Gupta2013: Network meta-analysis comparing interventions for actinic...

In NMAoutlier: Detecting Outliers in Network Meta-Analysis

Description

Network meta-analysis dataset for comparing interventions for actinic keratosis.

Format

A data frame in contrast format with the following columns:

logOR	log odds ratio
selogOR	standard error of log odds ratio
id	study ID
t1	first treatment
t2	second treatment

Details

The dataset compares the relative effects of nine interventions:

• placebo / vehicle (including placebo-PDT) (treatment 1),

• diclofenac 3 percent in 2.5 percent hyaluronic acid (DCF/HA) (treatment 2),

• 5-fluorouracil (5-FU) 0.5 percent (treatment 3),

• imiquimod (IMI) 5 percent (treatment 4),

• methyl aminolaevulinate (MAL)-PDT (treatment 5),

• 5-aminolaevulinic acid (ALA)-photodynamic therapy (PDT) (treatment 6),

• 5-fluorouracil (5-FU) 5.0 percent (treatment 7),

• cryotherapy (treatment 8),

• ingenol mebutate (IMB) 0.015-0.05 percent (treatment 9).

The outcome is the number of individuals with participant complete clearance or equivalent efficacy. These data are in contrast format with effect size the odds ratio (OR). The arm-level data were used in Gupta and Paquet (2013).

Source

Gupta AK, Paquet M (2013): Network meta-analysis of the outcome participant complete clearance in nonimmunosuppressed participants of eight interventions for actinic keratosis: a follow-up on a Cochrane review. British Journal of Dermatology, 169, 250–9

Examples

data(Gupta2013)
# Conduct forward search algorithm for the network of actinic keratosis
#
FSresult <- NMAoutlier(logOR, selogOR, t1, t2, id, data = Gupta2013, n_cores = 2)

# Plovide the forward plot for z-values from difference of direct and
# indirect evidence
#
fwdplot(FSresult, "nsplit")

# Provide forward plot for Q statistic
#
fwdplot(FSresult, "Q")

NMAoutlier documentation built on Oct. 11, 2021, 5:23 p.m.