On the age-scale vs. time-scale issue, chl has some good references and captures the essentials -- in particular, the requirement that the at-risk set contain sufficient subjects from all ages as would arise in a longitudinal study.
I would only note that there is no general consensus around this yet, but there is some literature to suggest that age should be preferred as the time scale in certain cases. In particular, if you have a situation where time doesn't accumulate in the same way for all subjects, for example due to exposure to some toxic material, then age may be more appropriate.
On the other hand, you can handle that specific example on a time-scale Cox PH model by using age as a time varying covariate -- rather than a fixed covariate at start time. You need to think about the mechanism behind your object of study to figure out which time scale is more appropriate. Sometimes it's worth fitting both models to existing data to see if discrepancies arise and how they might be explained before designing your new study.
Finally, the obvious difference in analyzing the two is that on an age-scale, the interpretation of survival is with respect to an absolute scale (age), whereas on a time-scale, it's relative to the start/entry date of the study.