{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,25]],"date-time":"2026-10-25T02:11:34Z","timestamp":1792894294487,"version":"4.5.0"},"reference-count":62,"publisher":"Oxford University Press (OUP)","issue":"7","license":[{"start":{"date-parts":[[2025,11,25]],"date-time":"2025-11-25T00:00:00Z","timestamp":1764028800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010269","name":"Wellcome Trust","doi-asserted-by":"publisher","award":["223499\/Z\/21\/Z"],"award-info":[{"award-number":["223499\/Z\/21\/Z"]}],"id":[{"id":"10.13039\/100010269","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010269","name":"Wellcome Trust","doi-asserted-by":"publisher","award":["301005\/Z\/23\/Z"],"award-info":[{"award-number":["301005\/Z\/23\/Z"]}],"id":[{"id":"10.13039\/100010269","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002997","name":"Dutch Kidney Foundation","doi-asserted-by":"publisher","award":["22OK2026"],"award-info":[{"award-number":["22OK2026"]}],"id":[{"id":"10.13039\/501100002997","id-type":"DOI","asserted-by":"publisher"}]},{"name":"VENI","award":["09150162310058"],"award-info":[{"award-number":["09150162310058"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,6,30]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background and hypothesis<\/jats:title>\n                    <jats:p>Guidelines recommend using risk prediction models for predicting kidney failure in chronic kidney disease (CKD). Many people with CKD have multiple long-term conditions (multimorbidity), which influences outcomes including kidney failure and mortality. This study validated the four-variable kidney failure risk equation (KFRE) in individuals with CKD, with and without multimorbidity, comparing performance of KFRE using creatinine and cystatin C to calculate estimated glomerular filtration rate (eGFR) and updated the model to account for competing mortality risks.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Observational cohort study using research-based (UK Biobank) and population-based cohorts (Stockholm Creatinine Measurements project: SCREAM). Multimorbidity was defined as two or more long-term conditions in addition to CKD. Kidney failure was defined as long-term dialysis or kidney transplantation. KFRE performance assessment included discrimination, calibration, and overall fit at 2 and 5 years. An updated model (using the same variables as KFRE) accounting for competing mortality risks was developed and validated.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>14\u2009998 of 24\u2009489 individuals in UK Biobank (61.2%) and 30\u2009147 of 42\u2009902 individuals in SCREAM (70.3%) had multimorbidity. Discrimination of KFRE was good (area under curve $\\ge $0.86 across eGFR equations in all cohorts, multimorbidity groups and time horizons). Kidney failure risk was under-estimated in people with multimorbidity in UK Biobank (observed\/expected (O\/E) ratio 1.75 at 5 years; eGFR creatinine). Conversely, calibration-in-the-large (O\/E ratio) at 5 years in SCREAM was 1.05 in the multimorbidity group (eGFR creatinine). Using cystatin C compared to creatinine did not improve model performance.<\/jats:p>\n                    <jats:p>Cumulative incidence of death was higher with multimorbidity compared to no multimorbidity. An updated model considering competing mortality improved calibration performance over KFRE, O\/E ratio 0.98 in multimorbidity group of the validation cohort (UK Biobank) at 5 years.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Competing mortality risk is important when predicting kidney failure, particularly for people with multimorbidity. An updated model accounting for competing mortality risk, permits improved model performance.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/ndt\/gfaf252","type":"journal-article","created":{"date-parts":[[2025,11,24]],"date-time":"2025-11-24T12:39:27Z","timestamp":1763987967000},"page":"1239-1252","source":"Crossref","is-referenced-by-count":3,"title":["The kidney failure risk equation in people with CKD and multimorbidity: the effect of competing mortality risks"],"prefix":"10.1093","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0148-0766","authenticated-orcid":false,"given":"Heather","family":"Walker","sequence":"first","affiliation":[{"name":"School of Cardiovascular and Metabolic Health, University of Glasgow , Glasgow 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