↓ Skip to main content

Dove Medical Press

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

Overview of attention for article published in Clinical Epidemiology, May 2018
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (63rd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
5 X users

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
37 Mendeley
Title
Describing the association between socioeconomic inequalities and cancer survival: methodological guidelines and illustration with population-based data
Published in
Clinical Epidemiology, May 2018
DOI 10.2147/clep.s150848
Pubmed ID
Authors

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

Abstract

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

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 16%
Student > Bachelor 5 14%
Other 4 11%
Professor > Associate Professor 3 8%
Student > Doctoral Student 2 5%
Other 8 22%
Unknown 9 24%
Readers by discipline Count As %
Medicine and Dentistry 15 41%
Biochemistry, Genetics and Molecular Biology 2 5%
Mathematics 2 5%
Agricultural and Biological Sciences 2 5%
Nursing and Health Professions 1 3%
Other 4 11%
Unknown 11 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 June 2018.
All research outputs
#7,365,867
of 25,400,630 outputs
Outputs from Clinical Epidemiology
#283
of 793 outputs
Outputs of similar age
#119,675
of 339,257 outputs
Outputs of similar age from Clinical Epidemiology
#12
of 24 outputs
Altmetric has tracked 25,400,630 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 793 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.6. This one has gotten more attention than average, scoring higher than 63% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 339,257 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.