r - 使用 survminer (ggsurvplot) 将 Kaplan-Meier 图 y 轴更改为失败概率而不是生存概率？

Question

我正在使用 survminer 包中的 ggsurvplot 创建 Kaplan-Meier 图，显示精神疾病家族史与精神疾病发作之间的关系。这是我使用的代码:

km_fhr <- ggsurvplot(fit = survfit(Surv(fu_time, smidg) ~ fhr, data = df),
                     legend.labs = c("Control", "Family high-risk"),
                     legend.title = "",
                     censor.shape = 124,
                     censor.size = 2.5,
                     palette = c("#00ABE7", "#FFA69E")) +
  labs(x = "Follow-up time (years)", y = "Probability of no SMI diagnosis")

Kaplan-Meier 曲线如下所示:

在我看来，在 y 轴上绘制患病风险(失败率)比不患病概率(存活率)更直观。我假设有一种简单的方法可以做到这一点，但我无法在 survminer 文档中找到描述。

提前致谢!

Answer 1

对累积事件使用参数 fun = event。可重现的例子:

library(survminer)

ggsurvplot(
    survfit(
        Surv(time, status) ~ sex + rx + adhere,
        data = colon
    ),
    fun = "event"
)

来自 ggsurvplot 的帮助:

fun: an arbitrary function defining a transformation of the survival curve. Often used transformations can be specified with a character argument: "event" plots cumulative events (f(y) = 1-y), "cumhaz" plots the cumulative hazard function (f(y) = -log(y)), and "pct" for survival probability in percentage.