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我已经制作了一些 Kaplan-Meier 图，我一直在努力让风险表的数量出现。它目前如下所示： 在此处输入图像描述1

使用 summary(survfit 函数) 这是 n.risk 和 n.events 的摘要

我的代码如下所示：

library(survival)

KMoverall = survfit(Surv(ds$followuptimemonths, ds$Death=="Y") ~ 1, data=ds)

ggsurvplot(KMoverall, xlim = c(0,46), break.x.by = 12, xlab= "Months", ylab = "OS Probability" , surv.scale = "percent" , legend = "none", conf.int = FALSE, pval = FALSE, surv.median.line = NULL , risk.table = TRUE, cumevents = FALSE, cumcensor = FALSE, table.height = 0.1, size = 1, linetype = "strata")

我做错了什么？

dput(ds) 相关列

followuptimemonths = structure(c(24.6901403820232, 27.944899233981, 
    10.7176907650327, 4.47118387743696, 14.0382023210705, 32.9421047440576, 
    31.9558141828583, 31.5941743104185, 21.3696288259855, 29.2599533155801, 
    10.6848144129927, 12.6902718874314, 19.4299240556268, 20.3175855607062, 
    10.6519380609528, 37.8406811980143, 18.3778807903475, 22.060032218825, 
    27.8133938258211, 31.0681526777789, 9.17250221915376, 18.4765098464674, 
    13.5450570404708, 44.2844461978499, 23.0463227800243, 34.3886642338166, 
    31.9886905348982, 42.1146069632114, 37.2817832133346, 35.0461912746162, 
    35.3749547950159, 23.4079626524641, 34.0927770654568, 20.2847092086662, 
    5.81911431107604, 28.1421573462209, 17.9176118617878, 16.0436597955091, 
    22.5860538514646, 21.6655159943453, 20.547720024986, 12.1642502547917, 
    11.5067232139922, 11.3423414537923, 10.6519380609528), units = "days", class = "difftime")

death <- structure(c(1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 
1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 
1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L
), .Label = c("N", "Y"), class = "factor")

ds <- data.frame(followuptimemonths, death)

知识管理总结

  time n.risk n.event survival std.err lower 95% CI upper 95% CI
  4.47     45       1    0.978  0.0220        0.936        1.000
  5.82     44       1    0.956  0.0307        0.897        1.000
 10.68     40       1    0.932  0.0381        0.860        1.000
 10.72     39       1    0.908  0.0440        0.826        0.998
 11.34     38       1    0.884  0.0489        0.793        0.985
 16.04     32       1    0.856  0.0546        0.756        0.970
 17.92     31       1    0.829  0.0594        0.720        0.954
 18.38     30       1    0.801  0.0635        0.686        0.936
 19.43     28       1    0.772  0.0674        0.651        0.917
 20.28     27       1    0.744  0.0707        0.617        0.896
 23.41     19       1    0.705  0.0771        0.569        0.873
 27.94     16       1    0.661  0.0839        0.515        0.847
 31.99     10       1    0.595  0.0981        0.430        0.822
 34.39      7       1    0.510  0.1151        0.327        0.794
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