RISCA (version 1.0.7)

dataKi67: The Aggregated Data Published By de Azambuja et al. (2007).

Description

The aggregated data from the meta-analysis proposed by Azambuja et al. (2007).

Usage

data(dataKi67)

Format

A data frame with 406 observations (rows) with the 10 following variables (columns).

classe

This numeric vector represents the groups of patients defined using KI-67. 1 is the first group which is defined by the lowest KI-67 values.

n

This numeric vector represents the number of recipients at the baseline (date of KI-67 collection) in each group.

year

This numeric vector represents the survival time (in years).

surv

This numeric vector represents the survival probabilities at each year (obtained using the Kaplan and Meier estimator from the published papers).

nrisk

This numeric vector represents the number of subjects at-risk of the event at the corresponding year.

proba

This numeric vector represents the proportion of the patients for a given paper which belong to the corresponding group.

log.marker.min

This numeric vector represents the logarithm of the minimum value of the KI-67 interval.

log.marker.max

This numeric vector represents the logarithm of the maximum value of the KI-67 interval.

study.num

This numeric vector identifies the studies.

author

This character vector identifies the first author of the paper.

year.paper

This numeric vector identifies the year of publication.

Details

KI-67 is a marker of the proliferative activity of breast cancer, but its prognostic capacity is still unclear. In their meta-analysis, de Azambuja et al. (2007) concluded that KI-67 positivity conferred a worse survival. This work focused on the 35 evaluable studies of the relationship between KI-67 and the overall survival. 23 studies described survival curves according to the level of KI-67. Survival probabilities were measured every year.

References

de Azambuja et al. Ki-67 as prognostic marker in early breast cancer: a meta-analysis of published studies involving 12 155 patients. British Journal of Cancer. 96:1504-1513, 2007. <doi: 10.1038/ sj.bjc.6603756>

Examples

data(dataKi67)

# Kaplan Meier estimations of graft survivals in Wintzer et al. (1991)
plot(dataKi67$year[dataKi67$study.num==1],
 dataKi67$surv[dataKi67$study.num==1],
 xlab="Post transplantation time (years)",
 ylab="Graft survival", ylim=c(0.6,1), xlim=c(0, 4), type="n")

# Goup 1
lines(c(0, dataKi67$year[dataKi67$study.num==1 & dataKi67$classe==1]),
 c(1, dataKi67$surv[dataKi67$study.num==1 & dataKi67$classe==1]),
 type="b", col=1, lty=1, lwd=2)

# Goup 2
lines(c(0, dataKi67$year[dataKi67$study.num==1 & dataKi67$classe==2]),
 c(1, dataKi67$surv[dataKi67$study.num==1 & dataKi67$classe==2]),
 type="b", col=2, lty=2, lwd=2)

# legend
legend("bottomleft", c("group #1 (log Ki67 < 2.49)",
 "group #2 (log Ki67 > 2.49)"), col=c(1, 2), lty=c(1, 2), lwd=c(2, 2))