Evidence map›Paper›PMID 30420618›Full record

SynthesisBritish journal of cancer2018

Assessment of proportional hazard assumption in aggregate data: a systematic review on statistical methodology in clinical trials using time-to-event endpoint.

Eliana Rulli, Francesca Ghilotti, Elena Biagioli, Luca Porcu, Mirko Marabese, Maurizio D'Incalci, Rino Bellocco, Valter Torri

Open access · hybridAbstract readSystematic Review
In one paragraph

Synthesis in British journal of cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 3 pooled it
4.6field-weighted citation impact, top 5% of its field
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

38 citing papers in PubMed, 3 syntheses or guidelines pooled it, 79 citations in OpenAlex.

  1. Pooled it
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  3. Pooled it
  4. Article
  5. In response to lean body mass index and hypertension risk in men: a nationwide epidemiological cohort study.Hypertension research : official journal of the Japanese Society of Hypertension · 2026
    Article
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  10. Interpretable Machine Learning for Survival Analysis.Biometrical journal. Biometrische Zeitschrift · 2025
    Review
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  15. Article
  16. Article
  17. Proportional Hazards Violations in Phase III Cancer Clinical Trials: A Potential Source of Trial Misinterpretation.Clinical cancer research : an official journal of the American Association for Cancer Research · 2024
    Article
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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

8 authors at 2 institutions in 2 countries.

Eliana RulliLaboratory of Methodology for Clinical Research, Oncology Department, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy. eliana.rulli@marionegri.it.
Francesca GhilottiLaboratory of Methodology for Clinical Research, Oncology Department, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.
Elena BiagioliLaboratory of Methodology for Clinical Research, Oncology Department, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.
Luca PorcuLaboratory of Methodology for Clinical Research, Oncology Department, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.
Mirko MarabeseLaboratory of Molecular Pharmacology, Oncology Department, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.
Maurizio D'IncalciLaboratory of Cancer Pharmacology, Oncology Department, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.
Rino BelloccoDepartment of Statistics and Quantitative Methods, University of Milano-Bicocca, Milano, Italy.
Valter TorriLaboratory of Methodology for Clinical Research, Oncology Department, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.
Mario Negri Institute for Pharmacological Research · ITUniversity of Milano-Bicocca · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe evaluation of the proportional hazards (PH) assumption in survival analysis is an important issue when Hazard Ratio (HR) is chosen as summary measure. The aim is to assess the appropriateness of statistical methods based on the PH assumption in oncological trials.

methodsWe selected 58 randomised controlled trials comparing at least two pharmacological treatments with a time-to-event as primary endpoint in advanced non-small-cell lung cancer. Data from Kaplan-Meier curves were used to calculate the relative hazard at each time point and the Restricted Mean Survival Time (RMST). The PH assumption was assessed with a fixed-effect meta-regression.

resultsIn 19% of the trials, there was evidence of non-PH. Comparison of treatments with different mechanisms of action was associated (P = 0.006) with violation of the PH assumption. In all the superiority trials where non-PH was detected, the conclusions using the RMST corresponded to that based on the Cox model, although the magnitude of the effect given by the HR was systematically greater than the one from the RMST ratio.

conclusionAs drugs with new mechanisms of action are being increasingly employed, particular attention should be paid on the statistical methods used to compare different types of agents.

Indexed as

Proportional Hazards ModelsRandomized Controlled Trials as TopicCarcinoma, Non-Small-Cell LungHumansLung Neoplasms

Identifiers

PMID30420618
PMCPMC6288087
OpenAlexW2899940828

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.