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Ponte Academic Journal
Jan 2019, Volume 75, Issue 1

A MCDM MODEL DESIGN FOR HER2+ BREAST CANCER TREATMENT TECHNIQUE USING AHP METHOD

Author(s): Hatice Camgoz Akdag ,Cagkan Alemdar, Eray Aydin

J. Ponte - Jan 2019 - Volume 75 - Issue 1
doi: 10.21506/j.ponte.2019.1.13



Abstract:
Purpose - The aim of this paper is to present a multi-criteria decision-making model in order to apply Analytical Hierarchy Process (AHP) method for the selection of the best treatment technique for HER2+ breast cancer from two different treatment alternatives: Kadcyla and Lapatinib plus Capecitabine. The study analyzes the decision making process of oncologists when there are more than one alternative treatment techniques for them to choose.\\\\r\\\\nDesign/methodology/approach – Data are collected from oncologists by using an online survey after the literature review was carried out and interviews with a drug developer and oncologists were made. In order to analyze the decision making process of oncologists and the effectiveness of two drugs based on determined attributes, AHP method was used and the results were verified with TOPSIS and Weighted Product methods.\\\\r\\\\nFindings – In this paper, it is proven that Kadcyla is better in AHP model when compared to Lapatinib plus Capecitabine in terms of meeting the expectations of the oncologists while fighting against HER2+ breast cancer.\\\\r\\\\nResearch limitations/implications - The biggest limitation of the research seems to be a halo effect that the oncologists might be experiencing because one of the alternative drug combinations in the research is more frequently prescribed than the other one which could affect the subjectivity of the answers.\\\\r\\\\nOriginality/Value - This paper gives an insight about the factors that are taken into account when choosing the best cancer treatment technique and their significance level. It presents a model for identifying the most effective targeted drug combination. It will be useful for academicians, oncologists and drug developers in terms of a better understanding of the needs in cancer treatment
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