Simulation Modeling of Cancer Clinical Trials: Application to Omitting Radiotherapy in Low-risk Breast Cancer.

Published

Journal Article

Background: We used two models to simulate a proposed noninferiority trial of radiotherapy (RT) omission in low-risk invasive breast cancer to illustrate how modeling could be used to predict the trial's outcomes, inform trial design, and contribute to practice debates. Methods: The proposed trial was a prospective randomized trial of no-RT vs RT in women age 40 to 74 years undergoing lumpectomy and endocrine therapy for hormone receptor-positive, human epidermal growth factor receptor 2-negative, stage I breast cancer with an Oncotype DX score of 18 or lower. The primary endpoint was recurrence-free interval (RFI), including locoregional recurrence, distant recurrence, and breast cancer death. Noninferiority required the two-sided 90% confidence interval of the RFI hazard ratio (HR) for no-RT vs RT to be entirely below 1.7. Model inputs included published data. The trial was simulated 1000 times, and results were summarized as percent concluding noninferiority and mean (standard deviation) of hazard ratios for Model GE and Model M, respectively. Results: Noninferiority was demonstrated in 18.0% and 3.7% for the two models. The respective means (SD) of the RFI hazard ratios were 1.8 (0.7) and 2.4 (0.9); most were locoregional recurrences. The mean five-year RFI rates for no-RT vs RT (SD) were 92.7% (2.9%) vs 95.5% (2.2%) and 88.4% (2.0%) vs 94.5% (1.6%). Both models showed little or no difference in breast cancer-specific or overall survival. Alternative definitions of low risk based on combinations of age and grade produced similar results. Conclusions: The proposed trial was unlikely to show noninferiority of omitting radiotherapy even using alternative definitions of low-risk, as the endpoint included local recurrence. Future trials regarding radiotherapy should address absolute reduction in recurrence and impact of type of recurrence on the patient.

Full Text

Duke Authors

Cited Authors

  • Jayasekera, J; Li, Y; Schechter, CB; Jagsi, R; Song, J; White, J; Luta, G; Chapman, J-AW; Feuer, EJ; Zellars, RC; Stout, N; Julian, TB; Whelan, T; Huang, X; Shelley Hwang, E; Hopkins, JO; Sparano, JA; Anderson, SJ; Fyles, AW; Gray, R; Sauerbrei, W; Mandelblatt, J; Berry, DA; CISNET-BOLD Collaborative Group,

Published Date

  • December 1, 2018

Published In

Volume / Issue

  • 110 / 12

Start / End Page

  • 1360 - 1369

PubMed ID

  • 29718314

Pubmed Central ID

  • 29718314

Electronic International Standard Serial Number (EISSN)

  • 1460-2105

Digital Object Identifier (DOI)

  • 10.1093/jnci/djy059

Language

  • eng

Conference Location

  • United States