Time-to-event analyses are frequently used in nephrology research, for instance, when recording time to death or time to peritonitis in dialysis patients. Many papers have pointed out the important issue of competing events (or competing risks) in such analyses. For example, when studying one particular cause of death it can be noted that patients also die from other causes. Such competing events preclude the event of interest from occurring and thereby complicate the statistical analysis. The Kaplan-Meier approach to calculating the cumulative probability of the event of interest yields invalid results in the presence of competing risks, thus the alternative cumulative incidence competing risk (CICR) approach has become the standard. However, when kidney transplant is the competing event that prevents observing the outcome of interest, CICR may not always be the matter of interest. We discuss situations where both the Kaplan-Meier and the CICR approach are not suitable for the purpose and point out alternative analysis methods for such situations. We also look at the suitability and interpretation of different estimators for relative risks. In the presence of transplant as a competing risk, one should very clearly state the research question and use an analysis method that targets this question.