Peto1980: Aspirin after myocardial infarction example data
In bayesmeta: Bayesian Random-Effects Meta-Analysis and Meta-Regression

Peto1980

R Documentation

Aspirin after myocardial infarction example data

Description

Numbers of cases (patients) and events (deaths) in treatment and control groups of six studies.

Usage

data("Peto1980")

Format

The data frame contains the following columns:

publication	`character`	publication reference
study	`character`	study acronym or abbreviation
start, end	`integer`	duration of study (calendar years)
age	`numeric`	mean patient age (years)
dose	`numeric`	total daily dose (mg)
followup	`numeric`	follow-up duration (months)
treat.cases	`integer`	number of cases in treatment group
treat.events	`integer`	number of events in treatment group
control.cases	`integer`	number of cases in control group
control.events	`integer`	number of events in control group

Details

Peto (1980) investigated mortality data from six randomized, placebo-controlled clinical trials of aspirin, involving a total of 10,703 post-myocardial infarction patients. Canner (1987) later investigated potential heterogeneity between study characteristics as well as their reported estimates. The included studies' abbreviations are:

UK-1	first United Kingdom trial
CDPA	Coronary Drug Project Aspirin trial
GAMS	German-Austrian Multicentre Study
UK-2	second United Kingdom trial
PARIS	Persantine-Aspirin Reinfarction Study
AMIS	Aspirin Myocardial Infarction Study

Source

P.L. Canner. An overview of six clinical trials of aspirin in coronary heart disease. Statistics in Medicine, 6(3):255-263, 1987. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1002/sim.4780060310")}

References

R. Peto. Aspirin after myocardial infarction. The Lancet, 315(8179):1172-1173, 1980. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/S0140-6736(80)91626-8")}.

P.C. Elwood, A.L. Cochrane, M.L.Burr, P.M. Sweetnam, G. Williams, E. Welsby, S.J. Hughes, R. Renton. A randomized controlled trial of acetyl salicylic acid in the secondary prevention of mortality from myocardial infarction. British Medical Journal, 1(5905):436-440, 1974. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1136/bmj.1.5905.436")}.

The Coronary Drug Project Research Group. Aspirin in coronary heart disease. Journal of Chronic Diseases, 29(10):625-642, 1976. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/0021-9681(76)90020-5")}.

K. Breddin, D. Loew, K. Lechner, K. Ueberla, E. Walter. Secondary prevention of myocardial infarction: a comparison of acetylsalicylic acid, placebo and phenprocoumon. Haemostasis, 9(6):325-344, 1980. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1159/000214375")}.

P.C. Elwood, P.M. Sweetnam. Aspirin and secondary mortality after myocardial infarction. The Lancet, 314(8156):1313-1315, 1979. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/S0140-6736(79)92808-3")}.

Aspirin Myocardial Infarction Study Research Group. A randomized, controlled trial of aspirin in persons recovered from myocardial infarction. Journal of the American Medical Association, 243(7):661-669, 1980. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1001/jama.1980.03300330019023")}.

The Persantine-Aspirin Reinfarction Study Research Group. Persantine and aspirin in coronary heart disease. Circulation, 62(3):449-461, 1980. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1161/01.CIR.62.3.449")}.

Examples

data("Peto1980")
## Not run: 
# compute effect sizes (log odds ratios) from count data
# (using "metafor" package's "escalc()" function):
require("metafor")
peto.es <- escalc(measure="OR",
                  ai=treat.events,   n1i=treat.cases,
                  ci=control.events, n2i=control.cases,
                  slab=publication, data=Peto1980)
print(peto.es)

# check sensitivity to different prior choices:
peto.ma01 <- bayesmeta(peto.es)
peto.ma02 <- bayesmeta(peto.es, tau.prior=function(t){dhalfnormal(t, scale=1)})
 
par(mfrow=c(2,1))
  plot(peto.ma01, which=4, prior=TRUE, taulim=c(0,1), main="uniform prior")
  plot(peto.ma02, which=4, prior=TRUE, taulim=c(0,1), main="half-normal prior")
par(mfrow=c(1,1))

# compare heterogeneity (tau) estimates:
print(rbind("uniform"    =peto.ma01$summary[,"tau"],
            "half-normal"=peto.ma02$summary[,"tau"]))

# compare effect (mu) estimates:
print(rbind("uniform"    =peto.ma01$summary[,"mu"],
            "half-normal"=peto.ma02$summary[,"mu"]))

summary(peto.ma02)
forestplot(peto.ma02)
plot(peto.ma02)

## End(Not run)

bayesmeta documentation built on July 9, 2023, 5:12 p.m.