In oncology, scenarios where intermediate endpoints such as PFS or DFS are more reliable than OS for the analysis of RCTs are becoming increasingly more common. See related post here and here is a scenario where PFS and not OS is the gold standard for proper RCT inferences.
The effect of subsequent therapies is a major reason why OS has structural biases that intermediate endpoints lack. It is a good problem to have. In aggressive cancers, or in the past when we had fewer treatments available, OS would happen earlier and be a more reliable endpoint to use under typical modeling assumptions.
It is also indeed a limitation of PFS and DFS that they treat other events as equal to death. However, in practice nowadays death often happens much later than other events in many cancers so that time to progression (TTP) strongly corresponds to PFS. Nevertheless, no endpoint is perfect and there is certainly much work to be done to address the limitations of OS and of PFS/DFS. Revamping our estimands in oncology, and the models we use for them, is a tremendous open methodological problem.