Evidence map›Paper›PMID 41992905›Full record

ArticleResearch synthesis methods2026

The hazards of using hazard ratios from proportional hazard models in indirect treatment comparisons.

Ziren Jiang, Jialing Liu, Weili He, Joseph Cappelleri, Satrajit Roychoudhury, Yong Chen, Haitao Chu

Abstract read
In one paragraph

Article in Research synthesis methods, 2026. 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
–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

2 citing papers in PubMed.

  1. Article
  2. 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

7 authors.

Ziren JiangDivision of Biostatistics and Health Data Science, https://ror.org/017zqws13University of Minnesota Twin Cities, Minneapolis, USA.ORCID https://orcid.org/0000-0002-5830-327X
Jialing LiuDivision of Biostatistics and Health Data Science, https://ror.org/017zqws13University of Minnesota Twin Cities, Minneapolis, USA.
Weili HeMedical Affairs and Health Technology Assessment Statistics, Data and Statistical Sciences, https://ror.org/02g5p4n58AbbVie Inc, USA.
Joseph CappelleriData Sciences and Analytics, https://ror.org/01xdqrp08Pfizer Inc, USA.ORCID https://orcid.org/0000-0001-9586-0748
Satrajit RoychoudhuryData Sciences and Analytics, https://ror.org/01xdqrp08Pfizer Inc, USA.
Yong ChenDepartment of Biostatistics, Epidemiology and Informatics, https://ror.org/04h81rw26University of Pennsylvania Perelman School of Medicine, Philadelphia, USA.
Haitao ChuDivision of Biostatistics and Health Data Science, https://ror.org/017zqws13University of Minnesota Twin Cities, Minneapolis, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Indirect treatment comparison (ITC) is widely used to estimate the comparative effectiveness of treatments when head-to-head trials are unavailable. For the typical scenario of anchored ITC where one trial compares drug A to drug C (AC trial) and another compares drug B to drug C (BC trial), the comparative effectiveness of drugs A versus B is calculated by subtracting (or dividing) the relative treatment effect of A versus C in the AC trial by that of B versus C in the BC trial, assuming the covariate distributions in both trials are balanced. This operation is valid only if the chosen effect measure is transitive, that is, in a three-arm randomized trial of drugs A, B, and C, the direct treatment effect of A versus B equals the indirect treatment effect of A versus B through their comparisons to C. For survival outcomes, many ITCs use the hazard ratio (HR) as the effect measure. In this article, we demonstrate that HR is generally not transitive and should be used with caution. As more reliable alternatives, we recommend effect measures with better transitivity properties: the restricted mean survival time (RMST) difference, the landmark survival probability difference (or ratio) at a prespecified time point, and the average hazard with survival weights (AH-SW) difference.

Indexed as

Proportional Hazards ModelsAlgorithmsComparative Effectiveness ResearchComputer SimulationData Interpretation, StatisticalHumansProbabilityRandomized Controlled Trials as TopicResearch DesignSurvival AnalysisTreatment Outcomeindirect treatment comparisonmatching-adjusted indirect comparisonpopulation-adjusted indirect comparisonstatistical transitivitytime-to-event outcome

Identifiers

PMID41992905
PMCPMC13126216

What OpenQuestion holds

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LicenceCC BY-ND
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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.