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Scheduling the adjuvant endocrine therapy for early stage breast cancer

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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.

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Authors and Affiliations

  1. Department of Industrial and Systems Engineering, Texas A&M University, College Station, Texas, 77843, USA

    Sera Kahruman, Elif Ulusal & Sergiy Butenko

  2. Computational and Applied Mathematics, Rice University, Houston, TX, 77005, USA

    Illya V. Hicks

  3. University of Michigan Health System, Ann Arbor, MI, 48109-0932, USA

    Kathleen M. Diehl

Authors
  1. Sera Kahruman
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  2. Elif Ulusal
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  3. Sergiy Butenko
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  4. Illya V. Hicks
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  5. Kathleen M. Diehl
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Correspondence to Sergiy Butenko.

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Kahruman, S., Ulusal, E., Butenko, S. et al. Scheduling the adjuvant endocrine therapy for early stage breast cancer. Ann Oper Res 196, 683–705 (2012). https://doi.org/10.1007/s10479-010-0741-y

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  • DOI: https://doi.org/10.1007/s10479-010-0741-y

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