Linde2015: Network meta-analysis of treatments for depression

In netmeta: Network Meta-Analysis using Frequentist Methods

Network meta-analysis of treatments for depression

Description

Network meta-analysis of nine classes of antidepressants including placebo for the primary care setting; partly shown in Linde et al. (2015), supplementary Table 2.

Format

A data frame with the following columns:

id	Study ID
author	First author
year	Publication year
treatment1	First treatment
treatment2	Second treatment
treatment3	Third treatment
n1	Number of patients receiving first treatment
resp1	Number of early responder (treatment 1)
remi1	Number of early remissions (treatment 1)
loss1	Number of patients loss to follow-up (treatment 1)
loss.ae1	Number of patients loss to follow-up due to adverse events (treatment 1)
ae1	Number of patients with adverse events (treatment 1)
n2	Number of patients receiving second treatment
resp2	Number of early responder (treatment 2)
remi2	Number of early remissions (treatment 2)
loss2	Number of patients loss to follow-up (treatment 2)
loss.ae2	Number of patients loss to follow-up due to adverse events (treatment 2)
ae2	Number of patients with adverse events (treatment 2)
n3	Number of patients receiving third treatment
resp3	Number of early responder (treatment 3)
remi3	Number of early remissions (treatment 3)
loss3	Number of patients loss to follow-up (treatment 3)
loss.ae3	Number of patients loss to follow-up due to adverse events (treatment 3)
ae3	Number of patients with adverse events (treatment 3)

Note

The dataset Linde2015 is identical to dataset dat.linde2015 in R package metadat.

Source

Linde K, Kriston L, Rücker G, et al. (2015): Efficacy and acceptability of pharmacological treatments for depressive disorders in primary care: Systematic review and network meta-analysis. Annals of Family Medicine, 13, 69–79

See Also

dat.dong2013, pairwise, metabin, netmeta, netposet

Examples

head(dat.linde2015)


# Transform data from arm-based format to contrast-based format
# Outcome: early response
pw1 <- pairwise(list(treatment1, treatment2, treatment3),
  event = list(resp1, resp2, resp3),
  n = list(n1, n2, n3),
  studlab = id, data = dat.linde2015, sm = "OR")
pw1

# Define order of treatments
trts <- c("TCA", "SSRI", "SNRI", "NRI", "Low-dose SARI",
  "NaSSa", "rMAO-A", "Hypericum", "Placebo")

# Conduct random effects network meta-analysis
net1 <- netmeta(pw1, common = FALSE, reference = "Placebo", seq = trts)
print(net1, digits = 2)

netmeta documentation built on April 3, 2025, 6:12 p.m.