, A vs B, B vs C, and A vs C trials. There are two roles for MTC: one is to strengthen inference concerning the relative efficacy of two treatments, by including both ‘direct’ and ‘indirect’ comparisons. The other is to facilitate simultaneous inference regarding all treatments, in order for example to select the best treatment. In this paper, we present a range of Bayesian hierarchical models using the Markov chain Monte Carlo software WinBUGS. These are multivariate random effects models that allow for variation in true treatment effects across trials. We consider models where the between‐trials variance is homogeneous across treatment comparisons as well as heterogeneous variance models. We also compare models with fixed (unconstrained) baseline study effects with models with random baselines drawn from a common distribution. These models are applied to an illustrative data set and posterior parameter distributions are compared. We discuss model critique and model selection, illustrating the role of Bayesian deviance analysis, and node‐based model criticism. The assumptions underlying the MTC models and their parameterization are also discussed. Copyright © 2004 John Wiley & Sons, Ltd.
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Cites
Network meta‐analysis for indirect treatment comparisons
Lumley, T. (2002) · Statistics in Medicine · doi:10.1002/sim.1201 · Cited by 1,206
Meta‐Analysis Of Controlled Clinical Trials
Whitehead, A. (2002) · doi:10.1002/0470854200 · Cited by 827
Bayesian approaches to random-effects meta-analysis: a comparative study
Smith, T. C., Spiegelhalter, D. J., & Thomas, A. (1995) · Statistics in Medicine · doi:10.1002/sim.4780142408 · Cited by 568 · cited 6×
“Experience has shown that the inverse Gamma priors −2 ∼Gamma(10−3; 10−3) used by many investigators for variance terms in random e ects meta-analysis [2, 8, 13] can on occasion produce di erent results to other formulations, such as ∼Uniform(0; 2), that appear equally ‘uninformative’.”
BackgroundMethodInfluentialA bivariate approach to meta-analysis
Van Houwelingen, H. C., Zwinderman, K. H., & Stijnen, T. (1993) · Statistics in Medicine · doi:10.1002/sim.4780122405 · Cited by 327
Warn, D. E., Thompson, S. G., & Spiegelhalter, D. J. (2002) · Statistics in Medicine · doi:10.1002/sim.1189 · Cited by 277
Cited by
Items 101–129 of 129
Beyer, F., Lynch, E., & Kaner, E. (2018) · Current Addiction Reports · doi:10.1007/s40429-018-0198-7 · Cited by 66
Khan, S. U., Talluri, S., Riaz, H., Rahman, H., Nasir, F., Bin Riaz, I., Sattur, S., Ahmed, H., Kaluski, E., & Krasuski, R. (2018) · European Journal of Preventive Cardiology · doi:10.1177/2047487318766612 · Cited by 61
Naci, H., Dias, S., & Ades, A. E. (2014) · BMJ · doi:10.1136/bmj.g5741 · Cited by 61
O'Connor, A. M., Hu, D., Totton, S. C., Scott, N., Winder, C. B., Wang, B., Wang, C., Glanville, J., Wood, H., White, B., et al. (2019) · Animal Health Research Reviews · doi:10.1017/s1466252320000031 · Cited by 60
Sun, F., Yu, K., Yang, Z., Wu, S., Zhang, Y., Shi, L., Ji, L., & Zhan, S. (2012) · Experimental Diabetes Research · doi:10.1155/2012/230624 · Cited by 58
Toth, P. P., Bray, S., Villa, G., Palagashvili, T., Sattar, N., Stroes, E. S. G., & Worth, G. M. (2022) · Journal of the American Heart Association · doi:10.1161/jaha.122.025551 · Cited by 56
Pescatello, L. S., Wu, Y., Gao, S., Livingston, J., Sheppard, B. B., & Chen, M.-H. (2021) · BMJ Open Sport & Exercise Medicine · doi:10.1136/bmjsem-2020-000895 · Cited by 50
Digital interventions in mental health: Evidence syntheses and economic modelling
Gega, L., Jankovic, D., Saramago, P., Marshall, D., Dawson, S., Brabyn, S., Nikolaidis, G. F., Melton, H., Churchill, R., & Bojke, L. (2022) · Health Technology Assessment · doi:10.3310/rcti6942 · Cited by 48
Abdel-Rahman, O., & Fouad, M. (2016) · Immunotherapy · doi:10.2217/imt-2015-0020 · Cited by 46
Sun, F., Wu, S., Guo, S., Yu, K., Yang, Z., Li, L., Zhang, Y., Ji, L., & Zhan, S. (2015) · Endocrine · doi:10.1007/s12020-014-0373-0 · Cited by 44
Comparing Bona Fide Psychotherapies of Depression in Adults with Two Meta-Analytical Approaches
Braun, S. R., Gregor, B., & Tran, U. S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0068135 · Cited by 41
Navarese, E. P., Gurbel, P. A., Andreotti, F., Kołodziejczak, M. M., Palmer, S. C., Dias, S., Buffon, A., Kubica, J., Kowalewski, M., Jadczyk, T., et al. (2017) · PLOS ONE · doi:10.1371/journal.pone.0168726 · Cited by 38
Application of network meta-analysis in the field of physical activity and health promotion
Su, X., McDonough, D. J., Chu, H., Quan, M., & Gao, Z. (2020) · Journal of Sport and Health Science · doi:10.1016/j.jshs.2020.07.011 · Cited by 38
“, between-trial) comparisons of multiple intervention strategies that may not be directly compared within the same trial.(3,9,10) The most basic requisite for conducting indirect quantitative comparisons using NMA is that there should be at least 1 intervention strategy in common for each chain of comparison.”
Background‘Arm‐based’ parameterization for network meta‐analysis
Hawkins, N., Scott, D. A., & Woods, B. (2016) · Research Synthesis Methods · doi:10.1002/jrsm.1187 · Cited by 35
Assessing the robustness of results from clinical trials and meta-analyses with the fragility index
Lin, L., Xing, A., Chu, H., Murad, M. H., Xu, C., Baer, B. R., Wells, M. T., & Sanchez-Ramos, L. (2023) · American Journal of Obstetrics and Gynecology · doi:10.1016/j.ajog.2022.08.053 · Cited by 35
Zhou, X., Cipriani, A., Zhang, Y., Cuijpers, P., Hetrick, S. E., Weisz, J. R., Pu, J., Giovane, C. D., Furukawa, T. A., Barth, J., et al. (2017) · BMJ Open · doi:10.1136/bmjopen-2017-016608 · Cited by 31
Hunot, V., Moore, T. H., Caldwell, D., Davies, P., Jones, H., Lewis, G., & Churchill, R. (2010) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd008704 · Cited by 29
Zhang, T., Ye, X., Zhu, T., XIAO, X., Liu, Y., Wei, X., Liu, Y., Wu, C., Guan, R., Li, X., et al. (2015) · Medicine · doi:10.1097/md.0000000000001732 · Cited by 28
Bayesian multivariate meta-analysis of multiple factors
Lin, L., & Chu, H. (2018) · Research Synthesis Methods · doi:10.1002/jrsm.1293 · Cited by 19
Rollins, B. M., Silva, M. A., Donovan, J. L., & Kanaan, A. O. (2014) · Clinical Therapeutics · doi:10.1016/j.clinthera.2014.06.033 · Cited by 18
Cheng, Y.-S., Tseng, P.-T., Wu, Y.-C., Tu, Y.-K., Wu, C.-K., Hsu, C.-W., Lei, W.-T., Li, D.-J., Chen, T.-Y., Stubbs, B., et al. (2021) · Journal of Psychiatry and Neuroscience · doi:10.1503/jpn.190122 · Cited by 16
Tseng, P., Zeng, B., Wang, H., Zeng, B., Liang, C., Chen, Y. B., Stubbs, B., Carvalho, A. F., Brunoni, A. R., Su, K., et al. (2024) · Acta Psychiatrica Scandinavica · doi:10.1111/acps.13688 · Cited by 14
Yang, Y., He, L., Liu, P., Wang, J., Yang, N., Li, Z., Ping, F., Xu, L., Li, W., Zhang, H., et al. (2024) · Diabetes, Obesity and Metabolism · doi:10.1111/dom.15342 · Cited by 12
Ma, Y., Sun, L., & Mu, Z. (2024) · International Journal of Obesity · doi:10.1038/s41366-023-01416-z · Cited by 12
Behavioural therapies versus other psychological therapies for depression
Churchill, R., Caldwell, D., Moore, T. H., Davies, P., Jones, H., Lewis, G., & Hunot, V. (2010) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd008696 · Cited by 11
Zhang, Y., Zhou, X., James, A. C., Qin, B., Whittington, C. J., Cuijpers, P., Del Giovane, C., Liu, Y., Cohen, D., Weisz, J. R., et al. (2015) · BMJ Open · doi:10.1136/bmjopen-2015-008572 · Cited by 10
Du, H., Bo, L., Lai, X., Zhu, H., & Huo, X. (2023) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2023.1095996 · Cited by 10
Arnardóttir, A., & Skarphedinsson, G. (2023) · Nordic Journal of Psychiatry · doi:10.1080/08039488.2022.2069858 · Cited by 9
Salanti, G., & Higgins, J. P. T. (2022) · Systematic Reviews in Health Research · doi:10.1002/9781119099369.ch13
Metadata
- Authors
- Lu, G., & Ades, A. E.
- Venue
- Statistics in Medicine
- Publisher
- Wiley
- Published
- 2004-09-24
- Volume
- 23
- Issue
- 20
- Pages
- 3105-3124
- ISSN
- 0277-6715 (ISSN-L)
- 1097-0258
- OpenAlex
- W2113144077
- Cited by
- 2,166
- References
- 5
- FWCI
- 14.26
- Type
- journal article
- Language
- en
- Open access
- closed
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