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A Primer on Dose-Response Data Modeling in Radiation Therapy.
- Moiseenko, Vitali (author)
- Marks, Lawrence B (author)
- Grimm, Jimm (author)
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- Jackson, Andrew (author)
- Milano, Michael T (author)
- Hattangadi-Gluth, Jona A (author)
- Huynh-Le, Minh-Phuong (author)
- Yorke, Ellen (author)
- El Naqa, Issam (author)
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- (creator_code:org_t)
- Elsevier BV, 2021
- 2021
- English.
- In: International journal of radiation oncology, biology, physics. - : Elsevier BV. - 1879-355X .- 0360-3016. ; 110:1, s. 11-20
- Journal article (peer-reviewed)
Abstract
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- 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.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Cancer och onkologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Cancer and Oncology (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Radiologi och bildbehandling (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Radiology, Nuclear Medicine and Medical Imaging (hsv//eng)
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