Ge, Long, Tian, Jin-hui, Li, Xiu-xia, Song, Fujian, Li, Lun, Zhang, Jun, Li, Ge, Pei, Gai-qin, Qiu, Xia and Yang, Ke-hu (2016) Epidemiology characteristics, methodological assessment and reporting of statistical analysis of network meta-analyses in the field of cancer. Scientific Reports, 6. ISSN 2045-2322
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Abstract
Because of the methodological complexity of network meta-analyses (NMAs), NMAs may be more vulnerable to methodological risks than conventional pair-wise meta-analysis. Our study aims to investigate epidemiology characteristics, conduction of literature search, methodological quality and reporting of statistical analysis process in the field of cancer based on PRISMA extension statement and modified AMSTAR checklist. We identified and included 102 NMAs in the field of cancer. 61 NMAs were conducted using a Bayesian framework. Of them, more than half of NMAs did not report assessment of convergence (60.66%). Inconsistency was assessed in 27.87% of NMAs. Assessment of heterogeneity in traditional meta-analyses was more common (42.62%) than in NMAs (6.56%). Most of NMAs did not report assessment of similarity (86.89%) and did not used GRADE tool to assess quality of evidence (95.08%). 43 NMAs were adjusted indirect comparisons, the methods used were described in 53.49% NMAs. Only 4.65% NMAs described the details of handling of multi group trials and 6.98% described the methods of similarity assessment. The median total AMSTAR-score was 8.00 (IQR: 6.00-8.25). Methodological quality and reporting of statistical analysis did not substantially differ by selected general characteristics. Overall, the quality of NMAs in the field of cancer was generally acceptable.
Item Type: | Article |
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Additional Information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
Uncontrolled Keywords: | sdg 3 - good health and well-being ,/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being |
Faculty \ School: | Faculty of Medicine and Health Sciences > Norwich Medical School |
UEA Research Groups: | Faculty of Medicine and Health Sciences > Research Groups > Epidemiology and Public Health Faculty of Medicine and Health Sciences > Research Groups > Health Services and Primary Care Faculty of Medicine and Health Sciences > Research Groups > Public Health and Health Services Research (former - to 2023) Faculty of Medicine and Health Sciences > Research Centres > Population Health |
Depositing User: | Pure Connector |
Date Deposited: | 01 Dec 2016 00:04 |
Last Modified: | 11 Oct 2024 00:02 |
URI: | https://ueaeprints.uea.ac.uk/id/eprint/61567 |
DOI: | 10.1038/srep37208 |
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