I think a statistically right way would be, if you run the regression again - without var1 & var6 - and compare the likelihood functions. If they don't differ much, you don't need the 2 variables. (Likelihood-Ratio-Test: Subtract lambda=2*(likelihood with var1&var6 - likelihood without var1&var6) -> get value of the chi-squared distribution with 2 degrees of freedom -> if the result is almost zero (e.g. <0.01) the 2 variables should not be excluded.)