search for: carcinoma

...ot;tumourA" "tumourEXP" "int" "stain" "tumourPERC" "branch" > levels(tma$tumourA) [1] "DCIS" "LN Metastasis" "Normal" "Primary Invasive Carcinoma" #split into cancer and normal tissue > tma1<-subset(tma, tumourA=="Primary Invasive Carcinoma") > tma2<-subset(tma, tumourA=="LN Metastasis") > tmaN<-subset(tma, tumourA=="Normal") #size of datasets > dim(tma1) [1] 587 9 > dim(tma2...

...n events median 0.95LCL 0.95UCL 136 96 6 6 8 # # predict a curve for a patient: (these are the answers I really want to extract) # > survfit(surv.results$cox, newdata=data.frame(onset=50, ic.duration=10, simple.msa=c('MSA','Not MSA'), autoimmune=F, carcinoma=F)) Call: survfit.coxph(object = surv.results$cox, newdata = data.frame(onset = 50, ic.duration = 10, simple.msa = c("MSA", "Not MSA"), autoimmune = F, carcinoma = F)) n events median 0.95LCL 0.95UCL [1,] 136 96 8 7 11 [2,] 136 96 3...

Dear R users I use Windows XP, R2.5.1 (I have read the posting guide, I have contacted the package maintainer first, it is not homework). In a research project on renal cell carcinoma we want to compute Harrell's c index, with optimism correction, for a multivariate Cox regression and also for some univariate Cox models. For some of these univariate models I have encountered an error message (and no result produced) from the function validate i Frank Harrell's Design...

Hi,

Dear R team, dear Prof. Therneau, library(survival) data(colon) ?colon gives me only a very rudimentary source (only a name). Is there a possibility to get a reference to the clinical trial these data are taken from? Many thanks in advance. With best wishes, Matthias Gondan --

...y performing kinase exon sequencing. More specifically, we are performing sequencing on 1) 400 samples from the NEO-ALTTO study to find alterations associated with resistance to HER2 targeted therapies; 2) at least 200 colorectal samples and 300 breast cancers (triple negatives and invasive lobular carcinomas) to detect alterations frequently occurring in these patient populations. A very strong feature of all these datasets is that matched controls are available to ensure high accuracy in variant calling. The goal is to detect genomic alterations associated with response to therapy and cancer subtypes...