MEASURING BRAZIL’S OUTCOMES OF BREAST CANCER MANAGEMENT GIVEN ITS GDP PER CAPITA: A WORLDWIDE COMPARISON

Introduction: Breast cancer (BC) treatment vary considerably over different parts of the world. There is a correlation between level of income and efficacy of its management. Therefore, countries of a lower level of income must try to maximize its cost-effectiveness strategies. The ratio of mortality/incidence (RMI) is an indicator of performance in this case. It measures how many women suffering of BC will eventually die from the disease. By modelling the RMI with the gross domestic product per capita (GDPpc) over the different countries, we can then analyze which of them are outperforming and underperforming, in relation to cost-effectiveness. METHODS We got our data from two different sources. The GDP per capita was taken from the World Bank database. The mortality and incidence of breast cancer data were taken from the GLOBOCAN. Our performance proxy was the RMI. We created a model with ordinary least squares (OLS) that tried to explain the RMI by the GDPpc of the countries. After that, we saw that each country had a real RMI and an estimated RMI based on its GDP per capita. Primary objective is to measure the distance between real RMI and estimated RMI (giving the Residues). If the Residue is positive, it means that the country has a real RMI higher than the predicted. This implies that the mortality is higher than expected, given the countrys incidence of breast cancer and GDP per capita. So, the country does not have a good cost/effectiveness performance. If the Residue is negative the result is the oposite. We calculated this Residue for Brazil, and analyzed how the country is performing in terms of management of breast cancer cases. RESULTS We collected data of GDPpc, incidence and mortality of breast cancer for 148 countries. Our regression with OLS yielded the following model: RMI = 1,15279-0,0829404*ln (GDPpc). It says that each 1% of increase in GDP per capita results in predicted decrease of 0,08 in RMI. The higher the GDPpc, the lower the mortality. Brazil had a real RMI of 0,21. The model predicted that, given the income only, Brazil should have an RMI of 0,35. It gives a Residue of -0,13. DISCUSSION The analysis showed that Brazil has a smaller RMI than predicted by its GDP per capita. Therefore, the country has a good cost-effectiveness profile. Our study is a hypothesis generator, and has some limitations, such as the possible heterogeneity of data from the different countries and the analysis limited to the RMI index.