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Table 2 Properties of methods to derive indirect and network meta-analysis estimates using individual patient data

From: A scoping review of indirect comparison methods and applications using individual patient data

  Adjusted indirect comparison (or Bucher method) Mixed comparison Meta-regression model Bayesian hierarchical NMA model MAIC [48] STC [49]
No. of empirical studies applying method (n = 33) 2 (6 %) [20, 52] 1 (3 %) [28] 4 (12 %) [19, 21, 25, 26] 17 (52 %) [6, 10, 18, 2224, 27, 2933, 4245, 51] 8 (24 %) MAICs [3438, 48, 57] and 1 (3 %) extended MAIC [46] 0 (0 %)
Properties
1-stage or 2-stage process 2-stage 2-stage Both can be applied Both can be applied NA NA
Format of data IPD+AD/IPD only IPD+AD/IPD only IPD+AD/IPD only IPD+AD/IPD only IPD+AD IPD+AD
Avoids selective use of indirect evidence from a network of trials No No Yes Yes No No
Can compare >2 treatments at a time for efficacy/safety No No Yes Yes No No
Preserves within-trial randomization Yes Yes Yes Yes No No
Study-specific true treatment effects can be assumed as fixed or random with common mean effect for each pairwise comparison Yes Yes Yes Yes No No
May account for potential clinical and methodological differences across trials Yes Yes Yes Yes No No
Does not require assessment for transitivity assumption No No No No Yes Yes
Mean treatment effects expressed via consistency equations No Yes Yes Yes No No
Can rank all competing treatments for same condition No No Yes Yes No No
Enables adjustment for predefined set of patient characteristics No No Yes Yes Yes Yes
Can be applied even in disconnected network of trials No No No No Yes Yes
  1. AD aggregated data, IPD individual patient data, MAIC matching adjusted indirect comparison, NA not applicable, NMA network meta-analysis, STC simulated treatment comparison