Restricted mean survival time over 15 years for patients starting renal replacement therapy: Clinical Epidemiology in Nephrology

Background. The restricted mean survival time (RMST) estimates life expectancy up to a given time horizon and can thus express the impact of a disease. The aim of this study was to estimate the 15‐year RMST of a hypothetical cohort of incident patients starting renal replacement therapy (RRT), according to their age, gender and diabetes status, and to compare it with the expected RMST of the general population. Methods. Using data from 67 258 adult patients in the French Renal Epidemiology and Information Network (REIN) registry, we estimated the RMST of a hypothetical patient cohort (and its subgroups) for the first 15 years after starting RRT (cRMST) and used the general population mortality tables to estimate the expected RMST (pRMST). Results were expressed in three different ways: the cRMST, which calculates the years of life gained under the hypothesis of 100% death without RRT treatment, the difference between the pRMST and the cRMST (the years lost), and a ratio expressing the percentage reduction of the expected RMST: (pRMST − cRMST)/pRMST. Results. Over their first 15 years of RRT, the RMST of end‐stage renal disease (ESRD) patients decreased with age, ranging from 14.3 years in patients without diabetes aged 18 years at ESRD to 1.8 years for those aged 90 years, and from 12.7 to 1.6 years, respectively, for those with diabetes; expected RMST varied from 15.0 to 4.1 years between 18 and 90 years. The number of years lost in all subgroups followed a bell curve that was highest for patients aged 70 years. After the age of 55 years in patients with and 70 years in patients without diabetes, the reduction of the expected RMST was >50%. Conclusion. While neither a clinician nor a survival curve can predict with absolute certainty how long a patient will live, providing estimates on years gained or lost, or percentage reduction of expected RMST, may improve the accuracy of the prognostic estimates that influence clinical decisions and information given to patients.