Import data:
load("./6Clusters.RData")
Remove Patients without Extra.Mets:
data.analysis <- data.with.clusts %>% filter(!is.na(Extra.Mets))
data.analysis.id <- data.analysis[!duplicated(data.analysis$Patient),]
data.no.missing <- data.analysis %>% filter(is.missing == FALSE)
missings.extended <- extended.data.frame(data = data.no.missing, "Patient", "time", "NTX", "Death.Status", "Survival.after.begining.ZA.mo")
missings.extended.fit <- coxph(Surv(start, stop, Death.Status) ~ Age.Diagnosis + Sex +
Extra.Mets + log(NTX), data = missings.extended)
summary(missings.extended.fit)
## Call:
## coxph(formula = Surv(start, stop, Death.Status) ~ Age.Diagnosis +
## Sex + Extra.Mets + log(NTX), data = missings.extended)
##
## n= 524, number of events= 101
##
## coef exp(coef) se(coef) z Pr(>|z|)
## Age.Diagnosis 0.017087 1.017234 0.007653 2.233 0.02557 *
## Sex 0.304946 1.356552 0.220031 1.386 0.16577
## Extra.Mets 0.648511 1.912690 0.229305 2.828 0.00468 **
## log(NTX) 0.140077 1.150362 0.080523 1.740 0.08193 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## exp(coef) exp(-coef) lower .95 upper .95
## Age.Diagnosis 1.017 0.9831 1.0021 1.033
## Sex 1.357 0.7372 0.8813 2.088
## Extra.Mets 1.913 0.5228 1.2203 2.998
## log(NTX) 1.150 0.8693 0.9824 1.347
##
## Concordance= 0.6 (se = 0.033 )
## Rsquare= 0.037 (max possible= 0.787 )
## Likelihood ratio test= 19.71 on 4 df, p=0.0005695
## Wald test = 18.58 on 4 df, p=0.0009522
## Score (logrank) test = 19 on 4 df, p=0.0007859
ocs.extended <- extended.data.frame(data = data.analysis, "Patient", "time", "NTX", "Death.Status", "Survival.after.begining.ZA.mo")
ocs.extended.fit <- coxph(Surv(start, stop, Death.Status) ~ Age.Diagnosis + Sex +
Extra.Mets + log(NTX), data = ocs.extended)
summary(ocs.extended.fit)
## Call:
## coxph(formula = Surv(start, stop, Death.Status) ~ Age.Diagnosis +
## Sex + Extra.Mets + log(NTX), data = ocs.extended)
##
## n= 698, number of events= 101
##
## coef exp(coef) se(coef) z Pr(>|z|)
## Age.Diagnosis 0.017209 1.017358 0.007578 2.271 0.02316 *
## Sex 0.296267 1.344829 0.219068 1.352 0.17625
## Extra.Mets 0.645800 1.907513 0.228948 2.821 0.00479 **
## log(NTX) 0.162920 1.176942 0.082967 1.964 0.04957 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## exp(coef) exp(-coef) lower .95 upper .95
## Age.Diagnosis 1.017 0.9829 1.0024 1.033
## Sex 1.345 0.7436 0.8754 2.066
## Extra.Mets 1.908 0.5242 1.2178 2.988
## log(NTX) 1.177 0.8497 1.0003 1.385
##
## Concordance= 0.605 (se = 0.033 )
## Rsquare= 0.029 (max possible= 0.687 )
## Likelihood ratio test= 20.52 on 4 df, p=0.0003949
## Wald test = 19.19 on 4 df, p=0.0007221
## Score (logrank) test = 19.61 on 4 df, p=0.000595