Studies on Bone-Marrow Transplantation versus Chemotherapy for the Treatment of Leukemia
Results from controlled and uncontrolled studies on the effectiveness of allogeneic bone-marrow transplantation (BMT) and conventional chemotherapy (CMO) in the treatment of acute nonlymphocytic leukemia.
dat.begg1989
The data frame contains the following columns:
| study | numeric |
study number |
| trt | character |
treatment (BMT or CMO) |
| arms | numeric |
number of arms in the study (1 = uncontrolled studies; 2 = controlled studies) |
| yi | numeric |
2-year disease-free survival |
| sei | numeric |
corresponding standard error |
| vi | numeric |
corresponding sampling variance |
The dataset includes the results from controlled and uncontrolled studies on the 2-year disease-free survival in patients with acute nonlymphocytic leukemia receiving either allogeneic bone-marrow transplantation (BMT) or conventional chemotherapy (CMO). In the controlled (two-arm) studies (studies 1-4), a cohort of patients in complete remission and potentially eligible for BMT was assembled, and those who consented and for whom a donor could be found received BMT, with the remaining patients used as controls (receiving CMO). In the uncontrolled (one-arm) studies (studies 5-16), only a single group was studied, receiving either BMT or CMO.
The data in this dataset were obtained from Table 1 in Begg & Pilote (1991, p. 902).
Begg, C. B., & Pilote, L. (1991). A model for incorporating historical controls into a meta-analysis. Biometrics, 47, 899–906.
Begg, C. B., Pilote, L., & McGlave, P. B. (1989). Bone marrow transplantation versus chemotherapy in acute non-lymphocytic leukemia: A meta-analytic review. European Journal of Cancer and Clinical Oncology, 25, 1519–1523.
### copy data into 'dat' and examine data
dat <- dat.begg1989
dat
### turn trt and arms into factors and set reference levels
dat$trt <- relevel(factor(dat$trt), ref="CMO")
dat$arms <- relevel(factor(dat$arms), ref="2")
### create data frame with the treatment differences for the controlled studies
dat2 <- data.frame(yi = dat$yi[c(1,3,5,7)] - dat$yi[c(2,4,6,8)],
vi = dat$vi[c(1,3,5,7)] + dat$vi[c(2,4,6,8)])
dat2
### DerSimonian and Laird method using the treatment differences
res <- rma(yi, vi, data=dat2, method="DL", digits=2)
res
### Begg & Pilote (1991) model incorporating the uncontrolled studies
res <- rma.mv(yi, vi, mods = ~ trt, random = ~ 1 | study,
data=dat, method="ML", digits=2)
res
### model involving bias terms for the uncontrolled studies
res <- rma.mv(yi, vi, mods = ~ trt + trt:arms, random = ~ 1 | study,
data=dat, method="ML", digits=2)
res
### model with random treatment effect
res <- rma.mv(yi, vi, mods = ~ trt, random = list(~ 1 | study, ~ trt | study),
struct="UN", tau2=c(0,NA), rho=0, data=dat, method="ML", digits=2)
res
### model with random treatment effect, but with equal variances in both arms
res <- rma.mv(yi, vi, mods = ~ trt, random = list(~ 1 | study, ~ trt | study),
struct="CS", rho=0, data=dat, method="ML", digits=2)
resPlease choose more modern alternatives, such as Google Chrome or Mozilla Firefox.