PRISMA-NMA Checklist
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PRISMA-NMA Checklist
Instructions
Use the boxes to confirm each reporting item.
Add reviewer notes under each section as needed.
Title
Abstract
Introduction
Methods
5. Protocol and
Registration: Indicate whether a review protocol exists
and if and where it can be accessed (e.g., Web address); and, if
available, provide registration information, including
registration number.
6. Eligibility
Criteria: Specify study characteristics (e.g., PICOS,
length of follow-up) and report characteristics (e.g., years
considered, language, publication status) used as criteria for
eligibility, giving rationale. Clearly describe eligible
treatments included in the treatment network, and note whether any
have been clustered or merged into the same node (with
justification).
7. Information
Sources: Describe all information sources (e.g.,
databases with dates of coverage, contact with study authors to
identify additional studies) in the search and date last
searched.
8. Search:
Present full electronic search strategy for at least one database,
including any limits used, such that it could be
repeated.
9. Study
Selection: State the process for selecting studies (i.e.,
screening, eligibility, included in systematic review, and, if
applicable, included in the meta-analysis).
10. Data Collection
Process: Describe method of data extraction from reports
(e.g., piloted forms, independently, in duplicate) and any
processes for obtaining and confirming data from
investigators.
11. Data
Items: List and define all variables for which data were
sought (e.g., PICOS, funding sources) and any assumptions and
simplifications made.
S1. Geometry of the
Network: Describe methods used to explore the geometry of
the treatment network under study and potential biases related to
it. This should include how the evidence base has been graphically
summarized for presentation, and what characteristics were
compiled and used to describe the evidence base to
readers.
12. Risk of Bias
within Individual Studies: Describe methods used for
assessing risk of bias of individual studies (including
specification of whether this was done at the study or outcome
level), and how this information is to be used in any data
synthesis.
13. Summary
Measures: State the principal summary measures (e.g.,
risk ratio, difference in means). Also describe the use of
additional summary measures assessed, such as treatment rankings
and surface under the cumulative ranking curve (SUCRA) values, as
well as modified approaches used to present summary findings from
meta-analyses.
14. Planned Methods of
Analysis: Describe the methods of handling data and
combining results of studies for each network meta-analysis. This
should include, but not be limited to:
Handling of multi-arm trials;
Selection of variance structure;
Selection of prior distributions in Bayesian analyses;
and
Assessment of model fit.
S2. Assessment of
Inconsistency: Describe the statistical methods used to
evaluate the agreement of direct and indirect evidence in the
treatment network(s) studied. Describe efforts taken to address
its presence when found.
15. Risk of Bias
across Studies: Specify any assessment of risk of bias
that may affect the cumulative evidence (e.g., publication bias,
selective reporting within studies).
16. Additional
Analyses: Describe methods of additional analyses if
done, indicating which were pre-specified. This may include, but
not be limited to, the following:
Sensitivity or subgroup analyses;
Meta-regression analyses;
Alternative formulations of the treatment network;
Use of alternative prior distributions for Bayesian analyses
(if applicable).
Results
17. Study
Selection: Give numbers of studies screened, assessed for
eligibility, and included in the review, with reasons for
exclusions at each stage, ideally with a flow
diagram.
S3. Presentation of
Network Structure: Provide a network graph of the
included studies to enable visualization of the geometry of the
treatment network.
S4. Summary of Network
Geometry: Provide a brief overview of characteristics of
the treatment network. This may include commentary on the
abundance of trials and randomized patients for the different
interventions and pairwise comparisons in the network, gaps of
evidence in the treatment network, and potential biases reflected
by the network structure.
18. Study
Characteristics: For each study, present characteristics
for which data were extracted (e.g., study size, PICOS, follow-up
period) and provide the citations.
19. Risk of Bias
within Studies: Present data on risk of bias of each
study and, if available, any outcome level
assessment.
20. Results of
Individual Studies: For all outcomes considered (benefits
or harms), present, for each study: 1) simple summary data for
each intervention group, and 2) effect estimates and confidence
intervals. Modified approaches may be needed to deal with
information from larger networks.
21. Synthesis of
Results: Present results of each meta-analysis done,
including confidence/credible intervals. In larger networks,
authors may focus on comparisons versus a particular comparator
(e.g. placebo or standard care), with full findings presented in
an appendix. League tables and forest plots may be considered to
summarize pairwise comparisons. If additional summary measures
were explored (such as treatment rankings), these should also be
presented.
S5. Exploration for
Inconsistency: Describe results from investigations of
inconsistency. This may include such information as measures of
model fit to compare consistency and inconsistency models, P
values from statistical tests, or summary of inconsistency
estimates from different parts of the treatment
network.
22. Risk of Bias
across Studies: Present results of any assessment of risk
of bias across studies for the evidence base being
studied.
23. Results of
Additional Analyses: Give results of additional analyses,
if done (e.g., sensitivity or subgroup analyses, meta-regression
analyses, alternative network geometries studied, alternative
choice of prior distributions for Bayesian analyses, and so
forth).
Discussion
24. Summary of
Evidence: Summarize the main findings, including the
strength of evidence for each main outcome; consider their
relevance to key groups (e.g., healthcare providers, users, and
policy-makers).
25.
Limitations: Discuss limitations at study and outcome
level (e.g., risk of bias), and at review level (e.g., incomplete
retrieval of identified research, reporting bias). Comment on the
validity of the assumptions, such as transitivity and consistency.
Comment on any concerns regarding network geometry (e.g.,
avoidance of certain comparisons).
26.
Conclusions: Provide a general interpretation of the
results in the context of other evidence, and implications for
future research.
Funding
Notes
Reviewer notes
Provenance
Source: See sidecar metadata in
source/variants/prisma-nma.yml
Version: 2015
License: CC-BY-4.0
Generated by the standards_check project.