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Recommendations on statistical approaches to account for dose uncertainties in radiation epidemiologic risk models.
Bellamy, Michael B; Bernstein, Jonine L; Cullings, Harry M; French, Benjamin; Grogan, Helen A; Held, Kathryn D; Little, Mark P; Tekwe, Carmen D.
Afiliación
  • Bellamy MB; Department of Medical Physics, Memorial Sloan Kettering Cancer Center New York, New York, NY, USA.
  • Bernstein JL; Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center New York, New York, NY, USA.
  • Cullings HM; Department of Statistics, Radiation Research Effects Foundation, Hiroshima, Japan.
  • French B; Vanderbilt University Medical Center, Nashville, TN, USA.
  • Grogan HA; NCRP, Bethesda, MD, USA.
  • Held KD; NCRP, Bethesda, MD, USA.
  • Little MP; Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
  • Tekwe CD; Faculty of Health and Life Sciences, Oxford Brookes University, Oxford, UK.
Int J Radiat Biol ; : 1-12, 2024 Jul 26.
Article en En | MEDLINE | ID: mdl-39058334
ABSTRACT

PURPOSE:

Epidemiological studies of stochastic radiation health effects such as cancer, meant to estimate risks of the adverse effects as a function of radiation dose, depend largely on estimates of the radiation doses received by the exposed group under study. Those estimates are based on dosimetry that always has uncertainty, which often can be quite substantial. Studies that do not incorporate statistical methods to correct for dosimetric uncertainty may produce biased estimates of risk and incorrect confidence bounds on those estimates. This paper reviews commonly used statistical methods to correct radiation risk regressions for dosimetric uncertainty, with emphasis on some newer methods. We begin by describing the types of dose uncertainty that may occur, including those in which an uncertain value is shared by part or all of a cohort, and then demonstrate how these sources of uncertainty arise in radiation dosimetry. We briefly describe the effects of different types of dosimetric uncertainty on risk estimates, followed by a description of each method of adjusting for the uncertainty.

CONCLUSIONS:

Each of the method has strengths and weaknesses, and some methods have limited applicability. We describe the types of uncertainty to which each method can be applied and its pros and cons. Finally, we provide summary recommendations and touch briefly on suggestions for further research.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Int J Radiat Biol Asunto de la revista: RADIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Int J Radiat Biol Asunto de la revista: RADIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido