Background: Cancer is a major and increasing public health problem, both in developed and developing countries. The International Agency for Research on Cancer (IARC) estimated 19.3 million new cancer cases worldwide in 2020. The greatest impact of the rising burden will occur in less developed countries, where about 82% of the world population resides. In this context, population studies are important sources on the etiology of cancer and the assessment of cancer trends over time. One of the ways to describe the incidence of cancer is to present data spatially through maps. There is great interest in understanding the geographic distribution of cancer cases, both by researchers and by health managers, to identify areas with excess cases and assess their association with regional characteristics. Objective: To perform a spatial and temporal analysis on the incidence of malignant neoplasms in the 18 cities belonging to the Regional Health Department of Barretos (RHD-V), from 2002 to 2018, describing the magnitude and distribution of the disease for the major cancer types. There will be a key focus in estimating the cancer burden in the state of Sao Paulo in 2020 and 2035, and stratifying, where applicable, by measures of social inequality. Methods: This is a time-series (ecological) population study that use a consolidated database where the quality of the information retrieved was assessed according to the IARC criteria. Cases for the major cancer types will be defined as all incident cases (between 2002 and 2018) in RHD-V residents, being obtained from the Population-Based Cancer Registry of Barretos at the Barretos Cancer Hospital. For assessment of geographic variations, the age-standardized incidence rates (ASR) stratified by year, age, and sex, will be calculated using the Segi world standard population. The ASRs will be represented in a thematic map for geographic visualization. Additionally, we will build an excess risk map and evaluate the spatial autocorrelation. For assessment of temporal variations, truncated (ages 35-74) age-standardized incidence rates will be initially visually examined using loess regression, and the estimated annual percentage change calculated using Joinpoint regression®. Synthetic and overlapping 10-year cohorts will be derived on subtracting the midpoints of 5-year age groups from the corresponding midyears of 5-year calendar time. An age-period-cohort (APC) model will be fitted on assuming the number of cases followed a Poisson random variable with the logarithm of the person-years at risk specified as an offset. Incidence rate ratios will be presented using the full APC model, constraining the linear component of the period or cohort effect to have zero slope. The significance of age and (non-linear) period and cohort effects will be tested via an analysis of deviance of the full APC and submodels. The geographic and temporal analyses will also, where possible, be assessed according to the socioeconomic status (SES). A prediction of the future incidence of cancer in the state of São Paulo will also be provided based on demographic projections assuming that the overall estimated rates estimated remain constant, as well as a trend-based prediction using NORDPRED. The predicted number of cases in five-year periods 2019-2023 through to 2034-2038 will estimated for the five major cancer sites and the residual cancer sites (excluding non-NMSC) to enable an estimate of the total cancer burden by age and sex, via the age-period-cohort prediction model NORDPRED, developed in R. All data management and analyses will be performed in R® and Stata®. This project is linked to a larger project approved by the Research Ethics Committee of the Barretos Cancer Hospital / Pio XII Foundation (CAAE: 33712320.4.0000.5437; registered number: 1954/2020).
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