[R] Issue when using a coxph + summary function in R while using a pspline-transformed covariate

[Dumortier, Thomas]

Hello 
 
I have an issue with obtaining a confidence interval from a coxph object in R while using a spline-transformed covariate.

This is a time to event analysis using coxph() from the survival package.
In the model below, COVA is a continuous covariate. COVA is time-dependent hence the counting process notation. COVA is transformed via pspline, COVB (FALSE or TRUE) is a fixed covariate. 
My goal is to get the confidence interval for COVB. With this purpose, I use the summary(…,conf.int=.95) function.
I have pasted the code and the console below.

The estimation works well.
The summary function returns the desired confidence interval in the console, but it returns a NULL object (psp.sum is returned NULL, see below the code and the console) 

Note that if I do not use pspline, it works !!!!!
So it seems that the use of pspline is not compatible with the summary function.

This is a problem because I would like to do some simulation and need to retrieve the confidence interval from psp.sum.

Can you kindly help?

Rgds
Tom

CODE
 
psp<-coxph(Surv(DAY2,DAY2P1,EVTF)~COVB+pspline(COVA, df = 0, caic = T),data=dsn4,method='breslow')
psp
psp.sum<-summary(psp,conf.int=.95)
psp.sum
 
CONSOLE

1> psp<-coxph(Surv(DAY2,DAY2P1,EVTF)~COVB+pspline(COVA, df = 0, caic = T),data=dsn4,method='breslow')
 
1> psp
Call:
coxph(formula = Surv(DAY2, DAY2P1, EVTF) ~ COVB + pspline(COVA, 
    df = 0, caic = T), data = dsn4, method = "breslow")
 
                          coef   se(coef) se2    Chisq DF   p      
COVBTRUE                  -1.625 0.4223   0.4198 14.80 1.00 1.2e-04
pspline(COVA, df = 0, caic -0.341 0.0761   0.0761 20.04 1.00 7.6e-06
pspline(COVA, df = 0, caic                         1.95 0.83 1.3e-01
 
Iterations: 10 outer, 29 Newton-Raphson
     Theta= 0.98 
Degrees of freedom for terms= 1.0 1.8 
Likelihood ratio test=22.3  on 2.81 df, p=4.52e-05  n= 16933 
 
1> psp.sum<-summary(psp,conf.int=.95)
Call:
coxph(formula = Surv(DAY2, DAY2P1, EVTF) ~ COVB + pspline(COVA, 
    df = 0, caic = T), data = dsn4, method = "breslow")
 
  n= 16933, number of events= 35 
 
                          coef   se(coef) se2    Chisq DF   p      
COVBTRUE                  -1.625 0.4223   0.4198 14.80 1.00 1.2e-04
pspline(COVA, df = 0, caic -0.341 0.0761   0.0761 20.04 1.00 7.6e-06
pspline(COVA, df = 0, caic                         1.95 0.83 1.3e-01
 
          exp(coef) exp(-coef) lower .95 upper .95
COVBTRUE    0.19690       5.08  8.61e-02    0.4506
ps(COVA)3    0.59903       1.67  3.48e-01    1.0301
ps(COVA)4    0.35872       2.79  1.36e-01    0.9470
ps(COVA)5    0.21394       4.67  5.82e-02    0.7857
ps(COVA)6    0.12594       7.94  2.69e-02    0.5898
ps(COVA)7    0.07290      13.72  1.31e-02    0.4051
ps(COVA)8    0.04275      23.39  6.84e-03    0.2673
ps(COVA)9    0.02647      37.78  3.89e-03    0.1802
ps(COVA)10   0.01785      56.04  2.45e-03    0.1301
ps(COVA)11   0.01310      76.32  1.68e-03    0.1024
ps(COVA)12   0.01019      98.11  1.19e-03    0.0870
ps(COVA)13   0.00810     123.39  8.32e-04    0.0790
ps(COVA)14   0.00645     154.95  5.43e-04    0.0767
ps(COVA)15   0.00512     195.45  3.26e-04    0.0803
ps(COVA)16   0.00405     246.92  1.80e-04    0.0913
ps(COVA)17   0.00320     312.04  9.11e-05    0.1127
ps(COVA)18   0.00254     394.32  4.29e-05    0.1499
ps(COVA)19   0.00201     498.30  1.89e-05    0.2133
 
Iterations: 10 outer, 29 Newton-Raphson
     Theta= 0.98 
Degrees of freedom for terms= 1.0 1.8 
Concordance= 0.673  (se = 0.05 )
Rsquare= 0.001   (max possible= 0.026 )
Likelihood ratio test= 22.3  on 2.81 df,   p=4.52e-05
Wald test            = 24.6  on 2.81 df,   p=1.48e-05
 
1> psp.sum
NULL
1>