Evidence map›Paper›PMID 41888306›Full record

ArticleClinical and experimental nephrology2026

Integrating nephron number into risk stratification for IgA nephropathy.

Yuya Yamaguchi, Takaya Sasaki, Nobuo Tsuboi, Hirokazu Marumoto, Yusuke Okabayashi, Kotaro Haruhara, Go Kanzaki, Kentaro Koike, Vivette D D'Agati, John F Bertram and 2 more

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Article in Clinical and experimental nephrology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Are noninvasive measurements of nephron number achievable in humans?Current opinion in nephrology and hypertension · 2026
    Review
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

12 authors.

Yuya Yamaguchi *Division of Nephrology and Hypertension, Department of Internal Medicine, The Jikei University School of Medicine, 3-25-8 Nishi-Shimbashi, Minato-Ku, Tokyo, Japan.
Takaya Sasaki *Division of Nephrology and Hypertension, Department of Internal Medicine, The Jikei University School of Medicine, 3-25-8 Nishi-Shimbashi, Minato-Ku, Tokyo, Japan.
Nobuo TsuboiDivision of Nephrology and Hypertension, Department of Internal Medicine, The Jikei University School of Medicine, 3-25-8 Nishi-Shimbashi, Minato-Ku, Tokyo, Japan. tsuboi-n@jikei.ac.jp.ORCID http://orcid.org/0000-0002-5407-5265
Hirokazu MarumotoDivision of Nephrology and Hypertension, Department of Internal Medicine, The Jikei University School of Medicine, 3-25-8 Nishi-Shimbashi, Minato-Ku, Tokyo, Japan.
Yusuke OkabayashiDivision of Nephrology and Hypertension, Department of Internal Medicine, The Jikei University School of Medicine, 3-25-8 Nishi-Shimbashi, Minato-Ku, Tokyo, Japan.
Kotaro HaruharaDivision of Nephrology and Hypertension, Department of Internal Medicine, The Jikei University School of Medicine, 3-25-8 Nishi-Shimbashi, Minato-Ku, Tokyo, Japan.
Go KanzakiDivision of Nephrology and Hypertension, Department of Internal Medicine, The Jikei University School of Medicine, 3-25-8 Nishi-Shimbashi, Minato-Ku, Tokyo, Japan.
Kentaro KoikeDivision of Nephrology and Hypertension, Department of Internal Medicine, The Jikei University School of Medicine, 3-25-8 Nishi-Shimbashi, Minato-Ku, Tokyo, Japan.
Vivette D D'AgatiDepartment of Pathology and Cell Biology, Columbia University Medical Center, New York, NY, USA.
John F BertramDepartment of Anatomy and Developmental Biology, Biomedicine Discovery Institute, Monash University, Melbourne, Australia.
Toshiharu NinomiyaDepartment of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Takashi YokooDivision of Nephrology and Hypertension, Department of Internal Medicine, The Jikei University School of Medicine, 3-25-8 Nishi-Shimbashi, Minato-Ku, Tokyo, Japan.

Funding

Japan Society for the Promotion of Science London 21K08238Japan Society for the Promotion of Science London 25K11551
6 · The paper itself

Abstract

backgroundThe International IgA Nephropathy (IgAN) prediction tool provides reliable risk estimates for kidney outcomes using clinical and histopathological variables. However, additional structural biomarkers may further improve prognostic precision. This study investigated whether incorporating estimated nephron number enhances the predictive performance of the International IgAN prediction tool.

methodsWe conducted a post hoc analysis of 218 adult patients with primary IgAN diagnosed with native kidney biopsy between 2007 and 2017. Nephron number per kidney was estimated by multiplying estimated kidney cortical volume derived from unenhanced computed tomography by nonsclerotic glomerular density obtained from kidney biopsy specimens. The 5 year risk of a composite kidney outcome (≥ 50% decline in estimated glomerular filtration rate [eGFR] or initiation of kidney replacement therapy) was calculated using the International IgAN prediction tool. Discrimination and reclassification were assessed using Harrell's C statistics, the category-free net reclassification improvement (NRI), and the integrated discrimination improvement (IDI).

resultsThe cohort had a mean age of 42.6 years, 61.5% were male, and the mean eGFR was 60.7 mL/min/1.73 m

conclusionsEstimated nephron number provides additive prognostic value beyond established clinical and pathological predictors in patients with IgAN, supporting its role as a complementary biomarker in risk stratification.

Indexed as

Glomerulonephritis, IGANephronsAdultBiopsyFemaleGlomerular Filtration RateHumansMaleMiddle AgedPredictive Value of TestsPrognosisRetrospective StudiesRisk AssessmentRisk FactorsTomography, X-Ray ComputedGlomerulonephritisNephronPredictionPrognosisRisk AssessmentValidation

Identifiers

PMID41888306

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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.