How to remove duplicated info from netmeta forest plot for NMA with all comparisons

I am doing NMA with netmeta package. Here is the example with publicly available dataset:

library(netmeta)
data("smokingcessation", package ='netmeta')

p1 <- pairwise(treat = list(treat1, treat2, treat3), event = list(event1, event2, event3),  n = list(n1, n2, n3), data = smokingcessation, sm = 'RD')
net <- netmeta(p1, common = TRUE, all.treatments = T, sm='RD', method.tau='REML')
forest(net, xlim=c(-0.1,0.1), pooled='common',
       reference.group = c('A', 'B', 'C', 'D'),
       drop.reference = T,
       sortvar = -TE,
) 

I got duplicated data on the plot. What I want is to have comparisons:

Other vs A:

• B
• C
• D

Other vs B:

• D
• C

Other vs C:

• D

One way is to assign an object to the plot, modify it, then use metagen from the meta package to generate the required object which you can pass to forest.

This is your code, which we assign to fp:

fp <- forest(net, 
       xlim=c(-0.1,0.1), pooled='common',
       reference.group = c('A','B','C','D'),
       drop.reference = TRUE, sortvar = -TE) 

It's a data frame:

fp

     comparison treat labels          TE        seTE Pscore SUCRA  k prop.direct n.trts
1  Other vs 'A'     D      D  0.05831001 0.019441217     NA    NA  2  0.44159097    555
2  Other vs 'A'     C      C  0.05280589 0.005317229     NA    NA 15  0.98197598   7383
3  Other vs 'A'     B      B  0.01043509 0.008396496     NA    NA  3  0.94657991   1571
4  Other vs 'B'     D      D  0.04787492 0.020346129     NA    NA  2  0.31528433    555
5  Other vs 'B'     C      C  0.04237080 0.009830423     NA    NA  2  0.04175929   7383
6  Other vs 'B'     A      A -0.01043509 0.008396496     NA    NA  3  0.94657991   7231
7  Other vs 'C'     D      D  0.00550412 0.019563970     NA    NA  4  0.57660148    555
8  Other vs 'C'     B      B -0.04237080 0.009830423     NA    NA  2  0.04175929   1571
9  Other vs 'C'     A      A -0.05280589 0.005317229     NA    NA 15  0.98197598   7231
10 Other vs 'D'     C      C -0.00550412 0.019563970     NA    NA  4  0.57660148   7383
11 Other vs 'D'     B      B -0.04787492 0.020346129     NA    NA  2  0.31528433   1571
12 Other vs 'D'     A      A -0.05831001 0.019441217     NA    NA  2  0.44159097   7231

We can drop the rows we don't want, make a minor edit to the labels, and create a new plot:

library(dplyr)

fp[-c(6,8:12),] |>
  rowwise() |>
  mutate(comparison=sub('Other', treat, comparison)) |>
  metagen(TE, seTE, comparison, data=_) |>
  forest() # common = FALSE, random=FALSE # omit "Weight" columns on right