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The time-varying effect of radiotherapy after breast-conserving surgery for DCIS

  • Eileen RakovitchEmail author
  • Rinku Sutradhar
  • Michael Hallett
  • Alastair M. Thompson
  • Sumei Gu
  • Vanessa Dumeaux
  • Timothy J. Whelan
  • Lawrence Paszat
Epidemiology

Abstract

Background

A better understanding underlying radiation (RT) response after breast-conserving surgery (BCS) is needed to mitigate over-treatment of DCIS. The hazard ratio (HR) measures the effect of RT but assumes the effect is constant over time. We examined the hazard function adjusted for adherence to surveillance mammography to examine variations in LR risk and the effect of RT over time.

Methods

Crude hazard estimates for the development of LR in a population cohort of DCIS treated by BCS ± RT were computed. Multivariable extended Cox models and hazard plots were used to examine the association between receipt of RT and risk of each outcome adjusted for baseline covariates and adherence to mammography.

Results

Population cohort includes 3262 women treated by BCS; 1635 received RT. Median follow-up was 13 years. LR developed in 364 women treated by BCS alone and 274 treated with RT. LR risk peaked at 2 years, declined until year 7, and then remained steady. The peak hazard of LR was associated with adverse features of DCIS. Early LR risk was attenuated in patients treated with RT but late annual risks of LR and invasive LR were similar among the two treatment groups. On multivariate analysis, RT was associated with a reduction in early LR risk (HR = 0.52, 95% CI 0.43–0.63, p < 0.0001) but did not reduce the risk of late LR (HR = 0.89, 95% CI: 0.67, 1.19, p = 0.44) (interaction, p = 0.002).

Conclusions

The effect of RT is not uniform over time and greatest in the first 7 years after BCS for DCIS, which can guide future research to understand mechanisms underlying RT response and optimize future management of DCIS.

Keywords

Ductal carcinoma in situ DCIS Hazards Local recurrence Radiation 

Notes

Acknowledgements

The authors would like to acknowledge the assistance of C. Fong and S. Trebinjac in the preparation and submission of this manuscript. This study was supported by the ICES, which is funded by an annual grant from the Ontario Ministry of Health and Long-Term Care (MOHLTC). The opinions, results, and conclusions reported in this paper are those of the authors and are independent from the funding sources. No endorsement by ICES or the Ontario MOHLTC is intended or should be inferred. These datasets were linked using unique encoded identifiers and analyzed at the ICES. Parts of this material are based on data and/or information compiled and provided by CIHI. However, the analyses, conclusions, opinions, and statements expressed in the material are those of the author(s), and not necessarily those of CIHI. Parts of this material are based on data and information provided by Cancer Care Ontario (CCO). The opinions, results, view, and conclusions reported in this paper are those of the authors and do not necessarily reflect those of CCO. No endorsement by CCO is intended or should be inferred.

Author contributions

All authors contributed to the interpretation of the analysis and manuscript preparation.

Funding

This work was supported in part by a grant from the Canadian Cancer Society Research Institute (Grant Number 18491). Dr. Rakovitch holds the LC Campbell Breast Cancer Research Chair.

Compliance with ethical standards

Conflicts of interest

ERakovitch has received research grant funding from Genomic Health Inc. A Thompson has received lecture honoraria from Pfizer outside of this work. T Whelan has received other research grant funding from Genomic Health Inc. All other authors declare no conflict of interest.

Ethical approval

Ethical approval was obtained from Sunnybrook Health Sciences Centre.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Radiation OncologyTorontoCanada
  2. 2.ICESTorontoCanada
  3. 3.Sunnybrook Health Sciences CentreUniversity of TorontoTorontoCanada
  4. 4.Department of BiologyConcordia UniversityMontrealCanada
  5. 5.School of Computer ScienceMcGill UniversityMontrealCanada
  6. 6.Dan L Duncan Comprehensive Cancer Center, Division of SurgicalBaylor College of MedicineHoustonUSA
  7. 7.PERFORM CentreConcordia UniversityMontréalCanada
  8. 8.Department of OncologyMcMaster UniversityHamiltonCanada
  9. 9.LC Campbell Chair in Breast Cancer ResearchSunnybrook Health Sciences CentreTorontoCanada

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