A Bayesian Approach for Prediction of Patient Radiosensitivity.

Int J Radiat Oncol Biol Phys

Research Division, Peter MacCallum Cancer Center, Melbourne, Australia; Division of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Australia; Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, Victoria, Australia. Electronic address:

Published: November 2018

Purpose: A priori identification of the small proportion of radiation therapy patients who prove to be severely radiosensitive is a long-held goal in radiation oncology. A number of published studies indicate that analysis of the DNA damage response after ex vivo irradiation of peripheral blood lymphocytes, using the γ-H2AX assay to detect DNA damage, provides a basis for a functional assay for identification of the small proportion of severely radiosensitive cancer patients undergoing radiotherapy.

Methods And Materials: We introduce a new, more rigorous, integrated approach to analysis of radiation-induced γ-H2AX response, using Bayesian statistics.

Results: This approach shows excellent discrimination between radiosensitive and non-radiosensitive patient groups described in a previously reported data set.

Conclusions: Bayesian statistical analysis provides a more appropriate and reliable methodology for future prospective studies.

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Source
http://dx.doi.org/10.1016/j.ijrobp.2018.06.033DOI Listing

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