Evidence map›Paper›PMID 36759725›Full record

ArticleBritish journal of cancer2023

Immortal-time bias in older vs younger age groups: a simulation study with application to a population-based cohort of patients with colon cancer.

Sophie Pilleron, Camille Maringe, Eva J A Morris, Clémence Leyrat

Open access · hybridAbstract readComparative Study
In one paragraph

Article in British journal of cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
3.4field-weighted citation impact, top 6% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

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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

4 authors at 2 institutions in 2 countries.

Sophie PilleronNuffield Department of Population Health, University of Oxford, Big Data Institute, Old Road Campus, Oxford, OX3 7LF, UK. sophie.pilleron@lih.lu.ORCID http://orcid.org/0000-0001-7146-4740
Camille MaringeInequalities in Cancer Outcomes Network, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
Eva J A MorrisNuffield Department of Population Health, University of Oxford, Big Data Institute, Old Road Campus, Oxford, OX3 7LF, UK.ORCID http://orcid.org/0000-0002-1075-6544
Clémence LeyratDepartment of Medical Statistics, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.ORCID http://orcid.org/0000-0002-4097-4577
London School of Hygiene & Tropical Medicine · GBUniversity of Oxford · GB

Funding

Cancer Research UK 18525Cancer Research UK 29018Medical Research Council MR/T032448/1Medical Research Council MR/W021021/1
6 · The paper itself

Abstract

backgroundIn observational studies, the risk of immortal-time bias (ITB) increases with the likelihood of early death, itself increasing with age. We investigated how age impacts the magnitude of ITB when estimating the effect of surgery on 1-year overall survival (OS) in patients with Stage IV colon cancer aged 50-74 and 75-84 in England.

methodsUsing simulations, we compared estimates from a time-fixed exposure model to three statistical methods addressing ITB: time-varying exposure, delayed entry and landmark methods. We then estimated the effect of surgery on OS using a population-based cohort of patients from the CORECT-R resource and conducted the analysis using the emulated target trial framework.

resultsIn simulations, the magnitude of ITB was larger among older patients when their probability of early death increased or treatment was delayed. The bias was corrected using the methods addressing ITB. When applied to CORECT-R data, these methods yielded a smaller effect of surgery than the time-fixed exposure approach but effects were similar in both age groups.

conclusionITB must be addressed in all longitudinal studies, particularly, when investigating the effect of exposure on an outcome in different groups of people (e.g., age groups) with different distributions of exposure and outcomes.

Indexed as

Colonic NeoplasmsAgedBiasEnglandHumansProbabilityTime Factors

Identifiers

PMID36759725
PMCPMC10070415
OpenAlexW4319662753

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.