R语言CoxPH分析置信区间过大问题的解决咨询

使用以下样本数据集进行CoxPH分析时出现异常：

structure(list(Systemic.Tx...2.classification..Chemotherapy..PD1.monotherapy..PD.1.CTLA.4.combo..PD.1.chemo..targetted.Tx..targetted.chemo.combo..etc.
 = c("Targetted Tx",  "Targetted Tx", "Targetted Tx", "Targetted Tx", "Targetted Tx",  "Targetted Tx", "Targetted Tx", "Targetted Tx",
 "Targetted Tx",  "Targetted Tx", "Targetted Tx", "Targetted Tx",
 "Targetted Tx",  "Targetted Tx", "Targetted Tx", "Targetted Tx",
 "Targetted Tx",  "Targetted Tx", "Targetted Tx", "Targetted Tx",
 "Targetted Tx",  "Targetted Tx", "Targetted Tx", "Targetted Tx",
 "Targetted Tx",  "Targetted Tx", "Targetted Tx", "Targetted Tx",
 "Targetted Tx",  "Targetted Tx", "Targetted/chemo combo", "Targetted Tx", "Targetted Tx",  "Targetted Tx"), Time.on.systemic.Tx =
 c("2.069815195", "2.332648871",  "2.069815195", "1.215605749",
 "2.661190965", "0.689938398", "1.839835729",  "2.858316222",
 "0.657084189", "2.529774127", "1.80698152", "3.482546201", 
 "2.891170431", "3.515400411", "2.431211499", "3.515400411",
 "1.347022587",  "5.519507187", "17.47843943", "26.90759754",
 "6.176591376", "5.979466119",  "8.246406571", "15.40862423",
 "5.749486653", "6.242299795", "5.683778234",  "6.636550308",
 "10.15195072", "10.0862423", "18.52977413", "5.749486653", 
 "10.7761807", "6.965092402"), PFS2 = c(2.595482546, 2.37, 2.069815195, 
1.412731006, 1.938398357, 0.657084189, 2.529774127, 3.219712526, 
 0.657084189, 2.529774127, 2.2, 3.482546201, 2.529774127, 3.712525667, 
 2.234086242, 3.778234086, 1.347022587, 5.55, 17.3798768, 30.32443532, 
 7.12936345, 7.09650924, 8.246406571, 15.24435318, 5.519507187, 
 5.749486653, 5.420944559, 6.636550308, 9.264887064, 10.02053388, 
 18.20123203, 6.110882957, 10.61190965, 6.866529774), PFS2_event = c(1,  1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1,  1, 1,
 1, 1, 1, 0, 1, 1, 0, 1, 1, 1), Binarised_Time.on.Tx.2 = c("≤ 3.52
 months",  "≤ 3.52 months", "≤ 3.52 months", "≤ 3.52 months", "≤ 3.52
 months",  "≤ 3.52 months", "≤ 3.52 months", "≤ 3.52 months", "≤ 3.52
 months",  "≤ 3.52 months", "≤ 3.52 months", "≤ 3.52 months", "≤ 3.52
 months",  "≤ 3.52 months", "≤ 3.52 months", "≤ 3.52 months", "≤ 3.52
 months",  "> 3.52 months", "> 3.52 months", "> 3.52 months", "> 3.52
 months",  "> 3.52 months", "> 3.52 months", "> 3.52 months", "> 3.52
 months",  "> 3.52 months", "> 3.52 months", "> 3.52 months", "> 3.52
 months",  "> 3.52 months", "> 3.52 months", "> 3.52 months", "> 3.52
 months",  "> 3.52 months")), row.names = c(NA, -34L), class =
 "data.frame")

分析代码：

fit1 <- coxph(Surv(PFS2, PFS2_event) ~ Binarised_Time.on.Tx.2, data = Test_Dataset) 
summary(fit1)

运行后收到警告：

Warning message: In coxph.fit(X, Y, istrat, offset, init, control, weights = weights, : Loglik converged before variable 1 ; coefficient may be infinite.

同时得到异常结果：置信区间为0到Inf，系数和p值异常偏高。但同一数据集用于Overall Survival分析时结果正常。

• 完全分离现象：观察数据可知，Binarised_Time.on.Tx.2为≤ 3.52 months的组中，17个样本里有15个发生了PFS2事件；而> 3.52 months组中17个样本里有7个删失，且事件发生时间普遍更长。这种两组间事件发生的极端差异，导致Cox模型无法估计有限的回归系数，模型倾向于认为其中一组风险为0或无穷大，进而出现系数无限大的警告和异常置信区间。
• PFS2的定义特性：PFS2是从一线治疗开始到第二次进展或死亡的时间，而分组变量Binarised_Time.on.Tx.2基于一线治疗持续时长。治疗持续久的患者本身更不易出现进展（否则治疗不会持续这么久），这就导致治疗时长与PFS2结果形成强关联甚至完全分离。而OS受后续治疗等更多因素影响，不会出现这种极端分组差异，因此分析结果正常。
• 小样本下的事件分布失衡：34个样本分成两组各17个，一组几乎全是事件，另一组删失比例高，小样本下的这种极端分布会放大完全分离的影响，让模型无法稳定估计参数。

内容的提问来源于stack exchange，提问作者Adam