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Colossus: software for radiation epidemiological studies with big data.

Eric Giunta1, Dawson Stutzman1, Sarah S Cohen2

  • 1Kansas State University, Manhattan, KS, United States of America.

Journal of Radiological Protection : Official Journal of the Society for Radiological Protection
|April 16, 2025
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Summary
This summary is machine-generated.

Colossus is a new R package for scalable survival analysis of large radiation epidemiology datasets. It accurately analyzes millions of rows, validating its performance against existing software and published results.

Keywords:
Cox proportional hazardMillion Person StudyPoisson regressionbig dataradiation epidemiology

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Area of Science:

  • Epidemiology
  • Biostatistics
  • Radiation Science

Background:

  • Growing need for survival analysis software for large-scale radiation epidemiology data.
  • Existing software limitations in handling millions of rows of data.

Purpose of the Study:

  • Introduce Colossus, an R package for scalable survival analysis.
  • Provide total and relative rate equations for use with regression models.
  • Validate Colossus performance against existing software and published results.

Main Methods:

  • Development of the Colossus R package.
  • Implementation of total and relative rate equations.
  • Application of Cox proportional hazards, Poisson, and Fine-Grey regression models.
  • Comparative analysis with existing software (Epicure) and published data.

Main Results:

  • Colossus successfully analyzed large radiation epidemiology datasets (tens of millions of rows).
  • Results obtained using Colossus were in agreement with existing software.
  • Validation confirmed Colossus's accuracy compared to previous publications.

Conclusions:

  • Colossus provides a scalable and accurate solution for survival analysis in radiation epidemiology.
  • The R package is suitable for analyzing large datasets, such as those from the Million Person Study.
  • Colossus performance is validated and comparable to established methods.