Question

如果我们使用以下生存数据......

library(survival)
data(pbc)

#model to be plotted and analyzed, convert time to years
fit <- survfit(Surv(time/365.25, status) ~ edema, data = pbc)

#visualize overall survival Kaplan-Meier curve
plot(fit)

...并以这种方式进一步计算1,2,3年的存活率：

>     summary(fit,times=c(1,2,3))

...输出是这样的：

Call: survfit(formula = Surv(time/365.25, status) ~ edema, data = pbc)

232 observations deleted due to missingness 
                edema=0 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
    1    126      12    0.913  0.0240        0.867        0.961
    2    112      12    0.825  0.0325        0.764        0.891
    3     80      26    0.627  0.0420        0.550        0.714

                edema=0.5 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
    1     22       7    0.759  0.0795        0.618        0.932
    2     17       5    0.586  0.0915        0.432        0.796
    3     11       4    0.448  0.0923        0.299        0.671

                edema=1 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
    1      8      11    0.421  0.1133       0.2485        0.713
    2      5       3    0.263  0.1010       0.1240        0.558
    3      3       2    0.158  0.0837       0.0559        0.446

如何将上述内容导出为“.csv”文件？

Answer 1

您可以从summary对象中提取所需的元素。将其转换为数据框并另存为csv。

res <- summary(fit,times=c(1,2,3))
save.df <- as.data.frame(res[c("strata", "time", "n.risk", "n.event", "surv", "std.err", "lower", "upper")])
write.csv(save.df, file = "./file.csv")

如何将survfit输出导出为.csv表？

1 个答案: