Julien Prouvot1,2, Emilie Pambrun2, Cecile Couchoud3,4, Cecile Vigneau5, Sophie Roche6, Vincent Allot7, Jerome Potier8, Maud Francois9, Daniela Babici10, Camelia Prelipcean2, Olivier Moranne11,12. 1. EA2415, Université de Montpellier, Montpellier, France. 2. Service de Nephrologie, Dialyse et Apherese, Hôpital Universitaire de Caremeau, Nimes, France. 3. Registre REIN, Agence de la Biomedecine, Saint-Denis La Plaine, France. 4. CNRS, UMR 5558, Laboratoire de Biométrie et Biologie Evolutive, Equipe Biostatistique Santé, Villeurbanne, France. 5. CHU Pontchaillou, Service de Néphrologie-Dialyse-Transplantation, Université Rennes 1, IRSET 1085, Rennes, France. 6. Service de Néphrologie-Dialyse, CH Macon, Macon, France. 7. CHU Limoges, Service de Néphrologie, Dialyse, Transplantation, Limoges, France. 8. Service de Néphrologie-Dialyse, CH St Brieuc, Saint Brieuc, France. 9. CHU Tours, Service de Néphrologie-Dialyse-Transplantation, Tours, France. 10. Hôpital Emile Muller, Service Néphrologie-Dialyse, GHR MSA, Mulhouse, France. 11. EA2415, Université de Montpellier, Montpellier, France. olivier.moranne@chu-nimes.fr. 12. Service de Nephrologie, Dialyse et Apherese, Hôpital Universitaire de Caremeau, Nimes, France. olivier.moranne@chu-nimes.fr.
Abstract
INTRODUCTION: Clinical decision-making about care plans can be difficult for very elderly people with advanced chronic kidney disease (CKD). Current guidelines propose the use of prognostic tools predicting end stage renal disease (ESRD) to assist in a patient-centered shared decision-making approach. Our objective was to evaluate the existing risk model scores predicting ESRD, from data collected for a French prospective multicenter cohort of mainly octogenarians with advanced CKD. METHODS: We performed a rapid review to identify the risk model scores predicting ESRD developed from CKD patient cohorts and evaluated them with data from a prospective multicenter French cohort of elderly (> 75 years) patients with advanced CKD (estimated glomerular filtration rate [eGFR] < 20 mL/min/1.75m2), followed up for 5 years. We evaluated these scores (in absolute risk) for discrimination, calibration and the Brier score. For scores using the same time frame, we made a joint calibration curve and compared areas under the curve (AUCs). RESULTS: The PSPA cohort included 573 patients; their mean age was 83 years and their median eGFR was 13 mL/min/1.73 m2. At the end of follow-up, 414 had died and 287 had started renal replacement therapy (RRT). Our rapid review found 12 scores that predicted renal replacement therapy. Five were evaluated: the TANGRI 4-variable, DRAWZ, MARKS, GRAMS, and LANDRAY scores. No score performed well in the PSPA cohort: AUCs ranged from 0.57 to 0.65, and Briers scores from 0.18 to 0.25. CONCLUSIONS: The low predictiveness for ESRD of the scores tested in a cohort of octogenarian patients with advanced CKD underlines the need to develop new tools for this population.
INTRODUCTION: Clinical decision-making about care plans can be difficult for very elderly people with advanced chronic kidney disease (CKD). Current guidelines propose the use of prognostic tools predicting end stage renal disease (ESRD) to assist in a patient-centered shared decision-making approach. Our objective was to evaluate the existing risk model scores predicting ESRD, from data collected for a French prospective multicenter cohort of mainly octogenarians with advanced CKD. METHODS: We performed a rapid review to identify the risk model scores predicting ESRD developed from CKD patient cohorts and evaluated them with data from a prospective multicenter French cohort of elderly (> 75 years) patients with advanced CKD (estimated glomerular filtration rate [eGFR] < 20 mL/min/1.75m2), followed up for 5 years. We evaluated these scores (in absolute risk) for discrimination, calibration and the Brier score. For scores using the same time frame, we made a joint calibration curve and compared areas under the curve (AUCs). RESULTS: The PSPA cohort included 573 patients; their mean age was 83 years and their median eGFR was 13 mL/min/1.73 m2. At the end of follow-up, 414 had died and 287 had started renal replacement therapy (RRT). Our rapid review found 12 scores that predicted renal replacement therapy. Five were evaluated: the TANGRI 4-variable, DRAWZ, MARKS, GRAMS, and LANDRAY scores. No score performed well in the PSPA cohort: AUCs ranged from 0.57 to 0.65, and Briers scores from 0.18 to 0.25. CONCLUSIONS: The low predictiveness for ESRD of the scores tested in a cohort of octogenarian patients with advanced CKD underlines the need to develop new tools for this population.
Entities:
Keywords:
Dialysis; ESRD; Nephrogeriatry; Predictive model
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