Personalized dose selection in radiation therapy using statistical models for toxicity and efficacy with dose and biomarkers as covariates

Matthew J. Schipper, Jeremy M.G. Taylor, Randy Tenhaken, Martha M. Matuzak, Feng Ming Kong, Theodore S. Lawrence

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Selection of dose for cancer patients treated with radiation therapy (RT) must balance the increased efficacy with the increased toxicity associated with higher dose. Historically, a single dose has been selected for a population of patients (e.g., all stage III non-small cell lung cancer). However, the availability of new biologic markers for toxicity and efficacy allows the possibility of selecting a more personalized dose. We consider the use of statistical models for toxicity and efficacy as a function of RT dose and biomarkers to select an optimal dose for an individual patient, defined as the dose that maximizes the probability of efficacy minus the sum of weighted toxicity probabilities. This function can be shown to be equal to the expected value of the utility derived from a particular family of bivariate outcome utility matrices. We show that if dose is linearly related to the probability of toxicity and efficacy, then any marker that only acts additively with dose cannot improve efficacy, without also increasing toxicity. Using a dataset of lung cancer patients treated with RT, we illustrate this approach and compare it to non-marker-based dose selection. Because typical metrics used in evaluating new markers (e.g., area under the ROC curve) do not directly address the ability of a marker to improve efficacy at a fixed probability of toxicity, we utilize a simulation study to assess the effects of marker-based dose selection on toxicity and efficacy outcomes.

Original languageEnglish (US)
Pages (from-to)5330-5339
Number of pages10
JournalStatistics in Medicine
Volume33
Issue number30
DOIs
StatePublished - Dec 30 2014

Fingerprint

Radiation Therapy
Biomarkers
Statistical Models
Toxicity
Statistical Model
Efficacy
Covariates
Dose
Radiotherapy
Aptitude
ROC Curve
Non-Small Cell Lung Carcinoma
Area Under Curve
Lung Neoplasms
Lung Cancer
Population
Neoplasms
Receiver Operating Characteristic Curve
Expected Value
Cancer

Keywords

  • Biomarkers
  • Dose finding
  • Phase I
  • Radiation therapy
  • Utilities

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability

Cite this

Personalized dose selection in radiation therapy using statistical models for toxicity and efficacy with dose and biomarkers as covariates. / Schipper, Matthew J.; Taylor, Jeremy M.G.; Tenhaken, Randy; Matuzak, Martha M.; Kong, Feng Ming; Lawrence, Theodore S.

In: Statistics in Medicine, Vol. 33, No. 30, 30.12.2014, p. 5330-5339.

Research output: Contribution to journalArticle

Schipper, Matthew J. ; Taylor, Jeremy M.G. ; Tenhaken, Randy ; Matuzak, Martha M. ; Kong, Feng Ming ; Lawrence, Theodore S. / Personalized dose selection in radiation therapy using statistical models for toxicity and efficacy with dose and biomarkers as covariates. In: Statistics in Medicine. 2014 ; Vol. 33, No. 30. pp. 5330-5339.
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