Evidence map›Paper›PMID 42528508›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Distributional Diagnosis and Calibration with Negative Controls for Outcome-wide Real-world Evidence.

Huiyuan Wang, Bingyu Zhang, Yuqing Lei, Yiwen Lu, Dazheng Zhang, Xinyao Jian, Yuru Zhu, Wenjie Hu, Haitao Chu, Yong Chen and 9 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

19 authors.

Huiyuan WangThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA.
Bingyu ZhangThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0001-7176-249X
Yuqing LeiThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA.
Yiwen LuThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA.
Dazheng ZhangThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA.
Xinyao JianThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA.
Yuru ZhuThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA.
Wenjie HuThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA.
Haitao ChuStatistical Research and Data Science Center, Pfizer Inc., New York, NY, USA.
Yong ChenStatistical Research and Data Science Center, Pfizer Inc., New York, NY, USA.
Marc A SuchardObservational Health Data Sciences and Informatics, New York, NY, USA.ORCID 0000-0001-9818-479X
Patrick B RyanObservational Health Data Sciences and Informatics, New York, NY, USA.
George HripcsakObservational Health Data Sciences and Informatics, New York, NY, USA.
David A AschLeonard Davis Institute of Health Economics, Philadelphia, PA, USA.
Yun LuCenter for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.
Bin YuDepartment of Statistics, University of California, Berkeley, Berkeley, CA, USA.
Martijn J SchuemieObservational Health Data Sciences and Informatics, New York, NY, USA.
Yumou QiuSchool of Mathematical Sciences and Center for Statistical Science, Peking University, Beijing, China.
Yong ChenThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0003-0835-0788

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glucagon-like peptide-1 receptor agonists (GLP-1RAs) have been linked to heterogeneous, potentially pleiotropic effects across organ systems, motivating outcome-wide comparative risk profiling in real-world data. A central challenge in such analyses is

Indexed as

Bias calibrationNegative control outcomesUnmeasured confounding

Identifiers

PMID42528508
PMCPMC13409211

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.