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Labour productivity loss caused by premature deaths associated with breast cancer: results from Spain over a 10-year period

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Abstract

Background

Breast cancer is one of the most common cancers among women worldwide, and is the most common cause of cancer deaths in them. Given that such disease has a significant impact on middle-aged women, it can result in considerable labour productivity losses. The main objective of this study is therefore to analyse labour productivity losses and years of potential working life lost as a result of premature deaths from breast cancer in Spain over a 10-year period (2005–2014).

Method

To this end, by combining data on average salary (Salary Structure Survey), occupation (Active Population Survey) and deaths (death registration according to cause of death), a simulation model based on the human capital approach was constructed to estimate productivity losses associated with premature deaths caused by this disease.

Results

The results reveal that labour productivity losses in women are estimated to cost 2,137 million euros, as a result of the 22,716 deaths occurring during working age and the 292,848 years of potential productive life lost. This implies that breast cancer is responsible for 10.45% of all estimated female labour productivity losses caused by premature deaths in the reference year.

Conclusion

The article concludes by highlighting the major economic impact associated with breast cancer deaths and by pointing out future research areas.

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Data availability

Data are freely available at http://www.ine.es.

References

  1. SEOM: Las Cifras del Cáncer en España (2016) http://www.seom.org/seomcms/images/stories/recursos/LAS_CIFRAS_DEL_CANCER_EN_ESP_2016.pdf. Accessed Jan 2018

  2. Fitzmaurice C, Dicker D, Pain A, Hamavid H, Moradi-Lakeh M, MacIntyre MF, Allen C et al (2015) The global burden of cancer 2013. JAMA Oncol 1(4):505–527

    Article  Google Scholar 

  3. Cabanes A, Vidal E, Aragonés N, Pérez-Gómez B, Pollán M, Lope V, López-Abente G (2010) Cancer mortality trends in Spain: 1980–2007. Ann Oncol 21(Suppl 3):iii14–i20

    PubMed  Google Scholar 

  4. Broekx S, Den Hond E, Torfs R, Remacle A, Mertens R, D’Hooghe T, Neven P, Christiaens MR, Simoens S (2011) The costs of breast cancer prior to and following diagnosis. Eur J Health Econ 12(4):311–317

    Article  Google Scholar 

  5. Mujahid MS, Janz NK, Hawley ST, Griggs JJ, Hamilton AS, Katz SJ (2010) The impact of sociodemographic, treatment, and work support on missed work after breast cancer diagnosis. Breast Cancer Res Treat 119(1):213–220

    Article  Google Scholar 

  6. Drolet M, Maunsell E, Mondor M, Brisson C, Brisson J, Mâsse B, Deschênes L (2005) Work absence after breast cancer diagnosis: a population-based study. CMAJ 27(7):765–771 173(

    Article  Google Scholar 

  7. Luengo-Fernandez R, Leal J, Gray A, Sullivan R (2013) Economic burden of cancer across the European Union: a population-based cost analysis. Lancet Oncol 14(12):1165–1174

    Article  Google Scholar 

  8. Oliva-Moreno J (2012) Loss of labour productivity caused by disease and health problems: what is the magnitude of its effect on Spain’s Economy? Eur J Health Econ 13(5):605–614

    Article  Google Scholar 

  9. Grossman M (1972) The demand for health: a theoretical and empirical investigation. Columbia University Press, New York

    Google Scholar 

  10. Grossman M ( 2000) The human capital model of the demand for health. In: Culyer AJ, Newhouse JP (eds.). Handbook of health economics. Elsevier, Boston.

    Google Scholar 

  11. Instituto Nacional de Estadística (INEa). Encuesta de Estructura Salarial. http://www.ine.es/dyngs/INEbase/es/operacion.htm?c=Estadistica_C&cid=1254736176780&menu=resultados&idp=1254735573175 (2004–2015). Accessed Jan 2018

  12. Instituto Nacional de Estadística (INEb). Encuesta de Población Activa. http://www.ine.es/dyngs/INEbase/es/operacion.htm?c=Estadistica_C&cid=1254736176918&menu=resultados&idp=1254735976595 (2004–2015). Accessed Jan 2018

  13. Instituto Nacional de Estadística (INEc). Registro de Defunciones Según la Causa de Muerte. http://www.ine.es/dyngs/INEbase/es/operacion.htm?c=Estadistica_C&cid=1254736177025&menu=resultados&idp=1254735976596 (2004–2015). Accessed Jan 2018

  14. Clasificación estadística Internacional de Enfermedades y problemas relacionados con la Salud. Décima Revisión. http://ais.paho.org/classifications/Chapters/pdf/Volume3.pdf. Accessed 17 Jan 2018

  15. López-Bastida J, Oliva J, Antoñanzas F, García-Altés A, Gisbert R, Mar J, Puig-Junoy J (2010) Spanish recommendations on economic evaluation of health technologies. Eur J Health Econ 11(5):513–520

    Article  Google Scholar 

  16. Bank of Spain. GDP deflator. Economic indicators. https://www.bde.es/webbde/es/estadis/infoest/indeco.html. Accessed Jan 2018

  17. Hanly PA, Sharp L (2014) The cost of lost productivity due to premature cancer-related mortality: an economic measure of the cancer burden. BMC Cancer 14:224

    Article  Google Scholar 

  18. Hanly A, Soerjomataram I, Sharp L (2015) Measuring the societal burden of cancer: the cost of lost productivity due to premature cancer-related mortality in Europe. Int J Cancer 136(4):E136–E145

    Article  CAS  Google Scholar 

  19. Bradley CJ, Bednarek HL, Neumark D (2002) Breast cancer survival, work, and earnings. J Health Econ 21(5):757–779

    Article  Google Scholar 

  20. Bradley CJ, Yabroff KR, Dahman B, Feuer EJ, Mariotto A, Brown ML (2008) Productivity costs of cancer mortality in the United States: 2000–2020. J Natl Cancer Inst 17(24):1763–1770 100(

    Article  Google Scholar 

  21. Max W, Sung HY, Stark B (2009) The economic burden of breast cancer in California. Breast Cancer Res Treat 116(1):201–207

    Article  Google Scholar 

  22. Fredrik A, Jurate B, Eline AAS, Hilde L (2017) Economic productivity loss due to breast cancer in Norway -a case control study using the human capital approach. Nordic J Health Econ. https://doi.org/10.5617/njhe.2981

    Article  Google Scholar 

  23. Zheng Z, Yabroff KR, Guy GP Jr, Han X, Li C, Banegas MP, Ekwueme DU, Jemal A: Annual Medical Expenditure and Productivity Loss Among Colorectal, Female Breast, and Prostate Cancer Survivors in the United States. JNCI J Natl Cancer Inst. 2016; 108(5)

    Article  Google Scholar 

  24. Hanly P, Timmons A, Walsh PM, Sharp L (2012) Breast and prostate cancer productivity costs: a comparison of the human capital approach and the friction cost approach. Value Health 15(3):429–436

    Article  Google Scholar 

  25. Ekwueme DU, Guy GP Jr, Rim SH, White A, Hall IJ, Fairley TL, Dean HD (2014) Health and economic impact of breast cancer mortality in young women, 1970–2008. Am J Prev Med 46(1):71–79

    Article  Google Scholar 

  26. Łyszczarz B, Nojszewska E (2017) Productivity losses and public finance burden attributable to breast cancer in Poland, 2010–2014. BMC Cancer 17(1):676

    Article  Google Scholar 

  27. Carter HE, Schofield DJ, Shrestha R: The Productivity Costs of Premature Mortality Due to Cancer in Australia: Evidence from a Microsimulation Model. PLoS ONE. 2016; 11(12)

    Article  Google Scholar 

  28. Pearce A, Bradley C, Hanly P, O’Neill C, Thomas AA, Molcho M, Sharp L (2016) Projecting productivity losses for cancer-related mortality 2011–2030. BMC Cancer 16(1):804

    Article  Google Scholar 

  29. Oliva J, Lobo F, López-Bastida J, Zozaya N, Romay R (2005) Indirect costs of cervical and breast cancers in Spain. Eur J Health Econ 6(4):309–313

    Article  Google Scholar 

  30. Peña-Longobardo LM, Aranda-Reneo I, Oliva-Moreno J, Val-Castello J (2015) Pérdidas laborales ocasionadas por muertes prematuras en España: Un análisis para el periodo 2005–2009. Rev Esp Salud Pública 89:39–50

    Article  Google Scholar 

  31. Vicente-Herrero MT, Terradillos-García MJ, Ramírez-Iñiguez de la Torre, MV, Capdevila-García LM, Aguilar-Jiménez E, López-González AA (2012) El cáncer de mama en España. Aproximación a su coste económico por incapacidad temporal durante 2010. GAMO 11:351–357

    Google Scholar 

  32. Lidgren M, Wilking N, Jönsson B, Rehnberg C (2007) Resource use and costs associated with different states of breast cancer. Int J Technol Assess Health Care 23(2):223–231

    Article  Google Scholar 

  33. Yabroff KR, Kim Y (2009) Time costs associated with informal caregiving for cancer survivors. Cancer 115(18):4362–4373

    Article  Google Scholar 

  34. Leal J, Luengo-Fernandez R, Sullivan R, Witjes JA (2016) Economic Burden of Bladder Cancer Across the European Union. Eur Urol 69(3):438–447 (2016)

    Article  Google Scholar 

  35. Round J, Jones L, Morris S (2015) Estimating the cost of caring for people with cancer at the end of life: A modelling study. Palliat Med 29(10):899–907

    Article  Google Scholar 

  36. Liljas B (1998) How to calculate indirect costs in economic evaluations. Pharmacoeconomics 13:1–7

    Article  CAS  Google Scholar 

  37. Krol M, Brouwer W, Rutten F (2013) Productivity costs in economic evaluations: past, present, future. Pharmacoeconomics 31(7):537–549

    Article  Google Scholar 

  38. Krol M, Brouwer W (2014) How to estimate productivity costs in economic evaluations. Pharmacoeconomics 32(4):335–344

    Article  Google Scholar 

  39. Hanly P, Pearce A, Sharp L (2014) The cost of premature cancer-related mortality: a review and assessment of the evidence. Expert Rev Pharmacoecon Outcomes Res 14(3):355–377

    Article  Google Scholar 

  40. Koopmanschap MA, van Ineveld BM (1992) Towards a new approach for estimating indirect costs of disease. Soc Sci Med 34:1005–1010

    Article  CAS  Google Scholar 

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Funding

This study has received a no-restricted grant from Pfizer, within the framework of a research project conducted by the University of Castilla-La Mancha.

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Authors and Affiliations

  1. Department of Economic Analysis and Finance, Faculty of Law and Social Sciences in Toledo, University of Castilla La-Mancha, Cobertizo San Pedro Martir S/N, 45071, Toledo, Spain

    J. Oliva-Moreno & L. M. Peña-Longobardo

Authors
  1. J. Oliva-Moreno
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  2. L. M. Peña-Longobardo
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Contributions

JO and LP designed and carried out the analysis. JO and LP wrote the paper.

Corresponding author

Correspondence to L. M. Peña-Longobardo.

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Authors declare not competing interest.

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Oliva-Moreno, J., Peña-Longobardo, L.M. Labour productivity loss caused by premature deaths associated with breast cancer: results from Spain over a 10-year period. Breast Cancer Res Treat 172, 571–576 (2018). https://doi.org/10.1007/s10549-018-4963-z

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  • DOI: https://doi.org/10.1007/s10549-018-4963-z

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