INTRODUCTION: Patient registries play an important role in obtaining real-world evidence of the cost-effectiveness of treatments. However, their implementation is costly and sometimes infeasible in many middle-income countries (MICs). We explored the combination of data-mining and a large claims database to estimate the direct healthcare costs of HER2-positive breast cancer (BC) treatment in Iran and the fraction of total costs from trastuzumab use.METHOD: We performed a retrospective analysis of claims data from the Iran Social Security Organization, a health insurer which covers approximately 50%(~40 million) of the Iranian population, in the period of 21/03/2011-20/03/2014. A data-mining algorithm using R software and validated using patient dossiers in the Cancer Research Center identified 1295 patients and divided them into the three main HER2-positive breast cancer stages (early, loco-regional and advanced). A payer perspective was used to calculate the absolute and relative direct costs of healthcare services associated with the treatment of HER2-positive breast cancer in the public and private healthcare systems.RESULTS: The number of women totaled 802 (early), 125 (loco-regional) and 218 (advanced). The mean age[SD] was 45[10], 46[10] and 48[10] years, respectively, while mean follow-up in all stages was approximately one year. Average costs of direct healthcare care in early, loco-regional and advanced stages were €11,796 (95%CI: €9,356-€12,498), €8,253 (95%CI: €6,843-€10,002), and €17,742 (95%CI: €15,720-€19,505), respectively. Trastuzumab accounted for the largest share of total costs in all three stages (range: 53-76%).CONCLUSION: Wherever comprehensive patient registries are infeasible or costly, real-world costs can be estimated through claims databases and data-mining strategies. Using this method, real-world costs have been estimated in Iran. The stage-specific cost estimates derived from this study can be used to perform real-world cost-effectiveness analyses of therapies for HER2-positive BC and support healthcare financing decisions.

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Persistent URL dx.doi.org/10.1371/journal.pone.0205079, hdl.handle.net/1765/110672
Journal PLoS ONE
Citation
Ansaripour, A. (Amir), Zendehdel, K. (Kazem), Tadayon, N. (Niki), Sadeghi, F. (Fatemeh), Uyl-de Groot, C.A, & Redekop, W.K. (2018). Use of data-mining to support real-world cost analyses: An example using HER2-positive breast cancer in Iran. PLoS ONE, 13(10). doi:10.1371/journal.pone.0205079