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Kidney Week

Abstract: FR-PO904

IgA Nephropathy (IgAN) in Pediatric Patients: A Kidney Health Initiative (KHI) Artificial Intelligence (AI)-Assisted Literature Review

Session Information

Category: Glomerular Diseases

  • 1402 Glomerular Diseases: Clinical, Outcomes, and Therapeutics

Authors

  • Selewski, David T., Medical University of South Carolina, Charleston, South Carolina, United States
  • Kerr, Eleanor M., Ripple Effect, Rockville, Maryland, United States
  • Fajardo, Cecile, Otsuka America Inc, San Francisco, California, United States
  • Gillespie, Barbara S., University of North Carolina, Chapel Hill, North Carolina, United States
  • Iyer, Sai Prasad N., SeaStar Medical, Denver, Colorado, United States
  • Khalid, Myda, Indiana University, Bloomington, Indiana, United States
  • Komers, Radko, Travere Therapeutics Inc, San Diego, California, United States
  • Nakanishi, Koichi, University of the Ryukyus, Nishihara, Okinawa, Japan
  • Nelson, Raoul D., University of Utah Health, Salt Lake City, Utah, United States
  • Oh, Jun, Universitat Hamburg, Hamburg, Hamburg, Germany
  • Shah, Lokesh N., Otsuka America Inc, San Francisco, California, United States
  • Webb, Nicholas J., GSK plc, Brentford, United Kingdom
  • Zhong, Xuhui, Peking University, Beijing, Beijing, China
  • Trachtman, Howard, University of Michigan, Ann Arbor, Michigan, United States

Group or Team Name

  • KHI Pediatric IgA Nephropathy Work Group.
Background

With proteinuria as an accepted reasonably likely surrogate endpoint in IgAN, availability of accelerated approval of new therapies has resulted in a surge of randomized clinical trials (RCT) for adults. There is a need to characterize the disease in pediatric patients and define a regulatory pathway for approval of new therapies in this age group. The KHI convened a work group to address this knowledge gap and conducted an AI-supported literature review of pediatric IgAN to determine similarities and differences in children and adolescents vs adults.

Methods

Published literature through 2023 was compiled using DistillerSR software and reviewed manually in a 2-step process by title, abstract, and full text if needed. Articles that combined adult and pediatric patients without the ability to analyze pediatric patients separately, that did not report IgAN as a separate entity, had a sample size less than 10, case reports, reviews, duplicate reports, and articles that focused on IgA vasculitis were excluded. Relevant content was extracted using Elicit, an artificial intelligence tool, validated, and reviewed by the work group.

Results

84 articles were included after preliminary review and classified into the following subgroups: Natural History/Epidemiology (n=41), Clinical Trials (n=10) and Biomarkers (n=33). Prompts were engineered for use in the AI extraction tool, allowing for systematic extraction of study characteristics, e.g., study design, trial region, sample size, patient characteristics, and outcome measures. Analysis of the papers is underway and is anticipated to be completed by August 2024.

Conclusion

AI-supported methods provide a novel strategy for future extensive literature reviews. They can identify in-scope articles, extract and expedite the review of large amounts of relevant data, and foster wider application in clinical research. The KHI-sponsored project will identify areas of similarity and difference regarding the clinical course, response to therapy, and clinically relevant endpoints in pediatric vs adults with IgAN to guide extrapolation of data from adults with IgAN to affected children and facilitate the performance of RCT in the pediatric age range.