Journal of Clinical and Diagnostic Research (Oct 2015)

Competing Risk Approach (CRA) for Estimation of Disability Adjusted Life Years (DALY’s) for Female Breast Cancer in India

  • Radhika Kunnavil,
  • Chethana Thirthahalli,
  • Shalini Chandrashekar Nooyi,
  • NS Shivaraj,
  • Nandagudi Srinivasa Murthy

DOI
https://doi.org/10.7860/JCDR/2015/13082.6590
Journal volume & issue
Vol. 9, no. 10
pp. LC01 – LC04

Abstract

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Background: Competing Risk Approach (CRA) has been used to compute burden of disease in terms of Disability Adjusted Life Years (DALYs) based on a life table for an initially diseasefree cohort over time. Objective: To compute Years of Life Lost (YLL) due to premature mortality, Years of life lost due to Disability (YLD), DALYs and loss in expectation of life (LEL) using competing risk approach for female breast cancer patients for the year 2008 in India. Materials and Methods: The published data on breast cancer by age & sex, incidence & mortality for the year 2006-2008 relating to six population based cancer registries (PBCR) under Indian Council of Medical Research (ICMR), general mortality rates of 2007 in India, published in national health profile 2010; based on Sample Registration System (SRS) were utilized for computations. Three life tables were constructed by applying attrition of factors: (i) risk of death from all causes (‘a’; where a is the general death rate); (ii) risk of incidence and that of death from causes other than breast cancer (‘b-a+c’; where ‘b’ is the incidence of breast cancer and ‘c’ is the mortality of breast cancer); and (iii) risk of death from all other causes after excluding cancer mortality (‘a-c’). Taking the differences in Total Person Years Lived (TPYL), YLD and YLL were derived along with LEL. Results: CRA revealed that the DALYs were 40209 per 100,000 females in the life time of 0-70+ years with a LEL of 0.11 years per person. Percentage of YLL to DALYs was 28.20% in the cohort. Conclusion: The method of calculation of DALYs based on the CRA is simple and this will help to identify the burden of diseases using minimal information in terms of YLL, YLD, DALYs and LEL.

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