Median waiting times published by transplant organizations around the world may be biased when death or censoring is disregarded. This leads to too optimistic waiting times, particularly in kidney transplantation, and as a consequence can deceive patients on the waiting list, transplant physicians, and healthcare policy maker. Competing risk multistate models are suited for the analysis of time-to-event data of the organ waiting list. Resulting cumulative incidences are probabilities for transplantation or death by a given time, and are a more accurate description of the events occurring on the waiting list. In accordance with the concept of median survival time in survival analysis in clinical trials, we suggest the median time to transplantation (MTT), the waiting time duration at which the transplant probability is 0.50, as a measure of average waiting time.

Summary points

Transplant candidates on the waiting list, healthcare professionals and policy makers may be interested in the accurate assessment of the probabilities of transplantation and undesirable events.

The median waiting time based on the median calculated across the waiting durations of transplanted individuals may be misleading due to selection bias, ignoring death and censored observations.

Competing risk multistate models based on the Aalen-Johansen estimator are effective in assessing the waiting list with multiple competing events.

From the cumulative incidence curve the probabilities of transplantation or death can be determined for any time period.

We propose to report both the median time to transplantation (MTT), i.e. the waiting time duration at which the transplant probably is 50%, as well as the probabilities of other competing events during MTT.

National transplant organizations around the world may consider changing their reporting policy regarding waiting list statistics.

The authors have declared no competing interest.

This study did not receive any funding.

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