Evidence map›Paper›PMID 41288427›Full record

ReviewNEJM evidence2025

Evaluating Treatment Effects with Patient-Response-Related Outcomes in Comparative Clinical Trials.

Lu Mao, Lu Tian, Bo Huang, Paul G Richardson, Ethan B Ludmir, Michael D Hughes, Lee-Jen Wei

Abstract readReview
In one paragraph

Review in NEJM evidence, 2025. 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

7 authors.

Lu MaoDepartment of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA.
Lu TianDepartment of Biomedical Data Science, Stanford University, Stanford, CA, USA.
Bo HuangPfizer Inc., New York, NY, USA.
Paul G RichardsonDana-Farber Cancer Institute, Boston, MA, USA.
Ethan B LudmirDepartment of Gastrointestinal Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Michael D HughesDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Lee-Jen WeiDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Funding

Statistical and Data Management Center (SDMC), AIDS Clinical Trials Group (ACTG)UM1AI068634 · NIAID · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Marlene Ann Cooper, Michael David Hughes · 2011 to 2026
$246.6M
NIAID NIH HHS UM1 AI068634
6 · The paper itself

Abstract

AbstractIn comparative clinical investigations for nearly all disease types, patient responses - signifying clinically meaningful improvements in health or reductions in disease burden - are routinely employed as key end points for assessing treatment activity or efficacy. Trials typically use the response rate to summarize treatment effects, a metric with limitations for investigating the temporal profile of the effect. In this Clinical Trials Workshop, the authors present a novel approach for analyzing time to response and duration of response in clinical trials using, as an example, data from the JAVELIN Renal-101 trial of avelumab and axitinib versus sunitinib for treating renal cell carcinoma.

Indexed as

Antineoplastic AgentsCarcinoma, Renal CellClinical Trials as TopicKidney NeoplasmsAntibodies, MonoclonalAntibodies, Monoclonal, HumanizedAxitinibHumansImidazolesIndazolesSunitinibTreatment OutcomeAntibodies, MonoclonalAntibodies, Monoclonal, HumanizedAntineoplastic AgentsavelumabAxitinibImidazolesIndazolesSunitinib

Identifiers

PMID41288427
PMCPMC13692082

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.