Author: Jinseob Kim
Date: 2026-03-30

# Competing risk analysis

#### Jinseob Kim

#### 2026-03-30

## Display results of comepting risk analysis using jstable(Fine-Gray Method)

## TableSubgroupMultiCox

### When using the TableSubgroupMultiCox function, preprocessing the data with the finegray function from the survival package is required. The finegray function generates a new dataset containing fgstart, fgstop, fgstatus, and fgwt. The TableSubgroupMultiCox function then displays results based on the corresponding formula and weights.

    data <- mgus2
    data$etime <- with(data, ifelse(pstat == 0, futime, ptime))
    data$event <- with(data, ifelse(pstat == 0, 2 * death, 1))
    data$event <- factor(data$event, 0:2, labels = c("censor", "pcm", "death"))
    data$age65 <- with(data, ifelse(age > 65, 1, 0))
    data$age65 <- factor(data$age65)
    pdata <- survival::finegray(survival::Surv(etime, event) ~ ., data = data)
    TableSubgroupMultiCox(formula = Surv(fgstart, fgstop, fgstatus) ~ sex, data = pdata, var_cov = "age", weights = "fgwt", var_subgroups = c("age65"))
    #>     Variable Count Percent Point Estimate Lower Upper sex=F sex=M P value
    #> sex  Overall 41775     100           0.77  0.54   1.1  10.4   8.1   0.153
    #> 1      age65  <NA>    <NA>           <NA>  <NA>  <NA>  <NA>  <NA>    <NA>
    #> 2          0  7572    18.1           0.71   0.4  1.27  17.2  10.5   0.252
    #> 3          1 34203    81.9            0.8  0.51  1.25   8.7   7.3    0.33
    #>     P for interaction
    #> sex              <NA>
    #> 1               0.673
    #> 2                <NA>
    #> 3                <NA>

## cox2.display

### As written above, preprocessing the data with finegray function is also required. By using corresponding formula and weights, cox2.display function will display table results.

    fgfit <- coxph(Surv(fgstart, fgstop, fgstatus) ~ age + sex,
      weight = fgwt, data = pdata, model = T
    )
    cox2.display(fgfit)
    #> $table
    #>             crude HR(95%CI)    crude P value adj. HR(95%CI)     adj. P value
    #> age         "0.98 (0.97,0.99)" "0.003"       "0.98 (0.97,0.99)" "0.002"
    #> sex: M vs F "0.8 (0.56,1.13)"  "0.207"       "0.77 (0.54,1.1)"  "0.153"
    #>
    #> $metric
    #>                     [,1]               [,2] [,3] [,4]
    #> <NA>                NA                 NA   NA   NA
    #> No. of observations "41775"            NA   NA   NA
    #> No. of events       "115"              NA   NA   NA
    #> AIC                 "1583.87165275874" NA   NA   NA
    #> C-Index             "0.548(0.026)"     NA   NA   NA
    #>
    #> $caption
    #> [1] "Cox model on time ('fgstart, fgstop') to event ('fgstatus')"