Journal
EPMA JOURNAL
Volume 10, Issue 2, Pages 137-152Publisher
SPRINGER INT PUBL AG
DOI: 10.1007/s13167-019-00169-y
Keywords
Prostate cancer; Incidence; Mortality; Mortality-to-incidence ratio; Human development index; Predictive preventive personalised medicine; Precision medicine
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AimTo examine the temporal patterns of the prostate cancer burden and its association with human development.Subject and methodsThe estimates of the incidence and mortality of prostate cancer for 87 countries were obtained from the Global Burden of Disease 2016 study for the period 1990 to 2016. The human development level of a country was measured using its human development index (HDI): a summary indicator of health, education, and income. The association between the burden of prostate cancer and the human development index (HDI) was measured using pairwise correlation and bivariate regression. Mortality-to-incidence ratio (MIR) was employed as a proxy for the survival rate of prostate cancer.ResultsGlobally, 1.4 million new cases of prostate cancer arose in 2016 claiming 380,916 lives which more than doubled from 579,457 incident cases and 191,687 deaths in 1990. In 2016, the age-standardised incidence rate (ASIR) was the highest in very high-HDI countries led by Australia with ASIR of 174.1/100,000 and showed a strong positive association with HDI (r=0.66); the age-standardised mortality rate (ASMR), however, was higher in low-HDI countries led by Zimbabwe with ASMR of 78.2/100,000 in 2016. Global MIR decreased from 0.33 in 1990 to 0.26 in 2016. Mortality-to-incidence ratio (MIR) exhibited a negative gradient (r=-0.91) with human development index with tenfold variation globally with seven countries recording MIR in excess of 1 with the USA recording the minimum MIR of 0.10.ConclusionThe high mortality and lower survival rates in less-developed countries demand all-inclusive solutions ranging from cost-effective early screening and detection to cost-effective cancer treatment. In tackling the rising burden of prostate cancer predictive, preventive and personalised medicine (PPPM) can play a useful role through prevention strategies, predicting PCa more precisely and accurately using a multiomic approach and risk-stratifying patients to provide personalised medicine.
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