Abstract
10560 Background: Cancer is a major cause of morbidity and mortality worldwide. Ten million cancer-related deaths were recorded in 2020, a rise of 66% over the preceding two decades. Malignancies of the breast, lung, prostate and colon account for over 40% of new cancer diagnoses worldwide. This study observes trends in oncological disease burden among higher (HIC’s) and lower-middle-income countries (LMIC’s) between 2000 and 2019. Methods: Mortality to incidence ratios (MIR) were calculated using the Global Burden of Disease database by extracting age standardized mortality and incidence rates per 100 000 for breast, lung, prostate and colorectal cancer for the years 2000-2019. The European Union (EU) 15+ countries were taken to represent HIC’s. 8 of the LMIC’s in the World Bank group were included as their data quality rating was 3/5 or higher. This cohort comprised Egypt, Sri Lanka, Ukraine, El Salvador, Republic of Moldova, Philippines, Kyrgyzstan and Nicaragua. Breast, lung, colorectal and prostate cancer were included as the tumor types with highest global incidence. Median MIR (with interquartile range) were computed for each LMIC and EU15+ groups for males and females for each of the four tumor types. Results: Between 2000 and 2019 median MIR for the LMIC group was higher than for EU15+ group for all four cancer types in males and females. Wilcoxon rank sum of the 2019 data showed a statistically significant difference (p <0.001) in MIR between HIC’s and LMIC’s (table 1). For breast, prostate and colorectal cancer the difference in median MIR between LMIC group and EU15+ decreased over the observation period, for lung cancer the difference increased. Conclusions: Globally there are wide geographical variations in MIR. Cancer outcomes appear consistently worse in LMIC’s compared to HIC’s. Availability of cancer screening, access to treatment and risk-factor prevalence may contribute to the above trends. Identifying these regional disparities provides an opportunity to target resource allocation to regions that would derive the greatest benefit. [Table: see text]
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