I had only looked some on the SAS software help. I looked at the SAS website just now and it says the output from the two PROCs should be the same, which is what I originally thought. So I'll have to check the code again but I could've sworn it's the same with both GENMOD and GLM.
Actually it's not the regular GENMOD and GLM output that was different (I diidn't even check that actually) but rather the results from the ESTIMATE statements that were different. So maybe even though the procs give the same output in general they give different output on identical ESTIMATE statements, perhaps because different paramaterizations are used. I'll check into it but if anyone has any idea off the top of their heads please pipe up.
You can use PROC GAM, rather than PROC LOESS, to fit a model to a logistic model to a binary response that includes loess- or spline-smoothed predictors. For details and examples, see the GAM documentation: