what is NMA, Assumptions for choosing model, softwares used

1. Network meta analysis
Presented By : Nitisha Thakur
Clinical Research Unit, Department of Pharmacy Practice,
National Institute of Pharmaceutical Education and Research,
SAS Nagar, Punjab

2. Network meta analysis
 Network meta-analysis, in the context of a systematic
review, is a meta-analysis in which multiple treatments are being
compared using both direct comparisons of interventions within
RCTs & indirect comparisons across trials based on a common
Comparator

3. Direct comparison
A synthesis and comparison of the relative efficacy of two
interventions that have been compared in (head-to-head)
randomised controlled trials
Indirect comparison
A synthesis and comparison of the relative effect of two
interventions that have not been directly compared in randomised
controlled trials
Multiple treatment comparison
A synthesis and comparison of direct evidence with indirect
evidence

4. Importance of NMA

5.  NMA synthesizes direct & indirect evidence in network of trials
that compare multiple interventions
 Enables drawing influence for treatment comparisons never
appeared in individual studies
 Provide an estimate of treatment relative ranking according to
studied outcome

6. Assumption
1) Similarity
 Combining studies should only be considered if they are clinically
and methodologically similar
 T he PICOS framework can be used to identify these variables

7. QUALITATIVE ASSESSMENT OF SIMILARITY
Study quality scales and checklists can help assess similarity
1) JADAD
2) Quality checklist templates for clinical studies and reviews

8. JADAD scale

10. Quality checklist templates for clinical studies and reviews
The checklist was developed by listing the most
commonly used assessment criteria for clinical
studies. To assess the categories of biases selection,
performance, attrition and detection bias

12. 2) HOMOGENEITY
 Refers to the equivalence of trials within each pairwise
comparison in the network.
A
B C

13. Heterogeneity
There are three types of heterogeneity:
1) statistical heterogeneity,
2) methodological heterogeneity
3) clinical heterogeneity

14. TEST FOR HETEROGENEITY
 Cochran Q-statistic
1) calculated as the weighted sum of squared differences between
individual study effects and the pooled effect across studies2)It has
low power to detect heterogeneity when the number of studies is
small or studies themselves have small sample size
 I2 statistic
1) The I² statistic describes the percentage of variation across
studies that is due to heterogeneity. I² is an intuitive and simple
expression of the inconsistency of studies’ results

15. WHAT TO DO IN PRESENCE OF HETEROGENEITY?
Heterogeneity is an indication of dissimilarity in some effect-modifying
factor
 In presence of heterogeneity, the first task should be to thoroughly
explore and compare patient and trial characteristics across the studies
 This should be already done as part of similarity testing
 If systematic differences are detected, then following methods could be
considered:
1.Sub-group analyses
2.Random-effects modelling
3.Meta-regression (depends on data availability

16. 3) Consistency
 Statistical manifestation of transitivity
 The consistency assumption states that direct and
indirect evidence should be in agreement

17. METHODS TO TEST FOR INCONSISTENCY
1)Node-splitting
 Direct and indirect studies are separated and a difference in
estimates is calculated
 Repeated for all treatment comparisons where inconsistency is
possible
2) Bucher method
 Measure of inconsistency is the difference between direct and
indirect estimates
 Statistically test whether inconsistency is present
 Must repeat these steps for each independent loop in the network

18. Software used for NMA
1) Addis software
2) Win bugs
3) Net MetaXL
4) RevMAn