Evidence map›Paper›PMID 32702147›Full record

GuidelineClinical and translational science2021

Standardized Data Structures in Rare Diseases: CDISC User Guides for Duchenne Muscular Dystrophy and Huntington's Disease.

Ariana P Mullin, Diane Corey, Emily C Turner, Richard Liwski, Daniel Olson, Jackson Burton, Sudhir Sivakumaran, Lynn D Hudson, Klaus Romero, Diane T Stephenson and 1 more

Abstract readPractice Guideline
In one paragraph

Guideline in Clinical and translational science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Fine-tuning large language models for rare disease concept normalization.Journal of the American Medical Informatics Association : JAMIA · 2024
    Article
  7. Article
  8. Fine-tuning Large Language Models for Rare Disease Concept Normalization.bioRxiv : the preprint server for biology · 2024
    Article
  9. Article
  10. Article
  11. Review
  12. 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

11 authors.

Ariana P MullinCritical Path Institute, Tucson, Arizona, USA.
Diane CoreyCritical Path Institute, Tucson, Arizona, USA.
Emily C TurnerCritical Path Institute, Tucson, Arizona, USA.
Richard LiwskiCritical Path Institute, Tucson, Arizona, USA.
Daniel OlsonCritical Path Institute, Tucson, Arizona, USA.
Jackson BurtonCritical Path Institute, Tucson, Arizona, USA.
Sudhir SivakumaranCritical Path Institute, Tucson, Arizona, USA.
Lynn D HudsonCritical Path Institute, Tucson, Arizona, USA.
Klaus RomeroCritical Path Institute, Tucson, Arizona, USA.
Diane T StephensonCritical Path Institute, Tucson, Arizona, USA.
Jane LarkindaleCritical Path Institute, Tucson, Arizona, USA.

Funding

Critical Path to Public Private PartnershipsU18FD005320 · FDA · CRITICAL PATH INSTITUTE · PI Klaus Romero · 2014 to 2026
$127.1M
FDA HHS U18 FD005320
6 · The paper itself

Abstract

Interest in drug development for rare diseases has expanded dramatically since the Orphan Drug Act was passed in 1983, with 40% of new drug approvals in 2019 targeting orphan indications. However, limited quantitative understanding of natural history and disease progression hinders progress and increases the risks associated with rare disease drug development. Use of international data standards can assist in data harmonization and enable data exchange, integration into larger datasets, and a quantitative understanding of disease natural history. The US Food and Drug Administration (FDA) requires the use of Clinical Data Interchange Consortium (CDISC) Standards in new drug submissions to help the agency efficiently and effectively receive, process, review, and archive submissions, as well as to help integrate data to answer research questions. Such databases have been at the core of biomarker qualification efforts and fit-for-purpose models endorsed by the regulators. We describe the development of CDISC therapeutic area user guides for Duchenne muscular dystrophy and Huntington's disease through Critical Path Institute consortia. These guides describe formalized data structures and controlled terminology to map and integrate data from different sources. This will result in increased standardization of data collection and allow integration and comparison of data from multiple studies. Integration of multiple data sets enables a quantitative understanding of disease progression, which can help overcome common challenges in clinical trial design in these and other rare diseases. Ultimately, clinical data standardization will lead to a faster path to regulatory approval of urgently needed new therapies for patients.

Indexed as

Biomedical ResearchDatabases, FactualDrug ApprovalDrug DevelopmentHealth Information ExchangeHumansHuntington DiseaseMuscular Dystrophy, DuchenneOrphan Drug ProductionRare DiseasesUnited StatesUnited States Food and Drug Administration

Identifiers

PMID32702147
PMCPMC7877853

What OpenQuestion holds

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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.