从 kaplan Meier 模型中提取 95% 置信区间值

Question

计算 kaplan Meier 模型后，我得到下面的 km_fit 列表。现在如何提取 95% 置信区间值？

library(survminer)
sg1<-structure(list(`patient serial number` = c(1, 2, 3, 4, 6), `Time from breast cancer diagnosis to bone metastasis (months) (NA = unknown)` = c(28.37260274, 
14.00547945, 75.02465753, 137.3260274, 34.15890411), `status (=1 as all pts have bone metastasis and BC)` = c(1, 
1, 1, 1, 1), `Molecular type (0=hr+her2+, 1=hr+her2-, 2=hr-her2+, 3=TNBC)` = structure(c(1L, 
2L, 2L, 1L, 1L), levels = c("HR+HER2-", "unknown", "HR-HER2+", 
"HR+HER2+", "HR-HER2-"), class = "factor")), row.names = c(NA, 
-5L), class = c("tbl_df", "tbl", "data.frame"))

# Plot Kaplan-Meier curves
sg1_survival <- Surv(
  time = sg1$`Time from breast cancer diagnosis to bone metastasis (months) (NA = unknown)`,
  event = sg1$`status (=1 as all pts have bone metastasis and BC)`
)


km_fit <- survfit(sg1_survival ~ sg1$`Molecular type (0=hr+her2+, 1=hr+her2-, 2=hr-her2+, 3=TNBC)`, data = sg1)

# Calculate 95% confidence intervals
ci <- confint(km_fit, level = 0.95)

Answer 1

km_fit <- survfit(sg1_survival ~ sg1$`Molecular type (0=hr+her2+, 1=hr+her2-, 2=hr-her2+, 3=TNBC)`, data = sg1)
sum <- summary(km_fit)
c <- data.frame(sum$time, sum$lower, sum$upper) 
c

Answer 2

请尝试以下扫帚套餐并检查

conf.high & conf.low

new_km_fit <- broom::tidy(km_fit)


# A tibble: 5 × 9
   time n.risk n.event n.censor estimate std.error conf.high conf.low strata                         
  <dbl>  <dbl>   <dbl>    <dbl>    <dbl>     <dbl>     <dbl>    <dbl> <chr>                          
1  28.4      3       1        0    0.667     0.408         1   0.300  sg1$`Molecular type (0=hr+her2…
2  34.2      2       1        0    0.333     0.816         1   0.0673 sg1$`Molecular type (0=hr+her2…
3 137.       1       1        0    0       Inf            NA  NA      sg1$`Molecular type (0=hr+her2…
4  14.0      2       1        0    0.5       0.707         1   0.125  sg1$`Molecular type (0=hr+her2…
5  75.0      1       1        0    0       Inf            NA  NA      sg1$`Molecular type (0=hr+her2…