Evidence map›Paper›PMID 41686506›Full record

ArticleClinical journal of the American Society of Nephrology : CJASN2026

Relationship between Total Kidney Volume and eGFR in Autosomal Dominant Polycystic Kidney Disease.

Alan S L Yu, Chelsie Parker, Lilian Golzarri-Arroyo, Douglas P Landsittel, Rekha Garg, Edmund C Lee, Arlene B Chapman, Frederic F Rahbari-Oskoui, Michal Mrug, Peter C Harris and 1 more

Abstract read
In one paragraph

Article in Clinical journal of the American Society of Nephrology : CJASN, 2026. 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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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Alan S L YuDivision of Nephrology and Hypertension, Jared Grantham Kidney Institute, University of Kansas Medical Center, Kansas City, Kansas.ORCID 0000-0002-1776-2533
Chelsie ParkerDepartment of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, Indiana.ORCID 0000-0001-5262-9693
Lilian Golzarri-ArroyoDepartment of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, Indiana.ORCID 0000-0002-1221-6701
Douglas P LandsittelDepartment of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, Indiana.
Rekha GargRegulus Therapeutics, San Diego, California.
Edmund C LeeRegulus Therapeutics, San Diego, California.ORCID 0000-0001-5843-247
Arlene B ChapmanDivision of Nephrology, University of Chicago School of Medicine, Chicago, Illinois.ORCID 0000-0002-6030-8694
Frederic F Rahbari-OskouiDepartment of Internal Medicine, Emory University School of Medicine, Atlanta, Georgia.ORCID 0000-0001-8933-4880
Michal MrugDivision of Nephrology, Department of Veterans Affairs Medical Center, University of Alabama at Birmingham, Birmingham, Alabama.
Peter C HarrisDivision of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota.ORCID 0000-0002-5304-6593
Vicente E TorresDivision of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota.ORCID 0000-0003-2008-1576

Funding

Polycystin Function Resource Development CoreU54DK126126 · NIDDK · UNIVERSITY OF KANSAS MEDICAL CENTER · PI DARREN P. WALLACE · 2020 to 2026
$5.8M
Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP) IV: Prognosis for End-Stage Renal Disease and Biomarker ValidationR01DK113111 · NIDDK · UNIVERSITY OF KANSAS MEDICAL CENTER · PI YU, ALAN S · 2017 to 2021
$3.5M
NIDDK NIH HHS R01 DK113111NIDDK NIH HHS U54 DK126126Regulus Therapeutics N/A
6 · The paper itself

Abstract

key pointsIn autosomal dominant polycystic kidney disease, there is a linear relationship between the log-transformed total kidney volume and eGFR. There is a predictable change in the rate of eGFR decline with reduction in kidney growth rate. This framework can be used to determine treatment effect to support accelerated approval of drugs for polycystic kidney disease.

backgroundTotal kidney volume (TKV) is accepted by the US Food and Drug Administration as a surrogate end point that is reasonably likely to predict clinical benefit in autosomal dominant polycystic kidney disease and the most commonly used response biomarker for proof-of-concept intervention trials. However, the magnitude of treatment effect on TKV that would be predictive of a meaningful improvement in a clinical outcome, such as eGFR, is unknown. Inference of this from observational studies has previously been approached by examining interindividual variance in the relationship between TKV and GFR slopes over time.

methodsWe developed a novel approach to modeling the intraindividual relationship between TKV and eGFR. Patients from the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease and Halt Progression of Polycystic Kidney Disease Study A dataset were stratified by Mayo Imaging Class (MIC). Linear mixed models were fitted to eGFR with a fixed effect of log(TKV) and random intercepts, and the average slope within each MIC was estimated.

resultsWe found that within each MIC, there is a consistent, linear relationship between log(TKV) and eGFR. The model predicts that within classes 1C-1E, for each 1% point per year reduction in TKV growth rate, the rate of eGFR decline would be reduced by 0.40-0.52 ml/min per 1.73 m 2 per year.

conclusionsWe have developed a new model that provides a framework for defining the magnitude of treatment effect on TKV that would support accelerated approval of a drug for autosomal dominant polycystic kidney disease.

Indexed as

ADPKDCKDclinical epidemiologyprogression

Identifiers

PMID41686506
PMCPMC13143477

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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.