Trend and spatial analysis of prostate cancer mortality in the state of Sergipe, Brazil

Abstract

This is an ecological study with exploratory analysis of spatial and temporal data based on mortality data with respect to prostate cancer obtained from the Mortality Information System concerning residents of the state of Sergipe, Brazil between 2000 and 2015. The analysis of temporal trends was performed using the Joinpoint Regression Program through Poisson regression. Spatial analysis was performed using the empirical Bayesian model, Kernel analysis, Global Moran and Local indices. There were 1,986 deaths due to prostate cancer, most of which occurring after 60 years of age. An increasing, non-constant but significant trend in mortality rates was noted. The kernel density estimator showed hotspot densities of the highest rates of prostate cancer mortality in the north-eastern and central regions of the state. High-risk clusters were identified for prostate cancer mortality (I = 0.55, P<0.01). There was an increase in prostate cancer mortality rates and a heterogeneous geographic distribution of risk areas, with high-risk priority areas identified in certain regions of the state. These priority areas include the municipalities located in the Northeast (Amparo do São Francisco, Aquidabã, Canhoba, Cedro de São João and Telha), the West (Frei Paulo and Pedra Mole) and the south-western region of the state (Poço Verde and Simão Dias).

Clinical and epidemiological indicators and spatial analysis of leprosy cases in patients under 15 years old in an endemic area of Northeast Brazil: an ecological and time series study

“…The maps present certain disagreements regarding the occurrence of leprosy cases in the state of Sergipe because they use distinct techniques of spatial analysis. The Kernel estimator produces a continuous surface, with densities calculated at all locations, based on total number of cases and not considering the geographical boundaries of the municipalities 27 30 31. The Kernel technique presents greater advantages to the quick visualisation of areas that deserve attention, besides not being affected by political-administrative division, while the Moran technique, constructs maps considering the political-administrative divisions of the state and the clusters are based on the number of cases divided by the municipalities 27 30…”

“…This programme estimates the Annual Percentage Change (APC) of a segmented linear regression (Jointpoint regression) and identifies inflection points. Each inflection point reflects changes in the increase or decline of leprosy rates 27. The joinpoint regression provided the adjustment of a series of lines as well as their inflection points on a logarithmic scale by means of the annual trend test.…”

“…The result showed growth (positive APC values), reduction (APC negative values) or maintenance (APC value equal to zero) of the trend throughout the historical series analysed (2006–2014). Poisson regression is used to determine the number of segments required to properly explain the relationship between two variables 27. We considered the points of trend change that presented P-value<0.05.…”

Investigating beam range uncertainty in proton prostate treatment using pelvic-like biological phantoms

“…Prostate cancer is a malignant disease that threatens healthy men around the world (Al-Abdin and Al-Beeshi 2018, Góes et al 2018, Joachim et al 2018. Proton therapy is an effective method to treat prostate tumor with lower toxicity to organs at risk and normal tissues because of the dosimetric characteristics of proton Bragg Peaks (Mendenhall et al 2012, Paganetti and Kooy 2014, Guan et al 2015, Shao et al 2017.…”

Temporal trend of cancer mortality in a Brazilian state with a medium Human Development Index (1980–2018)

“…There are few studies on cancer incidence and mortality in Sergipe; existing studies are focused on a particular group or type of cancer [9][10][11][12][13][14][15] . This study aimed to describe the temporal trends of cancer mortality in Sergipe in a comprehensive way to compare the results with regions with similar HDI and signal priorities for actions against cancer.…”