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Umpire 2.0: Simulating Associated Survival

Kevin R. Coombes and Caitlin E. Coombes

Base Survival
Appendix

Load the packages we need.

library(Umpire)
library(survival)

Base Survival

Create a survival model, and generate data.

sm <- SurvivalModel(baseHazard = 1/5, # default 1/5 inverse years
                    accrual = 5,      # default 5 years
                    followUp = 1,     # default 1 years
                    units = 12, unitName = "months")
R <- rand(sm, 200)
summary(R)

##       LFU          Event        
##  Min.   : 0.00   Mode :logical  
##  1st Qu.:14.75   FALSE:101      
##  Median :28.00   TRUE :99       
##  Mean   :29.25                  
##  3rd Qu.:41.00                  
##  Max.   :70.00

Fit a Kaplan-Meier curve.

baseModel <- survfit(Surv(LFU, Event) ~ 1, R)
plot(baseModel)

Base Kaplan-Meier survival curve.

Default method to generate beta coefficients.

Now create several cancer models and generate data.

for (ignore in 1:5) {
  for (jgnore in 1:4) {
    cm <- CancerModel("survtester", nPossible=20, nPattern=2,
                       SURV = function(n) rnorm(n, 0, 2), # old default; too large
                   survivalModel = sm)
    S <- rand(cm, 200)
    model <- survfit(Surv(LFU, Event) ~ CancerSubType, S)
    print(model)
    plot(model)
  }
}

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  90      9     NA      NA      NA
## CancerSubType=2 110    101      8       6       9

Two group survival curves (original).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  98      5     NA      NA      NA
## CancerSubType=2 102      0     NA      NA      NA

Two group survival curves (original).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1 101    101      0      NA      NA
## CancerSubType=2  99     94      7       5      10

Two group survival curves (original).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1 103     95      6       5      11
## CancerSubType=2  97     97      0       0       0

Two group survival curves (original).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  94     81     13      11      19
## CancerSubType=2 106     88     12      10      17

Two group survival curves (original).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  94     94      1       1       2
## CancerSubType=2 106      0     NA      NA      NA

Two group survival curves (original).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1 101     48     43      30      NA
## CancerSubType=2  99     72     22      18      30

Two group survival curves (original).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  89      2     NA      NA      NA
## CancerSubType=2 111     90     15      11      19

Two group survival curves (original).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1 100    100      0       0       0
## CancerSubType=2 100      0     NA      NA      NA

Two group survival curves (original).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1 101     12     NA      NA      NA
## CancerSubType=2  99     99      0       0       0

Two group survival curves (original).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  97      0     NA      NA      NA
## CancerSubType=2 103     53     34      27      53

Two group survival curves (original).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1 102      1     NA      NA      NA
## CancerSubType=2  98     93      5       4       6

Two group survival curves (original).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1 103     98      7       5       9
## CancerSubType=2  97      3     NA      NA      NA

Two group survival curves (original).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1 113     37     NA      64      NA
## CancerSubType=2  87     87      1       0       2

Two group survival curves (original).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1 117      1     NA      NA      NA
## CancerSubType=2  83     83      1       1       2

Two group survival curves (original).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1 103    102      2       2       3
## CancerSubType=2  97     12     NA      NA      NA

Two group survival curves (original).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1 105     18     NA      NA      NA
## CancerSubType=2  95     27     NA      57      NA

Two group survival curves (original).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  93      4     NA      NA      NA
## CancerSubType=2 107     89     15      12      17

Two group survival curves (original).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  88     72     11       7      19
## CancerSubType=2 112    111      3       2       4

Two group survival curves (original).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1 108    108      0       0       0
## CancerSubType=2  92     92      0      NA      NA

Two group survival curves (original).

Better method to generate beta coefficients.

Now create several cancer models and generate data.

for (ignore in 1:5) {
  for (jgnore in 1:4) {
    cm <- CancerModel("survtester", nPossible=20, nPattern=2,
                       SURV = function(n) rnorm(n, 0, 0.3),
                   survivalModel = sm)
    S <- rand(cm, 200)
    model <- survfit(Surv(LFU, Event) ~ CancerSubType, S)
    print(model)
    plot(model)
  }
}

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  92     40     45      41      NA
## CancerSubType=2 108     62     34      27      42

Two group survival curves (improved).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  89     29     NA      59      NA
## CancerSubType=2 111     46     51      39      NA

Two group survival curves (improved).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  94     35     NA      47      NA
## CancerSubType=2 106     39     62      52      NA

Two group survival curves (improved).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1 111     89     17      13      22
## CancerSubType=2  89     63     25      15      33

Two group survival curves (improved).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1 102     22     NA      NA      NA
## CancerSubType=2  98     78     15      11      22

Two group survival curves (improved).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  78     54     15      11      22
## CancerSubType=2 122     70     28      21      44

Two group survival curves (improved).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  98     34     NA      41      NA
## CancerSubType=2 102     28     NA      57      NA

Two group survival curves (improved).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  95     43     51      31      NA
## CancerSubType=2 105     63     28      22      45

Two group survival curves (improved).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  98     19     NA      NA      NA
## CancerSubType=2 102     29     NA      55      NA

Two group survival curves (improved).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  97     56     32      27      46
## CancerSubType=2 103     37     56      47      NA

Two group survival curves (improved).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  94     60     26      18      36
## CancerSubType=2 106     52     43      23      NA

Two group survival curves (improved).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1 100      5     NA      NA      NA
## CancerSubType=2 100     41     54      41      NA

Two group survival curves (improved).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1 106     40     61      48      NA
## CancerSubType=2  94     31     68      56      NA

Two group survival curves (improved).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  96     46     34      27      NA
## CancerSubType=2 104     28     NA      56      NA

Two group survival curves (improved).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1 111     87     16      12      21
## CancerSubType=2  89     41     40      36      NA

Two group survival curves (improved).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  96     55     26      20      55
## CancerSubType=2 104     53     42      27      56

Two group survival curves (improved).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1 107     65     36      24      46
## CancerSubType=2  93     24     63      57      NA

Two group survival curves (improved).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  98     66     19      17      28
## CancerSubType=2 102     51     35      30      49

Two group survival curves (improved).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  95     73     23      18      29
## CancerSubType=2 105     74     21      17      26

Two group survival curves (improved).

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1 105     94     11       9      15
## CancerSubType=2  95     30     NA      56      NA

Two group survival curves (improved).

Fewer possible hits

for (nPos in c(5, 10, 15)) {
  for (jgnore in 1:4) {
    cm <- CancerModel("survtester", nPossible=nPos, nPattern=2,
                       SURV = function(n) rnorm(n, 0, 0.3),
                   survivalModel = sm)
    S <- rand(cm, 200)
    model <- survfit(Surv(LFU, Event) ~ CancerSubType, S)
    print(model)
    plot(model)
  }
}

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  90     76     12      11      15
## CancerSubType=2 110     97     12       8      19

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1 101     18     NA      NA      NA
## CancerSubType=2  99     19     NA      NA      NA

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  92     50     34      24      51
## CancerSubType=2 108     56     38      28      50

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  95     48     40      29      51
## CancerSubType=2 105     48     45      40      NA

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  99     14     NA      NA      NA
## CancerSubType=2 101     19     NA      61      NA

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  91     72     15      12      23
## CancerSubType=2 109     75     21      18      35

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  96     27     NA      50      NA
## CancerSubType=2 104     40     47      38      NA

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  99     47     39      30      NA
## CancerSubType=2 101     53     33      30      61

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1 100     35     NA      45      NA
## CancerSubType=2 100     19     NA      NA      NA

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1 100     48     43      26      NA
## CancerSubType=2 100     53     31      23      NA

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  97     27     NA      62      NA
## CancerSubType=2 103     44     47      36      NA

## Call: survfit(formula = Surv(LFU, Event) ~ CancerSubType, data = S)
## 
##                   n events median 0.95LCL 0.95UCL
## CancerSubType=1  98     33     NA      53      NA
## CancerSubType=2 102     24     NA      62      NA

Appendix

sessionInfo()

## R version 4.4.1 (2024-06-14 ucrt)
## Platform: x86_64-w64-mingw32/x64
## Running under: Windows 11 x64 (build 26100)
## 
## Matrix products: default
## 
## 
## locale:
## [1] LC_COLLATE=C                          
## [2] LC_CTYPE=English_United States.utf8   
## [3] LC_MONETARY=English_United States.utf8
## [4] LC_NUMERIC=C                          
## [5] LC_TIME=English_United States.utf8    
## 
## time zone: America/New_York
## tzcode source: internal
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] survival_3.6-4 Umpire_2.0.11 
## 
## loaded via a namespace (and not attached):
##  [1] sass_0.4.9         utf8_1.2.4         generics_0.1.3     tidyr_1.3.1       
##  [5] rstatix_0.7.2      lattice_0.22-6     digest_0.6.36      magrittr_2.0.3    
##  [9] evaluate_0.24.0    grid_4.4.1         mvtnorm_1.2-5      fastmap_1.2.0     
## [13] jsonlite_1.8.8     Matrix_1.7-0       backports_1.5.0    mclust_6.1.1      
## [17] purrr_1.0.2        fansi_1.0.6        mc2d_0.2.1         BimodalIndex_1.1.9
## [21] scales_1.3.0       jquerylib_0.1.4    abind_1.4-5        cli_3.6.3         
## [25] rlang_1.1.4        munsell_0.5.1      splines_4.4.1      cachem_1.1.0      
## [29] yaml_2.3.10        tools_4.4.1        ggsignif_0.6.4     dplyr_1.1.4       
## [33] colorspace_2.1-1   ggplot2_3.5.1      ggpubr_0.6.0       broom_1.0.6       
## [37] vctrs_0.6.5        R6_2.5.1           lifecycle_1.0.4    car_3.1-2         
## [41] oompaBase_3.2.9    cluster_2.1.6      pkgconfig_2.0.3    pillar_1.9.0      
## [45] bslib_0.8.0        gtable_0.3.5       glue_1.7.0         xfun_0.46         
## [49] tibble_3.2.1       tidyselect_1.2.1   highr_0.11         knitr_1.48        
## [53] htmltools_0.5.8.1  rmarkdown_2.27     carData_3.0-5      compiler_4.4.1

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.