dat.begg1989 | R Documentation |
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 rates |
sei | numeric | corresponding standard errors |
vi | numeric | corresponding sampling variances |
The dataset includes the results from controlled and uncontrolled studies on the 2-year disease-free survival rate 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 and Pilote (1991, p. 902).
medicine, oncology, single-arm studies, multilevel models
Wolfgang Viechtbauer, wvb@metafor-project.org, https://www.metafor-project.org
Begg, C. B., & Pilote, L. (1991). A model for incorporating historical controls into a meta-analysis. Biometrics, 47(3), 899–906. https://doi.org/10.2307/2532647
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(11), 1519–1523. https://doi.org/10.1016/0277-5379(89)90291-5
### copy data into 'dat' and examine data dat <- dat.begg1989 dat ## Not run: ### load metafor package library(metafor) ### 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 a 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 a 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) res ## End(Not run)
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