Evidence map›Paper›PMID 38859982›Full record

ArticleThe quarterly journal of economics2024

REPRESENTATION AND EXTRAPOLATION: EVIDENCE FROM CLINICAL TRIALS

Marcella Alsan, Maya Durvasula, Harsh Gupta, Joshua Schwartzstein, Heidi Williams

Abstract read
In one paragraph

Article in The quarterly journal of economics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Article
  4. Article
  5. Article
  6. A comprehensive analysis of female participation in cardiovascular trials involving the WCN investigator network.Netherlands heart journal : monthly journal of the Netherlands Society of Cardiology and the Netherlands Heart Foundation · 2025
    Article
  7. Review
  8. From Dialogue to Action: Community Recommendations for Inclusive Research Participation Among Underrepresented Populations.Health expectations : an international journal of public participation in health care and health policy · 2025
    Article
  9. Article
  10. Review
  11. Artificial intelligence: Applications in cardio-oncology and potential impact on racial disparities.American heart journal plus : cardiology research and practice · 2024
    Article
  12. Article
  13. COVID-19 pandemic's relationship with enrollment at US Alzheimer's Disease Research Centers.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024
    Article
  14. REPRESENTATION AND EXTRAPOLATION: EVIDENCE FROM CLINICAL TRIALSThe quarterly journal of economics · 2024
    Article
  15. Racial, Ethnic, and Geographic Diversity in Population Neuroscience.Current topics in behavioral neurosciences · 2024
    Review
  16. 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

5 authors.

Marcella AlsanHarvard Kennedy School and National Bureau of Economic Research, United States.
Maya DurvasulaStanford University, United States.
Harsh GuptaStanford University, United States.
Joshua SchwartzsteinHarvard Business School, United States.
Heidi WilliamsStanford University and National Bureau of Economic Research, United States.

Funding

Understanding and Improving Healthcare Decision-Making and Outcomes for People Living with Alzheimer's Disease and Related DementiasP01AG005842 · NIA · NATIONAL BUREAU OF ECONOMIC RESEARCH · PI KOSALI ILAYPERUMA SIMON · 1986 to 2026
$56.5M
NIA NIH HHS P01 AG005842
6 · The paper itself

Abstract

This article examines the consequences and causes of low enrollment of Black patients in clinical trials. We develop a simple model of similarity-based extrapolation that predicts that evidence is more relevant for decision-making by physicians and patients when it is more representative of the group being treated. This generates the key result that the perceived benefit of a medicine for a group depends not only on the average benefit from a trial but also on the share of patients from that group who were enrolled in the trial. In survey experiments, we find that physicians who care for Black patients are more willing to prescribe drugs tested in representative samples, an effect substantial enough to close observed gaps in the prescribing rates of new medicines. Black patients update more on drug efficacy when the sample that the drug is tested on is more representative, reducing Black-white patient gaps in beliefs about whether the drug will work as described. Despite these benefits of representative data, our framework and evidence suggest that those who have benefited more from past medical breakthroughs are less costly to enroll in the present, leading to persistence in who is represented in the evidence base.

Indexed as

D91I12I14O31O33

Identifiers

PMID38859982
PMCPMC11164133

What OpenQuestion holds

Textmetadata
LicenceTDM
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.