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ORIGINAL RESEARCH article

Front. Oncol.
Sec. Head and Neck Cancer
Volume 14 - 2024 | doi: 10.3389/fonc.2024.1422211

Understanding the Impact of Radiotherapy Fractionation on Overall Survival in a Large Head and Neck Squamous Cell Carcinoma Dataset: A Comprehensive Approach Combining Mechanistic and Machine Learning Models

Provisionally accepted
Igor Shuryak Igor Shuryak *Eric Wang Eric Wang David J. Brenner David J. Brenner *
  • Columbia University Irving Medical Center, Columbia University, New York, United States

The final, formatted version of the article will be published soon.

    Treating head and neck squamous cell carcinomas (HNSCC), especially human papillomavirus negative (HPV-) and locally advanced cases, remains difficult. Our previous analyses of radiotherapy-only HNSCC clinical trials data using mechanistically-motivated models predicted that hyperfractionation with twice-daily fractions, or hypofractionation involving increased doses/fraction, both improve tumor control and reduce late normal tissue toxicity, compared with standard 35×2 Gy protocols. Here we further investigated the validity of these conclusions by analyzing a large modern dataset on 3,346 HNSCC radiotherapy patients from the University Health Network in Toronto, Canada, where 42.5% of patients were also treated with chemotherapy. We used a two-step approach that combines mechanistic modeling concepts with state-of-the-art machine learning, beginning with Random Survival Forests (RSF) for an exploratory analysis, followed by Causal Survival Forests (CSF) for a focused analysis. The mechanistic concept of biologically-effective-dose (BED) was implemented for the standard dose-independent (DI) tumor repopulation model, our alternative dose-dependent (DD) repopulation model, and a model with no repopulation (BEDsimp). These BED variants were included in the RSF model, along with age, stage, HPV status and other relevant variables, to predict patient overall survival (OS) and cause-specific mortality (deaths from the index cancer, other cancers or other causes). Model interpretation using Shapley Additive Explanations (SHAP) values and correlation matrices showed that high values of BEDDD or BEDDI, but not BEDsimp, were associated with decreased patient mortality. Targeted causal inference analyses were then performed using CSF to estimate the causal effect of each BED variant on OS. They revealed that high BEDDD (>61.8 Gy) or BEDDI (>57.6 Gy), but not BEDsimp, increased patient restricted mean survival time (RMST) by 0.5-1.0 years and increased survival probability (SP) by 5-15% several years after treatment. In addition to population-level averages, CSF generated individual-level causal effect estimates for each patient, facilitating personalized medicine. These findings are generally consistent with those of our previous mechanistic modeling, implying the potential benefits of altered radiotherapy fractionation schemes (e.g. 25×2.4 Gy, 20×2.75 Gy, 18×3.0 Gy) which increase BEDDD and BEDDI and counteract tumor repopulation more effectively than standard fractionation. Such regimens may represent potentially useful hypofractionated options for treating HNSCC.

    Keywords: Radiotherapy1, Head and neck squamous cell carcinoma2, causal survival forests3, survival4, fractionation5, biostatistics6

    Received: 23 Apr 2024; Accepted: 26 Jul 2024.

    Copyright: © 2024 Shuryak, Wang and Brenner. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Igor Shuryak, Columbia University Irving Medical Center, Columbia University, New York, United States
    David J. Brenner, Columbia University Irving Medical Center, Columbia University, New York, United States

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.