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Proposed minimum information guideline for kidney disease—research and clinical data reporting: a cross-sectional study
  1. Judit Kumuthini1,
  2. Christiaan van Woerden2,3,
  3. Andrew Mallett4,5,6,
  4. Lyndon Zass1,
  5. Melek Chaouch7,
  6. Michael Thompson8,
  7. Katherine Johnston2,
  8. Mamana Mbiyavanga2,
  9. Shakuntala Baichoo9,
  10. Zahra Mungloo-Dilmohamud9,
  11. Chirag Patel4,6,
  12. Nicola Mulder10
  1. 1 H3ABioNet, Centre for Proteomic & Genomic Research, Cape Town, South Africa
  2. 2 Department of Surgery, Division of Child Urology, University of Cape Town, Cape Town, South Africa
  3. 3 Global Child Health Group, Amsterdam University Medical Centers, Amsterdam, The Netherlands
  4. 4 KidGen Collaborative and AGHA Renal Genetics Flagships, Parkville, Victoria, Australia
  5. 5 Institute of Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
  6. 6 Royal Brisbane and Women’s Hospital, Brisbane, Queensland, Australia
  7. 7 Department of Parasitology, Institut Pasteur de Tunis, Tunis, Tunisia
  8. 8 National Institute of Mathematical Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
  9. 9 Department of Digital Technologies, University of Mauritius, Reduit, Mauritius
  10. 10 Department of Integrative Biomedical Sciences, Division of Computational Biology, University of Cape Town, Cape Town, South Africa
  1. Correspondence to Dr Judit Kumuthini; jkumuthini{at}


Objective This project aimed to develop and propose a standardised reporting guideline for kidney disease research and clinical data reporting, in order to improve kidney disease data quality and integrity, and combat challenges associated with the management and challenges of ‘Big Data’.

Methods A list of recommendations was proposed for the reporting guideline based on the systematic review and consolidation of previously published data collection and reporting standards, including PhenX measures and Minimal Information about a Proteomics Experiment (MIAPE). Thereafter, these recommendations were reviewed by domain-specialists using an online survey, developed in Research Electronic Data Capture (REDCap). Following interpretation and consolidation of the survey results, the recommendations were mapped to existing ontologies using Zooma, Ontology Lookup Service and the Bioportal search engine. Additionally, an associated eXtensible Markup Language schema was created for the REDCap implementation to increase user friendliness and adoption.

Results The online survey was completed by 53 respondents; the majority of respondents were dual clinician-researchers (57%), based in Australia (35%), Africa (33%) and North America (22%). Data elements within the reporting standard were identified as participant-level, study-level and experiment-level information, further subdivided into essential or optional information.

Conclusion The reporting guideline is readily employable for kidney disease research projects, and also adaptable for clinical utility. The adoption of the reporting guideline in kidney disease research can increase data quality and the value for long-term preservation, ensuring researchers gain the maximum benefit from their collected and generated data.

  • data standardisation
  • data reporting
  • FAIR
  • H3ABioNet
  • kidney disease
  • reporting guideline

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:

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  • Contributors The current project was designed by JK and supervised by NM. LZ, MC, CVW and AM were the primary developers of the reporting guidelines and drafted the manuscript. KJ, SB, ZMD and CP drafted and corrected the manuscript. MT and MM were the primary developers of the XML files. All authors read and approved the final manuscript.

  • Funding H3ABioNet is supported by the National Institutes of Health Common Fund under grant number U41HG006941. The content of this publication is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The Australian Genomics Health Alliance is supported by the National Health and Medical Research Council under grant number APP1113531.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement All data relevant to the study are included in the article or uploaded as supplementary information.

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