dat.stowe2010 | R Documentation |
Results from 29 trials assessing efficacy of three drug classes as adjuvant treatment to levodopa therapy in patients with Parkinson disease and motor complications.
dat.stowe2010
The data frame contains the following columns:
study | character | study label |
id | integer | study id |
t1 | character | treatment 1 |
y1 | numeric | treatment effect arm 1 |
sd1 | numeric | standard deviation arm 1 |
n1 | integer | sample size arm 1 |
t2 | character | treatment 2 |
y2 | numeric | treatment effect arm 2 |
sd2 | numeric | standard deviation arm 2 |
n2 | integer | sample size arm 2 |
t3 | character | treatment 3 |
y3 | numeric | treatment effect arm 3 |
sd3 | numeric | standard deviation arm 3 |
n3 | integer | sample size arm 3 |
This data set contains data from a Cochrane review assessing efficacy and safety of three drug classes as adjuvant treatment to levodopa therapy in patients with Parkinson disease and motor complications (Stowe et al., 2010).
The authors conducted three pairwise meta-analyses comparing dopamine agonists, catechol-O-methyl transferase inhibitors (COMTI), and monoamine oxidase type B inhibitors (MAOBI) with placebo. The primary outcome was the mean reduction of the time spent in a relatively immobile ‘off’ phase (mean off-time), calculated in hours per day. Relative treatment effects were expressed as mean difference. Data on this outcome were available for 5,331 patients from 28 studies comparing an active treatment with placebo and one three-arm study comparing two active treatments with placebo.
medicine, raw mean differences, network meta-analysis
Guido Schwarzer, sc@imbi.uni-freiburg.de, https://github.com/guido-s/
Stowe, R., Ives, N., Clarke, C. E., Deane, K., Hilten, V., Wheatley, K., Gray, R., Handley, K., & Furmston, A. (2010). Evaluation of the efficacy and safety of adjuvant treatment to levodopa therapy in Parkinson's disease patients with motor complications. Cochrane Database of Systematic Reviews, 7, CD007166. https://doi.org/10.1002/14651858.CD007166.pub2
pairwise
, metacont
, netmeta
, netrank
, rankogram
, netleague
### Show results from three studies (including three-arm study LARGO) dat.stowe2010[18:20, ] ## Not run: ### Load netmeta package suppressPackageStartupMessages(library(netmeta)) ### Print mean differences with two digits and standard errors with 3 ### digits settings.meta(digits = 2, digits.se = 3) ### Transform data from wide arm-based format to contrast-based ### format. Argument 'sm' must not be provided as the mean difference ### is the default in R function metacont() called internally. pw <- pairwise(treat = list(t1, t2, t3), n = list(n1, n2, n3), mean = list(y1, y2, y3), sd = list(sd1, sd2, sd3), studlab = study, data = dat.stowe2010, sm = "MD") ### Show calculated mean differences (TE) for three studies selstudy <- c("COMTI(E) INT-OZ", "LARGO", "COMTI(E) Nomecomt") subset(pw, studlab %in% selstudy)[, c(3:7, 10, 1)] ### Conduct random effects network meta-analysis (NMA) ### with placebo as reference net <- netmeta(pw, fixed = FALSE, ref = "plac") ### Show network graph netgraph(net, number = TRUE, multiarm = TRUE, cex = 1.25, offset = 0.025, cex.number = 1, pos.number.of.studies = 0.3) ### Print NMA results net ### Forest plot with NMA results forest(net) ### Forest plot showing all network estimates of active treatments ### compared with other treatments forest(net, ref = c("C", "D", "M"), baseline = FALSE, drop = TRUE) ### Treatment ranking using P-scores netrank(net) ### Rankogram with all ranking probabilities set.seed(1909) ran <- rankogram(net) ran plot(ran) ### Treatment ranking using SUCRAs netrank(ran) ### League table showing network and direct estimates netleague(net, seq = netrank(net), ci = FALSE) ## End(Not run)
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