Evidence map›Paper›PMID 29844706›Full record

ArticleClinical epidemiology2018

Describing the association between socioeconomic inequalities and cancer survival: methodological guidelines and illustration with population-based data.

Aurélien Belot, Laurent Remontet, Bernard Rachet, Olivier Dejardin, Hadrien Charvat, Simona Bara, Anne-Valérie Guizard, Laurent Roche, Guy Launoy, Nadine Bossard

Open access · goldAbstract read
In one paragraph

Article in Clinical epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 17% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Observational
  8. 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

10 authors at 5 institutions in 2 countries.

Aurélien BelotCancer Survival Group, Department of Non-Communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Laurent RemontetDepartment of Biostatistics and Bioinformatics, Hospices Civils de Lyon, Lyon, France.
Bernard RachetCancer Survival Group, Department of Non-Communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Olivier DejardinNational Institute of Health and Medical Research U1086 ANTICIPE, Caen, France.
Hadrien CharvatPrevention Division, Center for Public Health Sciences, National Cancer Center, Tokyo, Japan.
Simona BaraManche General Cancer Registry, Centre Hospitalier Public du Cotentin, Cherbourg-en-Cotentin, France.
Anne-Valérie GuizardNational Institute of Health and Medical Research U1086 ANTICIPE, Caen, France.
Laurent RocheDepartment of Biostatistics and Bioinformatics, Hospices Civils de Lyon, Lyon, France.
Guy LaunoyNational Institute of Health and Medical Research U1086 ANTICIPE, Caen, France.
Nadine BossardDepartment of Biostatistics and Bioinformatics, Hospices Civils de Lyon, Lyon, France.
Université Claude Bernard Lyon 1 · FRCentre Hospitalier Universitaire de Caen Normandie · FRLondon School of Hygiene & Tropical Medicine · GBCentre François Baclesse · FRCentre Hospitalier Public du Cotentin · FR

Funding

Cancer Research UK 18348Cancer Research UK 18525
6 · The paper itself

Abstract

backgroundDescribing the relationship between socioeconomic inequalities and cancer survival is important but methodologically challenging. We propose guidelines for addressing these challenges and illustrate their implementation on French population-based data.

methodsWe analyzed 17 cancers. Socioeconomic deprivation was measured by an ecological measure, the European Deprivation Index (EDI). The Excess Mortality Hazard (EMH), ie, the mortality hazard among cancer patients after accounting for other causes of death, was modeled using a flexible parametric model, allowing for nonlinear and/or time-dependent association between the EDI and the EMH. The model included a cluster-specific random effect to deal with the hierarchical structure of the data.

resultsWe reported the conventional age-standardized net survival (ASNS) and described the changes of the EMH over the time since diagnosis at different levels of deprivation. We illustrated nonlinear and/or time-dependent associations between the EDI and the EMH by plotting the excess hazard ratio according to EDI values at different times after diagnosis. The median excess hazard ratio quantified the general contextual effect. Lip-oral cavity-pharynx cancer in men showed the widest deprivation gap, with 5-year ASNS at 41% and 29% for deprivation quintiles 1 and 5, respectively, and we found a nonlinear association between the EDI and the EMH. The EDI accounted for a substantial part of the general contextual effect on the EMH. The association between the EDI and the EMH was time dependent in stomach and pancreas cancers in men and in cervix cancer.

conclusionThe methodological guidelines proved efficient in describing the way socioeconomic inequalities influence cancer survival. Their use would allow comparisons between different health care systems.

Indexed as

cancer net survivalEuropean Deprivation Indexexcess mortality hazardflexible parametric modelsocioeconomic inequalities

Identifiers

PMID29844706
PMCPMC5961638
OpenAlexW2803196494

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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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.