Simon Schwab, Andreas Elmer, Daniel Sidler, Lisa Straumann, Ueli Stürzinger, Franz Immer
{"title":"Selection bias in reporting of median waiting times in organ transplantation","authors":"Simon Schwab, Andreas Elmer, Daniel Sidler, Lisa Straumann, Ueli Stürzinger, Franz Immer","doi":"10.1101/2023.12.13.23299859","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":501561,"journal":{"name":"medRxiv - Transplantation","volume":"109 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Transplantation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2023.12.13.23299859","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
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.