Evidence map›Paper›PMID 38704598›Full record

ArticleSystematic reviews2024

Protocol for a systematic review of the application of the kidney failure risk equation and Oxford classification in estimating prognosis in IgA nephropathy.

Michael Toal, Ruth Fergie, Michael Quinn, Christopher Hill, Ciaran O'Neill, Alexander P Maxwell

Abstract read
In one paragraph

Article in Systematic reviews, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Michael ToalCentre for Public Health, Queen's University of Belfast, Belfast, BT12 6AB, Northern Ireland. mtoal11@qub.ac.uk.ORCID 0000-0002-1690-9206
Ruth FergieCentre for Public Health, Queen's University of Belfast, Belfast, BT12 6AB, Northern Ireland.
Michael QuinnCentre for Public Health, Queen's University of Belfast, Belfast, BT12 6AB, Northern Ireland.
Christopher HillRegional Nephrology Unit, Belfast City Hospital, Lisburn Road, BT9 7BA, Belfast, Northern Ireland.
Ciaran O'NeillCentre for Public Health, Queen's University of Belfast, Belfast, BT12 6AB, Northern Ireland.
Alexander P MaxwellCentre for Public Health, Queen's University of Belfast, Belfast, BT12 6AB, Northern Ireland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIgA nephropathy (IgAN) is a common cause of chronic kidney disease (CKD) and end-stage renal disease (ESRD). Outcomes are highly variable and predicting risk of disease progression at an individual level is challenging. Accurate risk stratification is important to identify individuals most likely to benefit from treatment. The Kidney Failure Risk Equation (KFRE) has been extensively validated in CKD populations and predicts the risk of ESRD at 2 and 5 years using non-invasive tests; however, its predictive performance in IgAN is unknown. The Oxford classification (OC) describes pathological features demonstrated on renal biopsy that are associated with adverse clinical outcomes that may also inform prognosis. The objective of this systematic review is to compare the KFRE with the OC in determining prognosis in IgAN.

methodsA systematic review will be conducted and reported in line with PRISMA guidelines (PRISMA-P checklist attached as Additional file 1). Inclusion criteria will be cohort studies that apply the KFRE or OC to determine the risk of CKD progression or ESRD in individuals with IgAN. Multiple databases will be searched in duplicate to identify relevant studies, which will be screened first by title, then by abstract and then by full-text analysis. Results will be collated for comparison. Risk of bias and confidence assessments will be conducted independently by two reviewers, with a third reviewer available if required. DISCUSSION: Identifying individuals at the highest risk of progression to ESRD is challenging in IgAN, due to the heterogeneity of clinical outcomes. Risk prediction tools have been developed to guide clinicians; however, it is imperative that these aids are accurate and reproducible. The OC is based on observations made by specialist renal pathologists and may be open to observer bias, therefore the utility of prediction models incorporating this classification may be diminished, particularly as in the future novel biomarkers may be incorporated into clinical practice. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42022364569.

Indexed as

Disease ProgressionGlomerulonephritis, IGAKidney Failure, ChronicSystematic Reviews as TopicBiopsyHumansPrognosisRenal Insufficiency, ChronicRisk AssessmentChronic kidney diseaseDisease progressionEnd-stage renal diseaseGlomerulonephritisIgA nephropathyKidney failureKidney Failure Risk EquationOxford classificationPrediction toolRenal biopsy

Identifiers

PMID38704598
PMCPMC11070080

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.