DLBCL {maxstat}R Documentation

Diffuse large B-cell lymphoma

Description

A data frame with gene expression data from DLBCL (diffuse large B-cell lymphoma) patients.

Usage

data(DLBCL)

Format

DLCLid
DLCL identifier
GEG
Gene Expression Group
time
survival time in month
cens
censoring: 0 cencored, 1 dead
IPI
International Prognostic Index
MGE
Mean Gene Expression

Except of MGE, the data is published at http://llmpp.nih.gov/lymphoma/data.shtml. MGE was computed by Berthold Lausen.

Source

Ash A. Alizadeh et. al (2000), Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature, 403, 504–509

References

Lausen, B. and Schumacher, M. (1992), Maximally Selected Rank Statistics. Biometrics 48, 73–85

Examples


data(DLBCL)

# remove NA's

DLBCL <- DLBCL[!is.na(DLBCL$time),]

# compute the cutpoint

postscript("statDLBCL.ps",horizontal=F, width=8, height=8)
par(mai=c(1.0196235, 1.0196235, 0.8196973, 0.4198450))

mod <- maxstat.test(DLBCL$MGE, DLBCL$time,
             cens=DLBCL$cens, smethod="LogRank", plot=T, cex.lab=1.6,
             cex.axis=1.6, xlab="Mean gene expression")

dev.off()

# significance of the cutpoint
# Limiting distribution

maxstat.test(DLBCL$MGE, DLBCL$time,
             cens=DLBCL$cens, smethod="LogRank", pmethod="Lau92")

# improved Bonferroni inequality

maxstat.test(DLBCL$MGE, DLBCL$time,
             cens=DLBCL$cens, smethod="LogRank", pmethod="Lau94")

# small sample solution Hothorn & Lausen (2001)

maxstat.test(DLBCL$MGE, DLBCL$time,
             cens=DLBCL$cens, smethod="LogRank", pmethod="HL")

maxstat.test(DLBCL$MGE, DLBCL$time,
             cens=DLBCL$cens, smethod="LogRank", pmethod="exactGauss")

# Nature article survival analysis

splitGEG <- rep(1, nrow(DLBCL))
DLBCL <- cbind(DLBCL, splitGEG)
DLBCL$splitGEG[DLBCL$GEG == "Activated B-like"] <- 0

plot(survfit(Surv(time, cens) ~ splitGEG, data=DLBCL),
     xlab="Survival time in month", ylab="Probability")

text(90, 0.7, "GC B-like")
text(60, 0.3, "Activated B-like")

splitIPI <- rep(1, nrow(DLBCL))
DLBCL <- cbind(DLBCL, splitIPI)
DLBCL$splitIPI[DLBCL$IPI <= 2] <- 0

plot(survfit(Surv(time, cens) ~ splitIPI, data=DLBCL),
     xlab="Survival time in month", ylab="Probability")

text(90, 0.7, "Low clinical risk")
text(60, 0.25, "High clinical risk")

# survival analysis using the cutpoint 

splitMGE <- rep(1, nrow(DLBCL))
DLBCL <- cbind(DLBCL, splitMGE)
DLBCL$splitMGE[DLBCL$MGE <= mod$estimate] <- 0

postscript("survDLBCL.ps",horizontal=F, width=8, height=8)
par(mai=c(1.0196235, 1.0196235, 0.8196973, 0.4198450))

plot(survfit(Surv(time, cens) ~ splitMGE, data=DLBCL),
xlab = "Survival time in month",
ylab="Probability", cex.lab=1.6, cex.axis=1.6)

text(90, 0.9, expression("Mean gene expression" > 0.186), cex=1.6)   
text(90, 0.45, expression("Mean gene expression" <= 0.186 ), cex=1.6)   

dev.off()