MétaCan
Menu
Back to cohort
Record W2103044501 · doi:10.1186/s13023-014-0170-0

A comparison of interventional clinical trials in rare versus non-rare diseases: an analysis of ClinicalTrials.gov

2014· article· en· W2103044501 on OpenAlexaboutno aff
Stuart Bell, Catrin Tudur Smith

Bibliographic record

VenueOrphanet Journal of Rare Diseases · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsnot available
FundersMedical Research CouncilUniversity of Liverpool
KeywordsClinical trialMedicineRare diseaseDiseaseOrphan drugPediatricsInternal medicineBioinformatics

Abstract

fetched live from OpenAlex

OBJECTIVES: To provide a comprehensive characterisation of rare disease clinical trials registered in ClinicalTrials.gov, and compare against characteristics of trials in non-rare diseases. DESIGN: Registry based study of ClinicalTrials.gov registration entries. METHODS: The ClinicalTrials.gov registry comprised 133,128 studies registered to September 27, 2012. By annotating medical subject heading descriptors to condition terms we could identify rare and non-rare disease trials. A total of 24,088 Interventional trials registered after January 1, 2006, conducted in the United States, Canada and/or the European Union were categorised as rare or non-rare. Characteristics of the respective trials were extracted and summarised with comparative statistics calculated where appropriate. MAIN OUTCOME MEASURES: Characteristics of interventional trials reported in the database categorised by rare and non-rare conditions to allow comparison. RESULTS: Of the 24,088 trials categorised 2,759 (11.5%) were classified as rare disease trials and 21,329 (88.5%) related to non-rare conditions. Despite the limitations of the database we found that rare disease trials differed to non-rare disease trials across all characteristics that we examined. Rare disease trials enrolled fewer participants (median 29 vs. 62), were more likely to be single arm (63.0% vs. 29.6%), non-randomised (64.5% vs. 36.1%) and open label (78.7% vs. 52.2%). A higher proportion of rare disease trials were terminated early (13.7% vs. 6.3%) and proportionally fewer rare disease studies were actively pursuing, or waiting to commence, enrolment (15.9% vs. 38.5%). CONCLUSION: Rare disease interventional trials differ from those in non-rare conditions with notable differences in enrolment, design, blinding and randomisation. However, clinical trials should aim to implement the highest trial design standards possible, regardless of whether diseases are rare or not.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.194
metaresearch head score (Gemma)0.500
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad)
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.990
Threshold uncertainty score0.994

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1940.500
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0100.011
Bibliometrics0.0400.069
Science and technology studies0.0010.002
Scholarly communication0.0070.007
Open science0.0030.007
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0080.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.082
GPT teacher head0.442
Teacher spread0.361 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designObservational
DomainMethods
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations147
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueOrphanet Journal of Rare DiseasesSame topicGenomics and Rare DiseasesFrench-language works237,207