IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0040917.html
   My bibliography  Save this article

Influence of Socioeconomic Status on Survival of Hepatocellular Carcinoma in the Ontario Population; A Population-Based Study, 1990–2009

Author

Listed:
  • Nathaniel Jembere
  • Michael A Campitelli
  • Morris Sherman
  • Jordan J Feld
  • Wendy Lou
  • Stuart Peacock
  • Eric Yoshida
  • Murray D Krahn
  • Craig Earle
  • Hla-Hla Thein

Abstract

Background: Research has shown that people from higher socioeconomic status (SES) have better hepatocellular carcinoma (HCC) survival outcomes, although no such research has been carried out in Canada. We aimed to assess if an association between SES and HCC survival existed in the Canadian context. Methodology/Prinicpal Findings: We conducted a population-based cohort study linking HCC cases identified in the Ontario Cancer Registry between 1990 and 2009 to administrative and hospital data. Logistic regression and chi-squared tests were used to evaluate associations between SES (income quintile) and covariates. The Kaplan-Meier method was used to estimate survival. Sequential analysis of the proportional-hazards models were used to determine the association between SES and HCC survival controlling for potential prognostic covariates. During the period 1990–2009, 5,481 cases of HCC were identified. A significant association was found between SES and curative treatment (p = 0.0003), but no association was found between SES and non-curative treatment (p = 0.064), palliative treatment (p = 0.680), or ultrasound screening (p = 0.615). The median survival for the lowest SES was 8.5 months, compared to 8.8 months for the highest SES group. The age- and sex-adjusted proportional-hazards model showed statistically significant difference in HCC survival among the SES groups, with hazard ratio 0.905 (95% confidence intervals 0.821, 0.998) when comparing highest to lowest SES group. Further adjustments indicated that potentially curative treatment was the likely explanation for the association between SES and HCC survival. Conclusions/Significance: Our findings suggest that a 10% HCC survival advantage exists for the higher SES groups. This association between SES and HCC survival is most likely a reflection of lack of access to care for low SES groups, revealing inequities in the Canadian healthcare system.

Suggested Citation

  • Nathaniel Jembere & Michael A Campitelli & Morris Sherman & Jordan J Feld & Wendy Lou & Stuart Peacock & Eric Yoshida & Murray D Krahn & Craig Earle & Hla-Hla Thein, 2012. "Influence of Socioeconomic Status on Survival of Hepatocellular Carcinoma in the Ontario Population; A Population-Based Study, 1990–2009," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-10, July.
  • Handle: RePEc:plo:pone00:0040917
    DOI: 10.1371/journal.pone.0040917
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0040917
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0040917&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0040917?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Krieger, N., 1992. "Overcoming the absence of socioeconomic data in medical records: Validation and application of a census-based methodology," American Journal of Public Health, American Public Health Association, vol. 82(5), pages 703-710.
    2. Gorey, K.M. & Luginaah, I.N. & Bartfay, E. & Fung, K.Y. & Holowaty, E.J. & Wright, F.C. & Hamm, C. & Kanjeekal, S.M., 2011. "Effects of socioeconomic status on colon cancer treatment accessibility and survival in Toronto, Ontario, and San Francisco, California, 1996-2006," American Journal of Public Health, American Public Health Association, vol. 101(1), pages 112-119.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hla-Hla Thein & Kika Anyiwe & Nathaniel Jembere & Brian Yu & Prithwish De & Craig C Earle, 2017. "Effects of socioeconomic status on esophageal adenocarcinoma stage at diagnosis, receipt of treatment, and survival: A population-based cohort study," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-20, October.
    2. Hla-Hla Thein & Yao Qiao & Ahmad Zaheen & Nathaniel Jembere & Gonzalo Sapisochin & Kelvin K W Chan & Eric M Yoshida & Craig C Earle, 2017. "Cost-effectiveness analysis of treatment with non-curative or palliative intent for hepatocellular carcinoma in the real-world setting," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-20, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cots, Francesc & Mercade, Lluc & Castells, Xavier & Salvador, Xavier, 2004. "Relationship between hospital structural level and length of stay outliers: Implications for hospital payment systems," Health Policy, Elsevier, vol. 68(2), pages 159-168, May.
    2. Martin Gaechter & Peter Schwazer & Engelbert Theurl, 2012. "Stronger Sex but Earlier Death: A Multi-level Socioeconomic Analysis of Gender Differences in Mortality in Austria," DANUBE: Law and Economics Review, European Association Comenius - EACO, issue 1, pages 1-23, March.
    3. Michelle Sholzberg & Tara Gomes & David N Juurlink & Zhan Yao & Muhammad M Mamdani & Andreas Laupacis, 2016. "The Influence of Socioeconomic Status on Selection of Anticoagulation for Atrial Fibrillation," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-12, February.
    4. Schulz, Jan & Mayerhoffer, Daniel M., 2021. "A network approach to consumption," BERG Working Paper Series 173, Bamberg University, Bamberg Economic Research Group.
    5. Clarke, Christina A. & Miller, Tim & Chang, Ellen T. & Yin, Daixin & Cockburn, Myles & Gomez, Scarlett L., 2010. "Racial and social class gradients in life expectancy in contemporary California," Social Science & Medicine, Elsevier, vol. 70(9), pages 1373-1380, May.
    6. Sean A. P. Clouston & Marcie S. Rubin & Jo C. Phelan & Bruce G. Link, 2016. "A Social History of Disease: Contextualizing the Rise and Fall of Social Inequalities in Cause-Specific Mortality," Demography, Springer;Population Association of America (PAA), vol. 53(5), pages 1631-1656, October.
    7. Floriane Calocer & Olivier Dejardin & Karine Droulon & Guy Launoy & Gilles Defer, 2018. "Socio-economic status influences access to second-line disease modifying treatment in Relapsing Remitting Multiple Sclerosis patients," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-12, February.
    8. Allison C. Morgan & Nicholas LaBerge & Daniel B. Larremore & Mirta Galesic & Jennie E. Brand & Aaron Clauset, 2022. "Socioeconomic roots of academic faculty," Nature Human Behaviour, Nature, vol. 6(12), pages 1625-1633, December.
    9. Keyes, Katherine M. & March, Dana & Link, Bruce G. & Chilcoat, Howard D. & Susser, Ezra, 2013. "Do socio-economic gradients in smoking emerge differently across time by gender? Implications for the tobacco epidemic from a pregnancy cohort in California, USA," Social Science & Medicine, Elsevier, vol. 76(C), pages 101-106.
    10. Jinani Jayasekera & Eberechukwu Onukwugha & Christopher Cadham & Donna Harrington & Sarah Tom & Francoise Pradel & Michael Naslund, 2019. "An ecological approach to monitor geographic disparities in cancer outcomes," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-14, June.
    11. Justin Stoler & John R Weeks & Richard Appiah Otoo, 2013. "Drinking Water in Transition: A Multilevel Cross-sectional Analysis of Sachet Water Consumption in Accra," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-11, June.
    12. Michael Adjemian & Jeffrey Williams, 2009. "Using census aggregates to proxy for household characteristics: an application to vehicle ownership," Transportation, Springer, vol. 36(2), pages 223-241, March.
    13. Philibert, M.D. & Pampalon, R. & Hamel, D. & Thouez, J.-P. & Loiselle, C.G., 2007. "KW - Quebec: A local-scale evaluation system," Social Science & Medicine, Elsevier, vol. 64(8), pages 1651-1664, April.
    14. Masayoshi Oka, 2022. "Census-Tract-Level Median Household Income and Median Family Income Estimates: A Unidimensional Measure of Neighborhood Socioeconomic Status?," IJERPH, MDPI, vol. 20(1), pages 1-23, December.
    15. Stacey L Tannenbaum & Monique Hernandez & D Dandan Zheng & Daniel A Sussman & David J Lee, 2014. "Individual- and Neighborhood-Level Predictors of Mortality in Florida Colorectal Cancer Patients," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-10, August.
    16. Stafford, Mai & Duke-Williams, Oliver & Shelton, Nicola, 2008. "Small area inequalities in health: Are we underestimating them?," Social Science & Medicine, Elsevier, vol. 67(6), pages 891-899, September.
    17. M. Manos & Chanda Ho & Rosemary Murphy & Valentina Shvachko, 2013. "Physical, Social, and Psychological Consequences of Treatment for Hepatitis C," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 6(1), pages 23-34, March.
    18. Andrea S Gershon & Deva Thiruchelvam & Shawn Aaron & Matthew Stanbrook & Nicholas Vozoris & Wan C Tan & Eunice Cho & Teresa To, 2019. "Socioeconomic status (SES) and 30-day hospital readmissions for chronic obstructive pulmonary (COPD) disease: A population-based cohort study," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-16, May.
    19. Neugebauer Romain & Chandra Malini & Paredes Antonio & J. Graham David & McCloskey Carolyn & S. Go Alan, 2013. "A Marginal Structural Modeling Approach with Super Learning for a Study on Oral Bisphosphonate Therapy and Atrial Fibrillation," Journal of Causal Inference, De Gruyter, vol. 1(1), pages 21-50, June.
    20. Ping Yin & Lan Mu & Marguerite Madden & John Vena, 2014. "Hierarchical Bayesian modeling of spatio-temporal patterns of lung cancer incidence risk in Georgia, USA: 2000–2007," Journal of Geographical Systems, Springer, vol. 16(4), pages 387-407, October.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0040917. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.