Evidence map›Paper›PMID 35680722›Full record

ArticleTherapeutic innovation & regulatory science2022

Quantifying Diversity and Representation in Pivotal Trials Leading to Marketing Authorization in Europe.

Zachary Smith, Emily Botto, Kenneth Getz

Abstract read
PubMed Publisher
In one paragraph

Article in Therapeutic innovation & regulatory science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.9field-weighted citation impact, top 29% of its field
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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Real-world evidence: new opportunities for osteoporosis research. Recommendations from a Working Group from the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO).Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2023
    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

3 authors at 1 institution in 1 country.

Zachary SmithTufts CSDD, Boston, MA, USA. zachary.smith605922@tufts.edu.ORCID 0000-0002-6764-1350
Emily BottoTufts CSDD, Boston, MA, USA.
Kenneth GetzTufts CSDD, Boston, MA, USA.
Tufts University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFollowing up on a study from 2019, Tufts CSDD collected and analyzed data on demographic disparities and representation in pivotal trials supporting the marketing authorization of novel drugs and biologics approved in Europe between 2007 and 2019.

methodsData were collected from products' EPAR, the EUDRACT database, and other publicly available sources, and compared to indication-specific demographic data or a census estimate. In total, data were collected on 446 drugs and 943 pivotal trials.

resultsResults indicated that gender demographic data were only reported for 80.7% of pivotal trials, and that racial and ethnicity demographic data were reported less often (64.1% and 29.9% of pivotal trials, respectively). Results also indicated that non-white racial identities were under-represented by more than 20% in nearly half or more of pivotal trials.

conclusionsGuidelines encouraging the reporting of patient demographic data are insufficient and availability of the data is problematic. The available data suggest that under-representation in pivotal trials is widespread.

Indexed as

Drug ApprovalRacial GroupsEthnicityEuropeHumansMarketingDemographicsDiversityEthnicityPivotal trialsRaceRepresentation

Identifiers

PMID35680722
OpenAlexW4282925973

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.