How to hide anova significance levels on the bottom of the table

Question

Suppose I compared two models of nested random effects using anova(), and the result is below:

new.model: new
current.model: new 
              Df    AIC    BIC  logLik  Chisq Chi Df Pr(>Chisq)    
new.model      8 299196 299259 -149590                             
current.model  9 299083 299154 -149533 115.19      1  < 2.2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

I would like to use only the table part (see below):

              Df    AIC    BIC  logLik  Chisq Chi Df Pr(>Chisq)    
new.model      8 299196 299259 -149590                             
current.model  9 299083 299154 -149533 115.19      1  < 2.2e-16 ***

I know I am able to get rid of the heading part (see blow) by setting the heading to null using attributes(anova.object)$heading = NULL, but I don't know how to get rid of the bottom part: Signif. codes: .....

new.model: new
current.model: new

I crucially do not want to use data.frame (see below) as it changes the blank cells to NAs

data.frame(anova(new.model, current.model))
              Df      AIC      BIC    logLik    Chisq Chi.Df   Pr..Chisq.
new.model      8 299196.4 299258.9 -149590.2       NA     NA           NA
current.model  9 299083.2 299153.6 -149532.6 115.1851      1 7.168247e-27

I wonder if you guys know a way to deal with this situation.

[UPDATE]: I ended up writing a wrapper using print.anova:

anova.print = function(object, signif.stars = TRUE, heading = TRUE){
    if(!heading)
         attributes(object)$heading = NULL
    print.anova(object, signif.stars = signif.stars)
}

Example:

dv = c(rnorm(20), rnorm(20, mean=2), rnorm(20))
iv = factor(rep(letters[1:3], each=20))
anova.object = anova(lm(dv~iv))

Analysis of Variance Table
Response: dv 
          Df Sum Sq Mean Sq F value    Pr(>F)    
iv         2 46.360 23.1798  29.534 1.578e-09 ***
Residuals 57 44.737  0.7849                      
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 


anova.print(anova.object, F, F)
          Df Sum Sq Mean Sq F value    Pr(>F)
iv         2 46.360 23.1798  29.534 1.578e-09
Residuals 57 44.737  0.7849             

Answer 1

EDIT: anova has a print method with signif.stars as a parameter

anova(new.model, current.model, signif.stars=FALSE)

> x <- anova(lm(hp~mpg+am, data=mtcars))
> print(x, signif.stars=F)
Analysis of Variance Table

Response: hp
          Df Sum Sq Mean Sq F value    Pr(>F)
mpg        1  87791   87791 54.5403 3.888e-08
am         1  11255   11255  6.9924   0.01307
Residuals 29  46680    1610