DLBCL                package:maxstat                R Documentation

_D_i_f_f_u_s_e _l_a_r_g_e _B-_c_e_l_l _l_y_m_p_h_o_m_a

_D_e_s_c_r_i_p_t_i_o_n:

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

_U_s_a_g_e:

     data(DLBCL)

_F_o_r_m_a_t:

     '_D_L_C_L_i_d' DLBCL identifier

     '_G_E_G' Gene Expression Group

     '_t_i_m_e' survival time in month

     '_c_e_n_s' censoring: 0 cencored, 1 dead

     '_I_P_I' International Prognostic Index

     '_M_G_E' Mean Gene Expression

_S_o_u_r_c_e:

     Except of 'MGE', the data is published at <URL:
     http://llmpp.nih.gov/lymphoma/data.shtml>. 'MGE' is the mean of
     the gene expression.

_R_e_f_e_r_e_n_c_e_s:

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

_E_x_a_m_p_l_e_s:

     data(DLBCL)

     # compute the cutpoint and plot the empirical process 

     mod <- maxstat.test(Surv(time, cens) ~ MGE, data=DLBCL, smethod="LogRank")

     print(mod)

     ## Not run: 
       # postscript("statDLBCL.ps", horizontal=F, width=8, height=8)
       pdf("statDLBCL.pdf", width=8, height=8)
     ## End(Not run)
     par(mai=c(1.0196235, 1.0196235, 0.8196973, 0.4198450))
     plot(mod, cex.lab=1.6, cex.axis=1.6, xlab="Mean gene expression",lwd=2)
     ## Not run: 
       dev.off()
     ## End(Not run)

     # significance of the cutpoint
     # limiting distribution

     maxstat.test(Surv(time, cens) ~ MGE, data=DLBCL,
                  smethod="LogRank", pmethod="Lau92", iscores=TRUE)

     # improved Bonferroni inequality, plot with significance bound

     maxstat.test(Surv(time, cens) ~ MGE, data=DLBCL,
                  smethod="LogRank", pmethod="Lau94", iscores=TRUE)

     mod <- maxstat.test(Surv(time, cens) ~ MGE, data=DLBCL, smethod="LogRank",
                         pmethod="Lau94", alpha=0.05)
     plot(mod, xlab="Mean gene expression")

     ## Not run: 
     #  postscript(file="RNewsStat.ps",horizontal=F, width=8, height=8)
        pdf("RNewsStat.pdf", width=8, height=8)

     ## End(Not run)
     par(mai=c(1.0196235, 1.0196235, 0.8196973, 0.4198450))
     plot(mod, xlab="Mean gene expression", cex.lab=1.6, cex.axis=1.6)
     ## Not run: 
       dev.off()
     ## End(Not run)

     # small sample solution Hothorn & Lausen

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

     # normal approximation

     maxstat.test(Surv(time, cens) ~ MGE, data=DLBCL,
                  smethod="LogRank", pmethod="exactGauss", iscores=TRUE,
                  abseps=0.01)

     # conditional Monte-Carlo

     maxstat.test(Surv(time, cens) ~ MGE, data=DLBCL,
                  smethod="LogRank", pmethod="condMC", B = 9999) 

     # survival analysis and plotting like in Alizadeh et al. (2000)

     if(require(survival, quietly = TRUE)) {

       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

       ## Not run: 
        # postscript("survDLBCL.ps",horizontal=F, width=8, height=8)
         pdf("survDLBCL.pdf", width=8, height=8)

       ## End(Not run)
       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, lwd=2)

       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)   

       ## Not run: 
         dev.off()
       
     ## End(Not run)
     }

