Evidence map›Paper›PMID 38592333›Full record

SynthesisStatistical methods in medical research2024

Methods for non-proportional hazards in clinical trials: A systematic review.

Maximilian Bardo, Cynthia Huber, Norbert Benda, Jonas Brugger, Tobias Fellinger, Vaidotas Galaune, Judith Heinz, Harald Heinzl, Andrew C Hooker, Florian Klinglmüller and 6 more

Abstract readSystematic Review
In one paragraph

Synthesis in Statistical methods in medical research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
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  6. Reduced risk of dementia with recombinant zoster vaccine in US adults age 65 or older.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
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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

16 authors.

Maximilian BardoDepartment of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany.ORCID 0000-0003-3554-5273
Cynthia HuberDepartment of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany.ORCID 0000-0003-2035-3682
Norbert BendaDepartment of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany.
Jonas BruggerCenter for Medical Data Science, Section of Medical Statistics, Medical University of Vienna, Vienna, Austria.
Tobias FellingerAgentur für Gesundheit und Ernährungssicherheit (AGES), Vienna, Austria.ORCID 0000-0001-9474-2731
Vaidotas GalauneDepartment of Pharmacy, Uppsala University, Uppsala, Sweden.
Judith HeinzDepartment of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany.
Harald HeinzlCenter for Medical Data Science, Section of Clinical Biometrics, Medical University of Vienna, Vienna, Austria.ORCID 0000-0003-4711-2379
Andrew C HookerDepartment of Pharmacy, Uppsala University, Uppsala, Sweden.ORCID 0000-0002-2676-5912
Florian KlinglmüllerAgentur für Gesundheit und Ernährungssicherheit (AGES), Vienna, Austria.
Franz KönigCenter for Medical Data Science, Section of Medical Statistics, Medical University of Vienna, Vienna, Austria.
Tim MathesDepartment of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany.
Martina MittlböckCenter for Medical Data Science, Section of Clinical Biometrics, Medical University of Vienna, Vienna, Austria.ORCID 0000-0003-1097-4047
Martin PoschCenter for Medical Data Science, Section of Medical Statistics, Medical University of Vienna, Vienna, Austria.
Robin RistlCenter for Medical Data Science, Section of Medical Statistics, Medical University of Vienna, Vienna, Austria.ORCID 0000-0002-4163-9236
Tim FriedeDepartment of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany.ORCID 0000-0001-5347-7441

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For the analysis of time-to-event data, frequently used methods such as the log-rank test or the Cox proportional hazards model are based on the proportional hazards assumption, which is often debatable. Although a wide range of parametric and non-parametric methods for non-proportional hazards has been proposed, there is no consensus on the best approaches. To close this gap, we conducted a systematic literature search to identify statistical methods and software appropriate under non-proportional hazard. Our literature search identified 907 abstracts, out of which we included 211 articles, mostly methodological ones. Review articles and applications were less frequently identified. The articles discuss effect measures, effect estimation and regression approaches, hypothesis tests, and sample size calculation approaches, which are often tailored to specific non-proportional hazard situations. Using a unified notation, we provide an overview of methods available. Furthermore, we derive some guidance from the identified articles.

Indexed as

Clinical Trials as TopicProportional Hazards ModelsHumansSample SizeSoftwareCox modellog-rank testnon-proportional hazardsright-censored observationssurvival analysis

Identifiers

PMID38592333
PMCPMC11162097

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.