Results from 33 trials comparing intravenous streptokinase versus placebo or no therapy in patients who had been hospitalized for acute myocardial infarction.

dat.lau1992

Format

The data frame contains the following columns:

trialcharactertrial name
yearnumericpublication year
ainumericnumber of deaths in the streptokinase group
n1inumericnumber of patients in the streptokinase group
cinumericnumber of deaths in the control group
n2inumericnumber of patients in the control group

Details

In the paper by Lau et al. (1992), the data are used to illustrate the idea of a cumulative meta-analysis, where the results are updated as each trial is added to the dataset. See ‘Examples’ for code that replicates the results and shows corresponding forest plots.

Source

Lau, J., Antman, E. M., Jimenez-Silva, J., Kupelnick, B., Mosteller, F., & Chalmers, T. C. (1992). Cumulative meta-analysis of therapeutic trials for myocardial infarction. New England Journal of Medicine, 327(4), 248–254. https://doi.org/10.1056/NEJM199207233270406

Concepts

medicine, cardiology, odds ratios, cumulative meta-analysis

Examples

### copy data into 'dat' and examine data
dat <- dat.lau1992
dat
#>           trial year  ai  n1i   ci  n2i
#> 1      Fletcher 1959   1   12    4   11
#> 2         Dewar 1963   4   21    7   21
#> 3    European 1 1969  20   83   15   84
#> 4    European 2 1971  69  373   94  357
#> 5   Heikinheimo 1971  22  219   17  207
#> 6       Italian 1971  19  164   18  157
#> 7  Australian 1 1973  26  264   32  253
#> 8   Frankfurt 2 1973  13  102   29  104
#> 9    NHLBI SMIT 1974   7   53    3   54
#> 10        Frank 1975   6   55    6   53
#> 11       Valere 1975  11   49    9   42
#> 12        Klein 1976   4   14    1    9
#> 13    UK Collab 1976  38  302   40  293
#> 14     Austrian 1977  37  352   65  376
#> 15 Australian 2 1977  25  123   31  107
#> 16     Lasierra 1977   1   13    3   11
#> 17 N Ger Collab 1977  63  249   51  234
#> 18     Witchitz 1977   5   32    5   26
#> 19   European 3 1979  18  156   30  159
#> 20         ISAM 1986  54  859   63  882
#> 21      GISSI-1 1986 628 5860  758 5852
#> 22        Olson 1986   1   28    2   24
#> 23     Baroffio 1986   0   29    6   30
#> 24    Schreiber 1986   1   19    3   19
#> 25      Cribier 1986   1   21    1   23
#> 26     Sainsous 1986   3   49    6   49
#> 27       Durand 1987   3   35    4   29
#> 28        White 1987   2  107   12  112
#> 29      Bassand 1987   4   52    7   55
#> 30         Vlay 1988   1   13    2   12
#> 31      Kennedy 1988  12  191   17  177
#> 32       ISIS-2 1988 791 8592 1029 8595
#> 33    Wisenberg 1988   2   41    5   25

# \dontrun{

### load metafor package
library(metafor)

### meta-analysis of log odds ratios using the MH method
res <- rma.mh(measure="OR", ai=ai, n1i=n1i, ci=ci, n2i=n2i, data=dat, slab=trial)
print(res, digits=2)
#> 
#> Equal-Effects Model (k = 33)
#> 
#> I^2 (total heterogeneity / total variability):  18.98%
#> H^2 (total variability / sampling variability): 1.23
#> 
#> Test for Heterogeneity: 
#> Q(df = 32) = 39.50, p-val = 0.17
#> 
#> Model Results (log scale):
#> 
#> estimate    se   zval  pval  ci.lb  ci.ub 
#>    -0.27  0.03  -8.16  <.01  -0.33  -0.20 
#> 
#> Model Results (OR scale):
#> 
#> estimate  ci.lb  ci.ub 
#>     0.76   0.72   0.82 
#> 
#> Cochran-Mantel-Haenszel Test:    CMH = 66.60, df = 1,  p-val < 0.01
#> Tarone's Test for Heterogeneity: X^2 = 43.84, df = 32, p-val = 0.08
#> 

### forest plot
forest(res, xlim=c(-10,9), atransf=exp, at=log(c(.01, 0.1, 1, 10, 100)),
       header=TRUE, top=2, ilab=dat$year, ilab.xpos=-6)
text(-6, 35, "Year", font=2)


### cumulative meta-analysis
sav <- cumul(res)

### forest plot of the cumulative results
forest(sav, xlim=c(-5,4), atransf=exp, at=log(c(0.1, 0.5, 1, 2, 10)),
       header=TRUE, top=2, ilab=dat$year, ilab.xpos=-3)
text(-3, 35, "Year", font=2)
id <- c(4, 8, 15, 33) # rows for which the z/p-values should be shown (as in Lau et al., 1992)
text(1.1, (res$k:1)[id], paste0("z = ", formatC(sav$zval[id], format="f", digits=2),
                                ", p = ", formatC(sav$pval[id], format="f", digits=4)))


# }