Horizontal mixture model for competing risks: a method used in waitlisted renal transplant candidates

Abstract

When a patient is registered on renal transplant waiting list, she/he expects a clear information on the likelihood of being transplanted. Nevertheless, this event is in competition with death and usual models for competing events are difficult to interpret for non-specialists. We used a horizontal mixture model. Data were extracted from two French dialysis and transplantation registries. The "Ile-de-France" region was used for external validation. The other patients were randomly divided for training and internal validation. Seven variables were associated with decreased long-term probability of transplantation: age over 40 years, comorbidities (diabetes, cardiovascular disease, malignancy), dialysis longer than 1 year before registration and blood groups O or B. We additionally demonstrated longer mean time-to-transplantation for recipients under the age of 50, overweight recipients, recipients with blood group O or B and with pre-transplantation anti-HLA class I or II immunization. Our model can be used to predict the long-term probability of transplantation and the time in dialysis among transplanted patients, two easily interpretable parts. Discriminative capacities were validated on both the internal and external (AUC at 5 years = 0.72, 95% CI from 0.68 to 0.76) validation samples. However, calibration issues were highlighted and illustrated the importance of complete re-estimation of the model for other countries. We illustrated the ease of interpretation of horizontal modelling, which constitutes an alternative to sub-hazard or cause-specific approaches. Nevertheless, it would be useful to test this in practice, for instance by questioning both the physicians and the patients. We believe that this model should also be used in other chronic diseases, for both etiologic and prognostic studies.

Outcomes after renal transplantation of obese patients: a French cohort-based study

“…The proportion of obese patients in our transplantation cohort was 15.9%, in-line with French practices recently described from the national French Registry. One can note that 20% of dialyzed patients in France are obese, illustrating that obesity may be an obstacle to access to transplantation, as previously reported [20]. This was the main reason of our study, obese patients have a lower access to transplantation in France, while the risk/bene t ratio associated with transplantation remains unknown in French obese patients.…”

“…Donor variables extracted from the database were age, sex, last serum creatininemia, donor cause of death and type (living or deceased including heart or non-heart beating donors), and expanded donor criteria (ECD). 20 Recipient characteristics at baseline were age, sex, blood group, initial renal disease, comorbidities prior to transplantation (diabetes, hypertension, dyslipidemia, neoplasia, cardiovascular history), duration on waiting list before transplantation, type of dialysis before transplantation (peritoneal, hemodialysis or pre-emptive) and anti-HLA class I or anti-class II immunization before transplantation. Transplantation parameters were cold ischemia time, number of HLA-A-B-DR incompatibilities and induction therapy.…”

Renal transplantation outcomes in obese patients: a French cohort-based study

“…The proportion of obese patients in our transplantation cohort was 15.9%, in-line with French practices recently described from the national French Registry. One can note that 20% of dialyzed patients in France are obese, illustrating that obesity may be an obstacle to transplantation access, as previously reported [20]. This was the main reason of our study; obese patients have a lower access to transplantation in France, whilst the risk/bene t ratio associated with transplantation remains unknown in French obese patients.…”

“…Donor variables extracted from the database were age, sex, last serum creatininemia, donor cause of death and type (living or deceased including heart or non-heart beating donors), and expanded donor criteria (ECD). 20 Recipient characteristics at baseline were age, sex, blood group, initial recurrent causal nephropathy following transplantation (the following were considered as possibly recurrent: glomerulosclerosis, serious nephrotic syndrome with focal sclerosis, IgA nephropathy (Berger's disease), dense deposit disease, glomerulonephritis, Wegener's granulomatosis, Lupus erythematosus, Henoch-Schoenlein purpura, Goodpasture's syndrome, systemic sclerosis (scleroderma), haemolytic uraemic syndrome, multi-system disease), renal disease, comorbidities prior to transplantation (diabetes, hypertension, dyslipidemia, neoplasia, cardiovascular history (cardiopathy and cardiomyopathy, cardiac insu ciency, coronaropathy, cardiac rhythm disorder, cardiac valvopathy, cardiac valvular prothesis, cardiac conduction disorder, pacemaker, cardiogenic shock or collapses, pulmonary hypertension, cerebrovascular accident (stroke or bleeding), peripheral arteriopathy, or venous thrombo-embolism), duration on waiting list before transplantation, type of dialysis before transplantation (peritoneal, hemodialysis or pre-emptive) and anti-HLA (Human Leucocyte Antigen) class I or anti-class II immunization before transplantation. Transplantation parameters were cold ischemia time, number of HLA (A+B+DR) incompatibilities and induction therapy.…”

Features of survival analysis on patients on the «waiting list» for kidney transplantation

“…Larson и G.E. Dinse, лег в основу другого интересного исследования [31]. Авторы использовали параметрическую регрессионную модель смеси (parametric mixture regression model) для оценки долгосрочной вероятности двух конкурирующих событий: трансплантации и смерти на диализе, а также среднего времени до каждого из ýтих событий с учетом различных факторов (возраст, группа крови, индекс массы тела, причина хронической болезни почек, наличие сахарного диабета, кардиоваскулярных и онкологических заболеваний, время на диализе, наличие анти-HLA антител, регион проживания и др.).…”