As you can see adjusting for control variables changes the plot. This is not my problem, but actually even what I expected (theoretically meaningful). My problem is, however, that ggsurvplot does not show the number at risk once one adjusts for other variables. This was discussed here. In the link provided, the suggstion is to simply use the number of risk values of the unjusted analysis for the plot of the adjusted analysis. Is this a valid approach?
The reason why I am sceptical: Thinking of number at risk as the number of people beeing alive in a certain group to a certain time suggests that the number of risk values do not change if one adjusts for other variables. On the other hand, I am confused because the unadjusted plot shows that the cumulative events are high in group 1, meaning that people in group 1 die more often during the study. The adjusted plot shows the exact opposite: people in group 1 have lowest cumulative incident rates, meaning less people die here. But if the number of people dying vary for a certain group between the unadjusted and the adjusted analysis, how can be the number of risk the same? I think I have a misconception either about number at risk or the cumulative incidence values. Thanks in advance.