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Integrating Data Envelopment Analysis into radiotherapy treatment planning for head and neck cancer patients

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  • Raith, Andrea
  • Ehrgott, Matthias
  • Fauzi, Fariza
  • Lin, Kuan-Min
  • Macann, Andrew
  • Rouse, Paul
  • Simpson, John

Abstract

Radiotherapy treatment (RT) irradiates a patient's tumour volume while minimising damage to healthy tissue and surrounding critical organs at risk (OAR). In the conventional RT planning process, the RT planner has to iteratively adjust either the planning objectives (tumour or OAR dose levels) or the weights of the planning objectives until an acceptable plan is obtained that satisfies the minimum requirements. At the end of this iterative process, it remains unknown whether this plan is the best that can be obtained for the patient. The oncologist reviews each plan and decides to either treat using this plan or request further plan development, which may or may not lead to an actual improvement of the reviewed plan.

Suggested Citation

  • Raith, Andrea & Ehrgott, Matthias & Fauzi, Fariza & Lin, Kuan-Min & Macann, Andrew & Rouse, Paul & Simpson, John, 2022. "Integrating Data Envelopment Analysis into radiotherapy treatment planning for head and neck cancer patients," European Journal of Operational Research, Elsevier, vol. 296(1), pages 289-303.
    • Handle: RePEc:eee:ejores:v:296:y:2022:i:1:p:289-303
    DOI: 10.1016/j.ejor.2021.04.007
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    1. William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), 2011. "Handbook on Data Envelopment Analysis," International Series in Operations Research and Management Science, Springer, number 978-1-4419-6151-8, December.
    2. Ruggiero, John, 1998. "Non-discretionary inputs in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 111(3), pages 461-469, December.
    3. Andrea Raith & Paul Rouse & Lawrence M. Seiford, 2019. "Benchmarking Using Data Envelopment Analysis: Application to Stores of a Post and Banking Business," International Series in Operations Research & Management Science, in: Sandra Huber & Martin Josef Geiger & Adiel Teixeira de Almeida (ed.), Multiple Criteria Decision Making and Aiding, pages 1-39, Springer.
    4. Breedveld, Sebastiaan & Craft, David & van Haveren, Rens & Heijmen, Ben, 2019. "Multi-criteria optimization and decision-making in radiotherapy," European Journal of Operational Research, Elsevier, vol. 277(1), pages 1-19.
    5. Bădin, Luiza & Daraio, Cinzia & Simar, Léopold, 2012. "How to measure the impact of environmental factors in a nonparametric production model," European Journal of Operational Research, Elsevier, vol. 223(3), pages 818-833.
    6. Subhash C. Ray, 1991. "Resource-Use Efficiency in Public Schools: A Study of Connecticut Data," Management Science, INFORMS, vol. 37(12), pages 1620-1628, December.
    7. Harold Fried & Shelton Schmidt & Suthathip Yaisawarng, 1999. "Incorporating the Operating Environment Into a Nonparametric Measure of Technical Efficiency," Journal of Productivity Analysis, Springer, vol. 12(3), pages 249-267, November.
    8. Diogo Cunha Ferreira & Rui Cunha Marques, 2020. "A step forward on order-α robust nonparametric method: inclusion of weight restrictions, convexity and non-variable returns to scale," Operational Research, Springer, vol. 20(2), pages 1011-1046, June.
    9. Sebastian Kohl & Jan Schoenfelder & Andreas Fügener & Jens O. Brunner, 2019. "The use of Data Envelopment Analysis (DEA) in healthcare with a focus on hospitals," Health Care Management Science, Springer, vol. 22(2), pages 245-286, June.
    10. H. Fried & C. Lovell & S. Schmidt & S. Yaisawarng, 2002. "Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 17(1), pages 157-174, January.
    11. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    12. R. Allen & A. Athanassopoulos & R.G. Dyson & E. Thanassoulis, 1997. "Weights restrictions and value judgements in Data Envelopment Analysis: Evolution, development and future directions," Annals of Operations Research, Springer, vol. 73(0), pages 13-34, October.
    13. Emma Stubington & Matthias Ehrgott & Glyn Shentall & Omid Nohadani, 2019. "Evaluating the Quality of Radiotherapy Treatment Plans for Prostate Cancer," International Series in Operations Research & Management Science, in: Sandra Huber & Martin Josef Geiger & Adiel Teixeira de Almeida (ed.), Multiple Criteria Decision Making and Aiding, pages 41-66, Springer.
    14. Joe Zhu, 2014. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Quantitative Models for Performance Evaluation and Benchmarking, edition 3, chapter 1, pages 1-9, Springer.
    15. Yasar A. Ozcan, 2014. "Evaluation of Performance in Health Care," International Series in Operations Research & Management Science, in: Health Care Benchmarking and Performance Evaluation, edition 2, chapter 0, pages 3-14, Springer.
    16. Aragon, Y. & Daouia, A. & Thomas-Agnan, C., 2005. "Nonparametric Frontier Estimation: A Conditional Quantile-Based Approach," Econometric Theory, Cambridge University Press, vol. 21(2), pages 358-389, April.
    17. Ferreira, D.C. & Marques, R.C. & Nunes, A.M., 2018. "Economies of scope in the health sector: The case of Portuguese hospitals," European Journal of Operational Research, Elsevier, vol. 266(2), pages 716-735.
    18. Ray, Subhash C., 1988. "Data envelopment analysis, nondiscretionary inputs and efficiency: an alternative interpretation," Socio-Economic Planning Sciences, Elsevier, vol. 22(4), pages 167-176.
    19. Jos Blank & Vivian Valdmanis, 2010. "Environmental factors and productivity on Dutch hospitals: a semi-parametric approach," Health Care Management Science, Springer, vol. 13(1), pages 27-34, March.
    20. Cook, Wade D. & Tone, Kaoru & Zhu, Joe, 2014. "Data envelopment analysis: Prior to choosing a model," Omega, Elsevier, vol. 44(C), pages 1-4.
    21. H. W. Hamacher & K. H. Küfer, 1999. "Inverse Radiation Therapy Planning: A Multiple Objective Optimisation Approach," World Scientific Book Chapters, in: V De Angelis & N Ricciardi & G Storchi (ed.), Monitoring, Evaluating, Planning Health Services, chapter 16, pages 177-189, World Scientific Publishing Co. Pte. Ltd..
    22. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    23. Sérgio P. Santos & Carla A. F. Amado, 2012. "Using data envelopment analysis for formative evaluation of radiotherapy services: An exploratory study," International Series in Operations Research & Management Science, in: Elena Tànfani & Angela Testi (ed.), Advanced Decision Making Methods Applied to Health Care, chapter 0, pages 173-190, Springer.
    24. Cazals, Catherine & Florens, Jean-Pierre & Simar, Leopold, 2002. "Nonparametric frontier estimation: a robust approach," Journal of Econometrics, Elsevier, vol. 106(1), pages 1-25, January.
    25. Rajiv D. Banker & Richard C. Morey, 1986. "Efficiency Analysis for Exogenously Fixed Inputs and Outputs," Operations Research, INFORMS, vol. 34(4), pages 513-521, August.
    26. Yasar A. Ozcan, 2014. "Health Care Benchmarking and Performance Evaluation," International Series in Operations Research and Management Science, Springer, edition 2, number 978-1-4899-7472-3, December.
    27. Rajiv D. Banker & Richard C. Morey, 1986. "The Use of Categorical Variables in Data Envelopment Analysis," Management Science, INFORMS, vol. 32(12), pages 1613-1627, December.
    28. Matthias Ehrgott & Çiğdem Güler & Horst Hamacher & Lizhen Shao, 2010. "Mathematical optimization in intensity modulated radiation therapy," Annals of Operations Research, Springer, vol. 175(1), pages 309-365, March.
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    1. de Freitas, Juliana Campos & Cantane, Daniela Renata & Rocha, Humberto & Dias, Joana, 2024. "A multiobjective beam angle optimization framework for intensity-modulated radiation therapy," European Journal of Operational Research, Elsevier, vol. 318(1), pages 286-296.

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