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Exploring Cancer Incidence, Risk Factors, and Mortality in the Lleida Region: Interactive, Open-source R Shiny

Didac Florensa1,2,3, Jordi Mateo-Fornes1, Sergi Lopez Sorribes1

  • 1Department of Computer Engineering, University of Lleida, Lleida, Spain.

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Summary

This study developed an R Shiny application for cancer registries, enabling rapid data analysis and visualization. The tool aids in understanding cancer patterns, trends, and risk factors for better public health surveillance.

Keywords:
DockerR Shinycancer incidencecancer risk factors, cancer mortalitycloud computingdecision support systemmicroservices

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Area of Science:

  • Public Health Surveillance
  • Cancer Epidemiology
  • Health Informatics

Background:

  • Cancer incidence rates are crucial for public health surveillance and resource allocation.
  • Analyzing cancer data helps identify patterns, monitor trends, and inform health policy.
  • Understanding regional cancer situations is vital for effective public health strategies.

Purpose of the Study:

  • To design and implement an R Shiny application for cancer registries.
  • To enable rapid, user-friendly, and scalable descriptive and predictive analytics.
  • To provide a roadmap for developing similar data exploitation tools for population registries.

Main Methods:

  • Consolidated and cross-validated data in a population registry cancer database.
  • Developed an R Shiny online tool for data visualization and report generation.
  • Built a microservices cloud platform using NodeJS, MongoDB, Docker, and Docker Compose.

Main Results:

  • Successfully applied the tool to the Lleida region cancer registry.
  • Demonstrated analytics for risk factors (e.g., excess weight), second tumors, and mortality.
  • Highlighted lung cancer as the leading cause of death and breast cancer in women.

Conclusions:

  • Documented a successful methodology for exploiting population cancer registry data.
  • Proposed guidelines for developing similar data analysis tools.
  • Aimed to inspire entities to create accessible and transparent cancer data applications.