A primer on dose-response data modeling in radiation therapy Review

  


Authors: Moiseenko, V.; Marks, L. B.; Grimm, J.; Jackson, A.; Milano, M. T.; Hattangadi-Gluth, J. A.; Huynh-Le, M. P.; Pettersson, N.; Yorke, E.; El Naqa, I.
Review Title: A primer on dose-response data modeling in radiation therapy
Abstract: An overview of common approaches used to assess a dose response for radiation therapy–associated endpoints is presented, using lung toxicity data sets analyzed as a part of the High Dose per Fraction, Hypofractionated Treatment Effects in the Clinic effort as an example. Each component presented (eg, data-driven analysis, dose-response analysis, and calculating uncertainties on model prediction) is addressed using established approaches. Specifically, the maximum likelihood method was used to calculate best parameter values of the commonly used logistic model, the profile-likelihood to calculate confidence intervals on model parameters, and the likelihood ratio to determine whether the observed data fit is statistically significant. The bootstrap method was used to calculate confidence intervals for model predictions. Correlated behavior of model parameters and implication for interpreting dose response are discussed. © 2020 Elsevier Inc.
Keywords: dose response; radiotherapy; prediction; confidence interval; radiation effects; bootstrapping; maximum likelihood method; statistical methods; maximum likelihood; treatment effects; uncertainty analysis; likelihood ratios; profile likelihood; human; article; dose-response analysis; bootstrap method; data-driven analysis; maximum likelihood methods
Journal Title: International Journal of Radiation Oncology, Biology, Physics
Volume: 110
Issue: 1
ISSN: 0360-3016
Publisher: Elsevier Inc.  
Date Published: 2021-05-01
Start Page: 11
End Page: 20
Language: English
DOI: 10.1016/j.ijrobp.2020.11.020
PUBMED: 33358230
PROVIDER: scopus
DOI/URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85098103207&doi=10.1016%2fj.ijrobp.2020.11.020&partnerID=40&md5=6e3abea2423d63a20e6c3f917737fc5f
Notes: Article -- Export Date: 3 May 2021 -- Source: Scopus
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MSK Authors
  1. Andrew Jackson
    253 Jackson
  2. Ellen D Yorke
    450 Yorke
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