A marginal structural model for normal tissue complication probability

The goal of radiation therapy for cancer is to deliver prescribed radiation dose to the tumor while minimizing dose to the surrounding healthy tissues. To evaluate treatment plans, the dose distribution to healthy organs is commonly summarized as dose-volume histograms (DVHs). Normal tissue complica...

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Bibliographic Details
Published in:arXiv.org 2024-05
Main Authors: Thai-Son Tang, Liu, Zhihui, Ali, Hosni, Kim, John, Saarela, Olli
Format: Article
Language:English
Subjects:
Cancer
Estimators
Feature extraction
Radiation dosage
Radiation therapy
Structural models
Toxicity
Online Access:Get full text
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Summary:The goal of radiation therapy for cancer is to deliver prescribed radiation dose to the tumor while minimizing dose to the surrounding healthy tissues. To evaluate treatment plans, the dose distribution to healthy organs is commonly summarized as dose-volume histograms (DVHs). Normal tissue complication probability (NTCP) modelling has centered around making patient-level risk predictions with features extracted from the DVHs, but few have considered adapting a causal framework to evaluate the safety of alternative treatment plans. We propose causal estimands for NTCP based on deterministic and stochastic interventions, as well as propose estimators based on marginal structural models that impose bivariable monotonicity between dose, volume, and toxicity risk. The properties of these estimators are studied through simulations, and their use is illustrated in the context of radiotherapy treatment of anal canal cancer patients.
ISSN:2331-8422