Trial reportBMC nephrology2013
Survival prognosis after the start of a renal replacement therapy in the Netherlands: a retrospective cohort study.
Trial report in BMC nephrology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.
- Mortality Risk Prediction Models for People With Kidney Failure: A Systematic Review.JAMA network open · 2025Pooled it
- A pre-transplantation risk assessment tool for graft survival in Dutch pediatric kidney recipients.Clinical kidney journal · 2023Article
- Age and gender differences in symptom experience and health-related quality of life in kidney transplant recipients: a cross-sectional study.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2023Article
- Predicting mortality after start of long-term dialysis-International validation of one- and two-year prediction models.PloS one · 2023Article
- Illness Perceptions and Medication Nonadherence to Immunosuppressants After Successful Kidney Transplantation: A Cross-Sectional Study.Transplant international : official journal of the European Society for Organ Transplantation · 2022Article
- Donor type and 3-month hospital readmission following kidney transplantation: results from the Netherlands organ transplant registry.BMC nephrology · 2021Article
- Living Donor Kidney Transplantation Should Be Promoted Among "Elderly" Patients.Transplantation direct · 2019Article
- Incidence of chronic kidney disease hospitalisations and mortality in Espírito Santo between 1996 to 2017.PloS one · 2019Article
- Development of a risk prediction model for infection-related mortality in patients undergoing peritoneal dialysis.PloS one · 2019Article
- One- and 2-Year Mortality Prediction for Patients Starting Chronic Dialysis.Kidney international reports · 2017Article
- Prediction models for the mortality risk in chronic dialysis patients: a systematic review and independent external validation study.Clinical epidemiology · 2017Article
- Association of Relapse with Renal Outcomes under the Current Therapy Regimen for IgA Nephropathy: A Multi-Center Study.PloS one · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThere is no single model available to predict the long term survival for patients starting renal replacement therapy (RRT). The available models either predict survival on dialysis until transplantation, survival on the transplant waiting list, or survival after transplantation. The aim of this study was to develop a model that includes dialysis survival and survival after an eventual transplantation.
methodsFrom the Dutch renal replacement registry, patients of 16 years of age or older were included if they started RRT between 1995 and 2005, still underwent RRT at baseline (90 days after the start of RRT) and were not registered at a non-renal organ transplant waiting list (N = 13868). A prediction model of 10-year patient survival after baseline was developed through multivariate Cox regression analysis, in one half of the research group. Age at start, sex, primary renal disease (PRD) and therapy at baseline were included as possible predictors. A sensitivity analysis has been performed to determine whether listing on the transplant waiting list should be added. The predictive performance of the model was internally validated. Calibration and discrimination were computed in the other half of the research group. Another sensitivity analysis was to assess whether the outcomes differed if the model was developed and tested in two geographical regions, which were less similar than the original development and validation group. No external validation has been performed.
resultsSurvival probabilities were influenced by age, sex, PRD and therapy at baseline (p < 0.001). The calibration and discrimination both showed very reasonable results for the prediction model (C-index = 0.720 and calibration slope for the prognostic index = 1.025, for the 10 year survival). Adding registration on the waiting list for renal transplantation as a predictor did not improve the discriminative power of the model and was therefore not included in the model.
conclusionsWith the presented prediction model, it is possible to give a reasonably accurate estimation on the survival chances of patients who start with RRT, using a limited set of easily available data.
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