Evidence map›Paper›PMID 41795009›Full record

ReviewPediatric nephrology (Berlin, Germany)2026

Promoting clinical trials in pediatric IgA nephropathy through extrapolation: an artificial intelligence-enhanced literature review of the disease in pediatrics sponsored by the Kidney Health Initiative.

David T Selewski, Eleanor M Kerr, Cecile Fajardo, Barbara S Gillespie, Sai Prasad N Iyer, Myda Khalid, Radko Komers, Koichi Nakanishi, Raoul D Nelson, Jun Oh and 7 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Pediatric nephrology (Berlin, Germany), 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. Article
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

17 authors.

David T SelewskiDepartment of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
Eleanor M KerrRipple Effect Communications, Inc, Rockville, MD, USA.
Cecile FajardoOtsuka Pharmaceutical Development & Commercialization, Princeton, NJ, USA.
Barbara S GillespieInternational Study of Glomerular Diseases, Florence, MA, USA.
Sai Prasad N IyerSeaStar Medical, Denver, CO, USA.
Myda KhalidRiley Hospital for Children, Indiana University, Bloomington, IN, USA.
Radko KomersTravere Therapeutics Inc, San Diego, CA, USA.
Koichi NakanishiDepartment of Child Health and Welfare (Pediatrics), Graduate School of Medicine, University of the Ryukyus, Ginowan, Okinawa, Japan.
Raoul D NelsonUniversity of Utah Health, Salt Lake City, UT, USA.
Jun OhUniversity Medical Center/at Hamburg, Hamburg/Eppendorf, Hamburg, Germany.
Bonnie SchneiderIgA Nephropathy Foundation, Wall Township, USA.
Lokesh N ShahOtsuka Pharmaceutical Development & Commercialization, Princeton, NJ, USA.
Nicholas J WebbSwedish Orphan Biovitrum AG, Basel, Switzerland.
Xuhui ZhongPeking University First Hospital, Beijing, China.
Grace SquillaciKidney Health Initiative, Washington, DC, USA.
Mark D LimKidney Health Initiative, Washington, DC, USA.
Howard TrachtmanDepartment of Pediatrics, Division of Nephrology, University of Michigan, 1150 W Medical Center Drive, Med Sci 1/ARF 2511, Ann Arbor, MI, 48109-1382, USA. howardtrachtman21@gmail.com.ORCID http://orcid.org/0009-0006-7778-292X

Funding

FDA HHS R18 FD005283
6 · The paper itself

Abstract

backgroundThere is an urgent need to evaluate the efficacy of novel therapeutics that have been approved for use in adults with IgA nephropathy (IgAN) in pediatric patients with this primary glomerular disease.

methodsTo explore the feasibility of deploying extrapolation to promote clinical trials in pediatric patients with IgA nephropathy (IgAN), an artificial intelligence (AI)-enhanced review of the published literature through 2023 was conducted to characterize the epidemiology and natural history of IgA nephropathy, summarize the clinical trial experience, and identify potential biomarkers for use in patient care and clinical trials.

resultsUsing Distiller SR® software to identify relevant articles and Elicit®, an artificial intelligence tool to extract content, 83 articles were included in the review. The clinical trial reports (n = 9) and biomarker studies (n = 33) were limited in scope. The natural history and epidemiology articles (n = 41) suggested that the severity of kidney histopathology at the time of diagnosis indicated a higher risk of disease progression while proteinuria < 0.5-1 mg/mg creatinine was associated with a more favorable prognosis.

conclusionsIn conjunction with the similar biological basis of the disease in pediatric and adult patients, these findings may enable the use of extrapolation in the design of clinical trials in pediatric patients with IgAN.

Indexed as

Artificial IntelligenceClinical Trials as TopicGlomerulonephritis, IGABiomarkersChildDisease ProgressionHumansPediatricsPrognosisBiomarkersArtificial intelligenceClinical trialsExtrapolationIgA nephropathyLiterature reviewPediatrics

Identifiers

PMID41795009
PMCPMC13337918

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Registered trials

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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.