Prediction and monitoring of chronic kidney disease

Elise Schutte

Prediction and monitoring of chronic kidney disease

Vertaalde titel van de bijdrage: Predictie en monitoren van chronische nierinsufficiëntie

Elise Schutte

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Chronische nierschade (afgekort als CKD) wordt gedefinieerd als een verminderde nierfunctie of de aanwezigheid van tekenen van structurele nierschade die langer dan 3 maanden bestaan en de gezondheid beïnvloeden. CKD komt voor bij ongeveer 10% van de wereldbevolking en kan leiden tot eindstadium nierfalen, hart- en vaatziekten en sterfte. Gezien de grote impact die CKD heeft op gezondheid is het nodig om factoren te identificeren die kunnen voorspellen of de nierfunctie van een patiënt achteruit zal gaan. Biomarkers worden vaak gebruikt als zo’n voorspellende factor. Voor CKD zijn de belangrijkste biomarkers geschatte glomerulaire filtratiesnelheid (nierfunctie) en de mate van albuminurie (eiwit in de urine). Patiënten met een slechte nierfunctie en/of veel albuminurie moeten worden behandeld om nierfunctieachteruitgang te vertragen. Toch hebben deze biomarkers maar een beperkt voorspellend vermogen. In dit proefschrift zijn daarom additionele biomarkers onderzocht op hun mogelijk toegevoegde waarde. We hebben laten zien dat deze biomarkers CKD progressie helaas niet beter voorspellen dan nierfunctie en albuminurie. We adviseren om toekomstig onderzoek niet meer te richten op individuele biomarkers, zoals dat nu altijd gebeurt, maar op combinaties van biomarkers (biomarkerpanels). Zo zal waarschijnlijk nauwkeuriger de kans op CKD progressie voorspeld kunnen worden. Het beloop van nierfunctie in een patiënt wordt in de medische praktijk gedaan met het bepalen van het kreatinine in het bloed. Deze methode wordt bekritiseerd wat betreft nauwkeurigheid. Wij hebben laten zien dat nieuwe nierfunctiemarkers niet beter functioneren voor het monitoren van nierfunctiebeloop. Daarom is er vooralsnog geen reden om kreatinine te vervangen door andere biomarkers.

Vertaalde titel van de bijdrage	Predictie en monitoren van chronische nierinsufficiëntie
Originele taal-2	English
Kwalificatie	Doctor of Philosophy
Toekennende instantie	Rijksuniversiteit Groningen
Begeleider(s)/adviseur	Gansevoort, Ron, Supervisor Wolffenbuttel, Bruce, Supervisor Lambers Heerspink, Hiddo, Supervisor Lutgers, Helen, Co-supervisor
Datum van toekenning	7-jun.-2017
Plaats van publicatie	[Groningen]
Uitgever	Rijksuniversiteit Groningen
Gedrukte ISBN's	978-94-028-0676-2
Status	Published - 2017

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Title and contentsFinal publisher's version, 84,4 KB
Chapter 1Final publisher's version, 286 KB
Chapter 2Final publisher's version, 453 KB
Chapter 3Final publisher's version, 245 KB
Chapter 4Final publisher's version, 218 KB
Chapter 5Final publisher's version, 196 KB
Chapter 6Final publisher's version, 218 KB
Chapter 7Final publisher's version, 310 KB
Chapter 8Final publisher's version, 214 KB
Chapter 9Final publisher's version, 173 KB
Chapter 10Final publisher's version, 286 KB
Chapter 11Final publisher's version, 86,4 KB
Chapter 12Final publisher's version, 55,2 KB
Complete thesisFinal publisher's version, 2,05 MB
PropositionsFinal publisher's version, 338 KB

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title = "Prediction and monitoring of chronic kidney disease",

abstract = "Chronic kidney disease (CKD) is defined as impaired kidney function or signs of structural kidney damage, that persist for longer than 3 months and that have implications for health. CKD has a prevalence of approximately 10%, and can lead to end stage renal disease (ESRD), cardiovascular disease and mortality. Given the large impact CKD has on global health, it is necessary to identify factors that can predict whether a patient with CKD is likely to have disease progression. To this end biomarkers are often used as a predictive factor. For CKD the estimated glomerular filtration rate (kidney function) and presence of albuminuria (protein in the urine) are the most important biomarkers. Patients with severe impairment of kidney function or severe albuminuria need treatment to slow kidney function decline. However, these biomarkers have limited predictive performance. Therefore, additional biomarkers have been investigated in this thesis. We have shown that unfortunately these biomarkers do not outperform kidney function and albuminuria for the prediction of CKD progression. We advise to not focus future research on individual biomarkers, which is currently common practice, but on combinations of markers (biomarker panels) to accomplish a more accurate risk prediction for CKD progression. In clinical practice, monitoring of kidney function is performed using creatinine. This method is criticized with regards to its precision. We have shown that novel kidney function markers are not better for monitoring kidney function decline. Therefore there is currently no reason to replace creatinine by other biomarkers.",

author = "Elise Schutte",

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N2 - Chronic kidney disease (CKD) is defined as impaired kidney function or signs of structural kidney damage, that persist for longer than 3 months and that have implications for health. CKD has a prevalence of approximately 10%, and can lead to end stage renal disease (ESRD), cardiovascular disease and mortality. Given the large impact CKD has on global health, it is necessary to identify factors that can predict whether a patient with CKD is likely to have disease progression. To this end biomarkers are often used as a predictive factor. For CKD the estimated glomerular filtration rate (kidney function) and presence of albuminuria (protein in the urine) are the most important biomarkers. Patients with severe impairment of kidney function or severe albuminuria need treatment to slow kidney function decline. However, these biomarkers have limited predictive performance. Therefore, additional biomarkers have been investigated in this thesis. We have shown that unfortunately these biomarkers do not outperform kidney function and albuminuria for the prediction of CKD progression. We advise to not focus future research on individual biomarkers, which is currently common practice, but on combinations of markers (biomarker panels) to accomplish a more accurate risk prediction for CKD progression. In clinical practice, monitoring of kidney function is performed using creatinine. This method is criticized with regards to its precision. We have shown that novel kidney function markers are not better for monitoring kidney function decline. Therefore there is currently no reason to replace creatinine by other biomarkers.

AB - Chronic kidney disease (CKD) is defined as impaired kidney function or signs of structural kidney damage, that persist for longer than 3 months and that have implications for health. CKD has a prevalence of approximately 10%, and can lead to end stage renal disease (ESRD), cardiovascular disease and mortality. Given the large impact CKD has on global health, it is necessary to identify factors that can predict whether a patient with CKD is likely to have disease progression. To this end biomarkers are often used as a predictive factor. For CKD the estimated glomerular filtration rate (kidney function) and presence of albuminuria (protein in the urine) are the most important biomarkers. Patients with severe impairment of kidney function or severe albuminuria need treatment to slow kidney function decline. However, these biomarkers have limited predictive performance. Therefore, additional biomarkers have been investigated in this thesis. We have shown that unfortunately these biomarkers do not outperform kidney function and albuminuria for the prediction of CKD progression. We advise to not focus future research on individual biomarkers, which is currently common practice, but on combinations of markers (biomarker panels) to accomplish a more accurate risk prediction for CKD progression. In clinical practice, monitoring of kidney function is performed using creatinine. This method is criticized with regards to its precision. We have shown that novel kidney function markers are not better for monitoring kidney function decline. Therefore there is currently no reason to replace creatinine by other biomarkers.

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