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Scheduling the adjuvant endocrine therapy for early stage breast cancer

Author

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  • Sera Kahruman
  • Elif Ulusal
  • Sergiy Butenko
  • Illya Hicks
  • Kathleen Diehl

Abstract

Based on the data available through published trial results, we build a mixed integer nonlinear programming (MINLP) model in order to find an optimal treatment plan for a given HR+ early stage breast cancer patient who is postmenopausal. The objective is to maximize the disease-free survival percentage at the end of the treatment period subject to the constraints on the risk of contralateral breast cancer and the risks of several side effects, including endometrial cancer, thromboembolic events, cardiovascular diseases, bone fractures, hot flushes, and vaginal bleeding. The results of numerical experiments suggest the effectiveness of some of the schedules currently used in practice, as well as suggest some attractive alternative treatment plans. Copyright Springer Science+Business Media, LLC 2012

Suggested Citation

  • Sera Kahruman & Elif Ulusal & Sergiy Butenko & Illya Hicks & Kathleen Diehl, 2012. "Scheduling the adjuvant endocrine therapy for early stage breast cancer," Annals of Operations Research, Springer, vol. 196(1), pages 683-705, July.
    • Handle: RePEc:spr:annopr:v:196:y:2012:i:1:p:683-705:10.1007/s10479-010-0741-y
    DOI: 10.1007/s10479-010-0741-y
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    References listed on IDEAS

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    1. H. Edwin Romeijn & Ravindra K. Ahuja & James F. Dempsey & Arvind Kumar, 2006. "A New Linear Programming Approach to Radiation Therapy Treatment Planning Problems," Operations Research, INFORMS, vol. 54(2), pages 201-216, April.
    2. Eva Lee & Tim Fox & Ian Crocker, 2003. "Integer Programming Applied to Intensity-Modulated Radiation Therapy Treatment Planning," Annals of Operations Research, Springer, vol. 119(1), pages 165-181, March.
    3. Zvia Agur & Refael Hassin & Sigal Levy, 2006. "Optimizing Chemotherapy Scheduling Using Local Search Heuristics," Operations Research, INFORMS, vol. 54(5), pages 829-846, October.
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    1. Nazila Bazrafshan & M. M. Lotfi, 2020. "A finite-horizon Markov decision process model for cancer chemotherapy treatment planning: an application to sequential treatment decision making in clinical trials," Annals of Operations Research, Springer, vol. 295(1), pages 483-502, December.

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