Pretty much agree with the above. Note that in our manuscript we use response as a continuous variable (e.g., in Figure 4d) and generally do not categorize until later in the analyses. We are always bound of course by problematic conventions such as the limitations of the RECIST criteria used to assess response by imaging in oncology etc.
Note also that our “responder analysis” is not done in a vacuum. We have plenty of functional experimental data and other preclinical and clinical analyses (observational via correlatives and experimental via trials) that guide our analyses. Even right now I am brainstorming these pathways with my collaborators via text messages. Without that context, any such attempts are likely to be lost in a hopeless maze of possibilities. Basing inferences using clinical data alone is typically a bad idea outside of comparative inferences from RCTs, and even then there are caveats. Essentially: don’t try this at home 
BTW, your connection with randomized non-comparative trials (RNCTs) is extremely insightful. Indeed, collaborators focused on the type of responder analyses in our manuscript do not intuitively find anything wrong with RNCTs. Part of the reason why this design is so insidious is that it takes advantage of cognitive blind spots in highly accomplished scientists not familiar with the mechanics of randomization.