Hostname: page-component-586b7cd67f-gb8f7 Total loading time: 0 Render date: 2024-11-23T00:48:22.420Z Has data issue: false hasContentIssue false
  • English
  • Français

MODEL-BASED COST-EFFECTIVENESS OF CONVENTIONAL AND INNOVATIVE CHEMO-RADIATION IN LUNG CANCER

Published online by Cambridge University Press:  10 November 2017

Mathilda L. Bongers ,
Dirk de Ruysscher ,
Cary Oberije ,
Philippe Lambin ,
Carin A. Uyl-de Groot ,
José Belderbos  and
Veerle M.H. Coupé
Mathilda L. Bongers
Affiliation:
Department of Epidemiology and Biostatistics, VU University Medical Center
Dirk de Ruysscher
Affiliation:
Department of Radiation Oncology, University Hospitals Leuven/KU Leuven
Cary Oberije
Affiliation:
Department of Radiation Oncology (MAASTRO), GROW Research Institute, Maastricht University Medical Centre
Philippe Lambin
Affiliation:
Department of Radiation Oncology (MAASTRO), GROW Research Institute, Maastricht University Medical Centre
Carin A. Uyl-de Groot
Affiliation:
Institute for Medical Technology Assessment, Erasmus University Rotterdam
José Belderbos
Affiliation:
Department of Radiotherapy, The Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital
Veerle M.H. Coupé
Affiliation:
Department of Epidemiology and Biostatistics, VU University Medical [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Introduction: Optimizing radiotherapy with or without chemotherapy through advanced imaging and accelerated radiation schemes shows promising results in locally advanced non–small-cell lung cancer (NSCLC). This study compared the cost-effectiveness of positron emission tomography-computed tomography based isotoxic accelerated sequential chemo-radiation (SRT2) and concurrent chemo-radiation with daily low-dose cisplatin (CRT2) with standard sequential (SRT1) and concurrent chemo-radiation (CRT1).

Methods: We used an externally validated mathematical model to simulate the four treatment strategies. The model was built using data from 200 NSCLC patients treated with curative sequential chemo-radiation. For concurrent strategies, data from a meta-analysis and a single study were included in the model. Costs, utilities, and resource use estimates were obtained from literature. Primary outcomes were the incremental cost-effectiveness and cost-utility ratio (ICUR) of each strategy. Scenario analyses were carried out to investigate the impact of uncertainty.

Results: Total undiscounted costs and quality-adjusted life-years (QALYs) for SRT1, CRT1, SRT2, and CRT2 were EUR 17,288, EUR 18,756, EUR 19,072, EUR 17,360 and QALYs 1.10, 1.15, 1.40, and 1.40, respectively. Compared with SRT1, the ICURs were EUR 38,024/QALY for CRT1, EUR 6,249/QALY for SRT2, and EUR 346/QALY for CRT2. CRT2 was highly cost-effective compared with SRT1. Moreover, CRT2 was more effective and less costly than CRT1 and SRT2. Therefore, these strategies were dominated by CRT2.

Conclusion: Optimized sequential and concurrent chemo-radiation strategies are more effective and cost-effective than the current conventional sequential and concurrent strategies. Concurrent chemo-radiation with a daily low dose cisplatin regimen is the most cost-effective treatment option for locally advanced inoperable NSCLC patients.

Keywords

Cost-effectivenessModelingChemo-radiationRadiotherapyLung cancer
Type
Assessments
Information
International Journal of Technology Assessment in Health Care , Volume 33 , Issue 6 , 2017 , pp. 681 - 690
Copyright
Copyright © Cambridge University Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1. Parkin, DM, Bray, F, Ferlay, J, Pisani, P. Global cancer statistics, 2002. CA Cancer J Clin. 2005;55:74–108.Google Scholar
2. Vansteenkiste, J, De Ruysscher, D, Eberhardt, WEE, et al. Early and locally advanced non-small-cell lung cancer (NSCLC): ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2013;24 (Suppl 6):vi89–vi98.Google Scholar
3. O'Rourke, N, Roqué I Figuls, M, Farré Bernadó, N, Macbeth, F. Concurrent chemoradiotherapy in non-small cell lung cancer. Cochrane Database Syst Rev. 2010:CD002140.Google Scholar
4. De Ruysscher, D, Faivre-Finn, C, Nestle, U, et al. European Organisation for Research and Treatment of Cancer recommendations for planning and delivery of high-dose, high-precision radiotherapy for lung cancer. J Clin Oncol. 2010;28:5301–5310.Google Scholar
5. Mauguen, A, Le Pechoux, C, Saunders, MI, et al. Hyperfractionated or accelerated radiotherapy in lung cancer: An individual patient data meta-analysis. J Clin Oncol. 2012;30:2788–2797.Google Scholar
6. Koning, CC, Wouterse, SJ, Daams, JG, et al. Toxicity of concurrent radiochemotherapy for locally advanced non–small-cell lung cancer: A systematic review of the literature. Clin Lung Cancer. 2013;14: 481–487.Google Scholar
7. Drummond, MF. Methods for the economic evaluation of health care programmes. Cambridge: Oxford University Press; 2005:404.Google Scholar
8. Bongers, ML, De Ruysscher, D, Oberije, C, et al. Multi-state statistical modeling: A tool to build a lung cancer micro-simulation model that includes parameter uncertainty and patient heterogeneity. Med Decis Making. 2016;36:86–100.Google Scholar
9. Bongers, ML, Coupé, VHM, De Ruysscher, D, et al. Individualized PET-based isotoxic accelerated radiotherapy is cost effective compared to conventional radiotherapy: A model-based evaluation. Int J Radiat Oncol Biol Phys. 2015;91:857–865.CrossRefGoogle ScholarPubMed
10. Dehing-Oberije, C, De Ruysscher, D, Petit, S, et al. Development, external validation and clinical usefulness of a practical prediction model for radiation-induced dysphagia in lung cancer patients. Radiother Oncol. 2010;97:455–461.Google Scholar
11. Dehing-Oberije, C, De Ruysscher, D, van Baardwijk, A, et al. The importance of patient characteristics for the prediction of radiation-induced lung toxicity. Radiother Oncol. 2009;91:421–426.CrossRefGoogle ScholarPubMed
12. De Ruysscher, D, Dehing, C, Yu, S, et al. Dyspnea evolution after high-dose radiotherapy in patients with non-small cell lung cancer. Radiother Oncol. 2009;91:353–359.CrossRefGoogle ScholarPubMed
13. Dehing-Oberije, C, Yu, S, De Ruysscher, D, et al. Development and external validation of prognostic model for 2-year survival of non-small-cell lung cancer patients treated with chemoradiotherapy. Int J Radiat Oncol Biol Phys. 2009;74:355–362.CrossRefGoogle ScholarPubMed
14. Vanni, T, Karnon, J, Madan, J, et al. Calibrating models in economic evaluation: a seven-step approach. Pharmacoeconomics. 2011;29: 35–49.CrossRefGoogle ScholarPubMed
15. Aupérin, A, Le Péchoux, C, Rolland, E, et al. Meta-analysis of concomitant versus sequential radiochemotherapy in locally advanced non-small-cell lung cancer. J Clin Oncol. 2010;28:2181–2190.Google Scholar
16. Uyterlinde, W, Belderbos, J, Baas, C, et al. Prediction of acute toxicity grade ≥ 3 in patients with locally advanced non-small-cell lung cancer receiving intensity modulated radiotherapy and concurrent low-dose Cisplatin. Clin Lung Cancer. 2013;14:541–548.Google Scholar
17. Grutters, JPC, Pijls-Johannesma, M, Ruysscher, DD, et al. The cost-effectiveness of particle therapy in non-small cell lung cancer: Exploring decision uncertainty and areas for future research. Cancer Treat Rev. 2010;36:468–476.Google Scholar
18. Tan, SS, Bouwmans, CA, Rutten, FF, Hakkaart-van Roijen, L. Update of the Dutch Manual for Costing in Economic Evaluations. Int J Technol Assess Health Care. 2012;28:152–158.Google Scholar
19. Polder, JJ, Barendregt, JJ, van Oers, H. Health care costs in the last year of life–The Dutch experience. Soc Sci Med. 2006;63:1720–1731.Google Scholar
20. Timmer-Bonte, JNH, Adang, EMM, Termeer, E, Severens, JL, Tjan-Heijnen, VCG. Modeling the cost effectiveness of secondary febrile neutropenia prophylaxis during standard-dose chemotherapy. J Clin Oncol. 2008;26:290–296.Google Scholar
21. Timmer-Bonte, JNH, Adang, EMM, Smit, HJM, et al. Cost-effectiveness of adding granulocyte colony-stimulating factor to primary prophylaxis with antibiotics in small-cell lung cancer. J Clin Oncol. 2006;24:2991–2997.CrossRefGoogle ScholarPubMed
22. Sturza, J. A review and meta-analysis of utility values for lung cancer. Med Decis Making. 2010;30:685–693.CrossRefGoogle ScholarPubMed
23. Nafees, B, Stafford, M, Gavriel, S, Bhalla, S, Watkins, J. Health state utilities for non small cell lung cancer. Health Qual Life Outcomes. 2008;6:84.Google Scholar
24. Marseille, E, Larson, B, Kazi, DS, Kahn, JG, Rosen, S. Thresholds for the cost-effectiveness of interventions: alternative approaches. Bull World Health Organ. 2015;93:118–124. doi: http://dx.doi.org/10.2471/BLT.14.138206 CrossRefGoogle ScholarPubMed
25. De Ruysscher, D, van Baardwijk, A, Steevens, J, et al. Individualised isotoxic accelerated radiotherapy and chemotherapy are associated with improved long-term survival of patients with stage III NSCLC: A prospective population-based study. Radiother Oncol. 2012;102:228–233.Google Scholar
26. Belderbos, J, Uitterhoeve, L, van Zandwijk, N, et al. Randomised trial of sequential versus concurrent chemo-radiotherapy in patients with inoperable non-small cell lung cancer (EORTC 08972–22973). Eur J Cancer. 2007;43:114–121.CrossRefGoogle ScholarPubMed
27. Lievens, Y, Kesteloot, K, Van den Bogaert, W. CHART in lung cancer: Economic evaluation and incentives for implementation. Radiother Oncol. 2005;75:171–178.CrossRefGoogle ScholarPubMed
28. Ramaekers, BLT, Joore, MA, Lueza, B, et al. Cost effectiveness of modified fractionation radiotherapy versus conventional radiotherapy for unresected non-small-cell lung cancer patients. J Thorac Oncol. 2013;8:1295–1307.Google Scholar
29. Whyte, S, Walsh, C, Chilcott, J. Bayesian calibration of a natural history model with application to a population model for colorectal cancer. Med Decis Making. 2011;31:625.Google Scholar
30. Driessen, EJ, Bootsma, GP, Hendriks, LE, et al. Stage III non-small cell lung cancer in the elderly: Patient characteristics predictive for tolerance and survival of chemoradiation in daily clinical practice. Radiother Oncol. 2016;121:26–31.Google Scholar
Supplementary material: File

Bongers et al supplementary material

Figures S1-S5 and Tables S1-S6

Download Bongers et al supplementary material(File)
File 1.8 MB