I wonder if I'm misunderstanding the issue because as far as I understand things, you should be getting different results with PROC GLM and PROC MIXED for repeated measures. In the Class Levels section of the GLM output, are you getting a note that observations have been removed due to missing data? In the Dimensions section of the PROC MIXED output, how many observations are used and not used? Does the number used match the total number of non-missing values or just for the subjects with complete data?
I found this in the SAS Course Notes for Mixed Model Analyses:
"In the presence of missing repeated measures for a subject, the MIXED procedure does not exclude this subject from the analysis; instead it uses all the available data. This method (likelihood-based ignorable analysis) leads to a valid analysis when the missing data can be assumed missing at random (MAR)."
Unfortunately, it doesn't sound like your data is missing at random, so there might be better methods than PROC MIXED anyway.
Here are some other web links about this topic:
http://support.sas.com/rnd/app/papers/mixedglm.pdf
http://www.stat.lsu.edu/faculty/moser/exst7037/repeatedpres.pdf
http://www.ats.ucla.edu/stat/sas/faq/mixmiss.htm
There is an example in the third link that shows how GLM drops 4 of the 8 subjects because of missing data, but MIXED uses the available data from all 8 subjects. The two methods produce different p-values because of this.