Evidence map›Paper›PMID 28769547›Full record

ArticleShanghai archives of psychiatry2017

Win Ratio -An Intuitive and Easy-To-Interpret Composite Outcome in Medical Studies.

Hongyue Wang, Jing Peng, Juila Z Zheng, Bokai Wang, Xiang Lu, Chongshu Chen, Xin M Tu, Changyong Feng

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Shanghai archives of psychiatry, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Article
  4. Article
  5. On recurrent-event win ratio.Statistical methods in medical research · 2022
    Article
  6. Article
  7. Article
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

8 authors.

Hongyue WangDepartment of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, USA.
Jing PengDepartment of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, USA.
Juila Z ZhengDepartment of Microbiology and Immunology, McGill University, Montreal, QC, Canada.
Bokai WangDepartment of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, USA.
Xiang LuDepartment of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, USA.
Chongshu ChenDepartment of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, USA.
Xin M TuDepartment of Family Medicine and Public Health, UC San Diego School of Medicine, La Jolla, CA, USA.
Changyong FengDepartment of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In medical studies with multiple outcomes, researchers always need to make choices as to whether to use a composite outcome (after combining multiple outcomes) as their primary outcome. In this paper we review a new measurement of the treatment effect - win ratio, which can be easily used in studies with prioritized multiple outcomes. We also propose some research topics to be done in this area.

Indexed as

proportional hazards modelsurvival functionstime-to-event data

Identifiers

PMID28769547
PMCPMC5518256

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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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.