Intensity modulated radiation therapy following lumpectomy in early-stage breast cancer: Patterns of use and cost consequences among Medicare beneficiaries

Autoři: Lia M. Halasz aff001;  Shilpen A. Patel aff001;  Jean A. McDougall aff003;  Catherine Fedorenko aff004;  Qin Sun aff004;  Bernardo H. L. Goulart aff002;  Joshua A. Roth aff002
Působiště autorů: Department of Radiation Oncology, University of Washington, Seattle, Washington, United States of America aff001;  Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America aff002;  Department of Internal Medicine, University of New Mexico, Albuquerque, New Mexico, United States of America aff003;  Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America aff004;  Department of Medicine, Division of Medical Oncology, University of Washington, Seattle, Washington, United States of America aff005
Vyšlo v časopise: PLoS ONE 14(9)
Kategorie: Research Article
doi: 10.1371/journal.pone.0222904



In 2013, the American Society for Radiation Oncology (ASTRO) issued a Choosing Wisely recommendation against the routine use of intensity modulated radiotherapy (IMRT) for whole breast irradiation. We evaluated IMRT use and subsequent impact on Medicare expenditure in the period immediately preceding this recommendation to provide a baseline measure of IMRT use and associated cost consequences.

Methods and materials

SEER records for women ≥66 years with first primary diagnosis of Stage I/II breast cancer (2008–2011) were linked with Medicare claims (2007–2012). Eligibility criteria included lumpectomy within 6 months of diagnosis and radiotherapy within 6 months of lumpectomy. We evaluated IMRT versus conventional radiotherapy (cRT) use overall and by SEER registry (12 sites). We used generalized estimating equations logit models to explore adjusted odds ratios (OR) for associations between clinical, sociodemographic, and health services characteristics and IMRT use. Mean costs were calculated from Medicare allowable costs in the year after diagnosis.


Among 13,037 women, mean age was 74.4, 50.5% had left-sided breast cancer, and 19.8% received IMRT. IMRT use varied from 0% to 52% across SEER registries. In multivariable analysis, left-sided breast cancer (OR 1.75), living in a big metropolitan area (OR 2.39), living in a census tract with ≤$90,000 median income (OR 1.75), neutral or favorable local coverage determination (OR 3.86, 1.72, respectively), and free-standing treatment facility (OR 3.49) were associated with receipt of IMRT (p<0.001). Mean expenditure in the year after diagnosis was $8,499 greater (p<0.001) among women receiving IMRT versus cRT.


We found highly variable use of IMRT and higher expenditure in the year after diagnosis among women treated with IMRT (vs. cRT) with early-stage breast cancer and Medicare insurance. Our findings suggest a considerable opportunity to reduce treatment variation and cost of care while improving alignment between practice and clinical guidelines.

Klíčová slova:

Breast cancer – Cancer detection and diagnosis – Cancer treatment – Census – Medicare – Oncology – Radiation therapy – Lumpectomy


1. Pinsky PF, Gierada DS, Hocking W, Patz EF Jr, Kramer BS. National Lung Screening Trial Findings by Age: Medicare-Eligible Versus Under-65 PopulationNational Lung Screening Trial Findings by Age. Annals of Internal Medicine. 2014;N/A(N/A):N/A–N/A.

2. Ramsey SD, Bansal A, Fedorenko CR, Blough DK, Overstreet KA, Shankaran V, et al. Financial Insolvency as a Risk Factor for Early Mortality Among Patients With Cancer. J Clin Oncol. 2016;34(9):980–6. doi: 10.1200/JCO.2015.64.6620 26811521

3. Schnipper LE, Davidson NE, Wollins DS, Tyne C, Blayney DW, Blum D, et al. American Society of Clinical Oncology Statement: A Conceptual Framework to Assess the Value of Cancer Treatment Options. J Clin Oncol. 2015;33(23):2563–77. Epub 2015/06/24. doi: 10.1200/JCO.2015.61.6706 26101248 online at Author contributions are found at the end of this article.

4. Waddle MR, Sio TT, Van Houten HK, Foote RL, Keole SR, Schild SE, et al. Photon and Proton Radiation Therapy Utilization in a Population of More Than 100 Million Commercially Insured Patients. Int J Radiat Oncol Biol Phys. 2017;99(5):1078–82. doi: 10.1016/j.ijrobp.2017.07.042 28939229.

5. van den Bogaard VA, Ta BD, van der Schaaf A, Bouma AB, Middag AM, Bantema-Joppe EJ, et al. Validation and Modification of a Prediction Model for Acute Cardiac Events in Patients With Breast Cancer Treated With Radiotherapy Based on Three-Dimensional Dose Distributions to Cardiac Substructures. J Clin Oncol. 2017;35(11):1171–8. Epub 2017/01/18. doi: 10.1200/JCO.2016.69.8480 28095159

6. Darby SC, Ewertz M, McGale P, Bennet AM, Blom-Goldman U, Bronnum D, et al. Risk of ischemic heart disease in women after radiotherapy for breast cancer. N Engl J Med. 2013;368(11):987–98. doi: 10.1056/NEJMoa1209825 23484825.

7. Shah C, Banda B, Chandra R, Vicini F. Minimizing toxicity in breast irradiation. Expert Rev Anticancer Ther. 2017;17(3):187–9. doi: 10.1080/14737140.2017.1285231 28110574.

8. Boekel NB, Schaapveld M, Gietema JA, Russell NS, Poortmans P, Theuws JC, et al. Cardiovascular Disease Risk in a Large, Population-Based Cohort of Breast Cancer Survivors. Int J Radiat Oncol Biol Phys. 2016;94(5):1061–72. Epub 2016/03/31. doi: 10.1016/j.ijrobp.2015.11.040 27026313.

9. Boero IJ, Paravati AJ, Triplett DP, Hwang L, Matsuno RK, Gillespie EF, et al. Modern Radiation Therapy and Cardiac Outcomes in Breast Cancer. Int J Radiat Oncol Biol Phys. 2016;94(4):700–8. Epub 2016/03/15. doi: 10.1016/j.ijrobp.2015.12.018 26972642.

10. Zagar TM, Marks LB. Breast cancer: risk of heart disease after radiotherapy-cause for concern. Nat Rev Clin Oncol. 2013;10(6):310–2. Epub 2013/04/24. doi: 10.1038/nrclinonc.2013.59 23609314.

11. Pignol JP, Truong P, Rakovitch E, Sattler MG, Whelan TJ, Olivotto IA. Ten years results of the Canadian breast intensity modulated radiation therapy (IMRT) randomized controlled trial. Radiother Oncol. 2016;121(3):414–9. doi: 10.1016/j.radonc.2016.08.021 27637858.

12. Donovan E, Bleakley N, Denholm E, Evans P, Gothard L, Hanson J, et al. Randomised trial of standard 2D radiotherapy (RT) versus intensity modulated radiotherapy (IMRT) in patients prescribed breast radiotherapy. Radiother Oncol. 2007;82(3):254–64. doi: 10.1016/j.radonc.2006.12.008 17224195.

13. Mukesh MB, Barnett GC, Wilkinson JS, Moody AM, Wilson C, Dorling L, et al. Randomized controlled trial of intensity-modulated radiotherapy for early breast cancer: 5-year results confirm superior overall cosmesis. J Clin Oncol. 2013;31(36):4488–95. doi: 10.1200/JCO.2013.49.7842 24043742.

14. Barnett GC, Wilkinson J, Moody AM, Wilson CB, Sharma R, Klager S, et al. A randomised controlled trial of forward-planned radiotherapy (IMRT) for early breast cancer: baseline characteristics and dosimetry results. Radiother Oncol. 2009;92(1):34–41. doi: 10.1016/j.radonc.2009.03.003 19375808.

15. Jagsi R, Griffith KA, Moran JM, Ficaro E, Marsh R, Dess RT, et al. A Randomized Comparison of Radiation Therapy Techniques in the Management of Node-Positive Breast Cancer: Primary Outcomes Analysis. Int J Radiat Oncol Biol Phys. 2018;101(5):1149–58. doi: 10.1016/j.ijrobp.2018.04.075 30012527.

16. Wang EH, Mougalian SS, Soulos PR, Smith BD, Haffty BG, Gross CP, et al. Adoption of intensity modulated radiation therapy for early-stage breast cancer from 2004 through 2011. Int J Radiat Oncol Biol Phys. 2015;91(2):303–11. doi: 10.1016/j.ijrobp.2014.09.011 25442334.

17. Smith BD, Pan IW, Shih YC, Smith GL, Harris JR, Punglia R, et al. Adoption of intensity-modulated radiation therapy for breast cancer in the United States. Journal of the National Cancer Institute. 2011;103(10):798–809. Epub 2011/04/29. doi: 10.1093/jnci/djr100 21525437.

18. Roberts KB, Soulos PR, Herrin J, Yu JB, Long JB, Dostaler E, et al. The adoption of new adjuvant radiation therapy modalities among Medicare beneficiaries with breast cancer: clinical correlates and cost implications. Int J Radiat Oncol Biol Phys. 2013;85(5):1186–92. doi: 10.1016/j.ijrobp.2012.10.009 23182396

19. Chapman PB, Hauschild A, Robert C, Haanen JB, Ascierto P, Larkin J, et al. Improved survival with vemurafenib in melanoma with BRAF V600E mutation. The New England journal of medicine. 2011;364(26):2507–16. Epub 2011/06/07. doi: 10.1056/NEJMoa1103782 21639808.

20. Sosman JA, Kim KB, Schuchter L, Gonzalez R, Pavlick AC, Weber JS, et al. Survival in BRAF V600-mutant advanced melanoma treated with vemurafenib. The New England journal of medicine. 2012;366(8):707–14. Epub 2012/02/24. doi: 10.1056/NEJMoa1112302 22356324.

21. Potosky AL, Riley GF, Lubitz JD, Mentnech RM, Kessler LG. Potential for cancer related health services research using a linked Medicare-tumor registry database. Med Care. 1993;31(8):732–48. Epub 1993/08/01. 8336512.

22. Hattangadi JA, Taback N, Neville BA, Harris JR, Punglia RS. Accelerated partial breast irradiation using brachytherapy for breast cancer: patterns in utilization and guideline concordance. J Natl Cancer Inst. 2012;104(1):29–41. doi: 10.1093/jnci/djr495 22180643.

23. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. Journal of chronic diseases. 1987;40(5):373–83. doi: 10.1016/0021-9681(87)90171-8 3558716.

24. Klabunde CN, Potosky AL, Legler JM, Warren JL. Development of a comorbidity index using physician claims data. J Clin Epidemiol. 2000;53(12):1258–67. doi: 10.1016/s0895-4356(00)00256-0 11146273.

25. Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. Journal of clinical epidemiology. 1992;45(6):613–9. Epub 1992/06/01. doi: 10.1016/0895-4356(92)90133-8 1607900.

26. Etzioni R, Riley GF, Ramsey SD, Brown M. Measuring costs: administrative claims data, clinical trials, and beyond. Medical care. 2002;40(6 Suppl):III63–72. Epub 2002/06/18. 12064760.

27. Zeger SL, Liang K-Y, Albert PS. Models for Longitudinal Data: A Generalized Estimating Equation Approach. Biometrics. 1988;44(4):1049–60. doi: 10.2307/2531734 3233245

28. Hanley JA, Negassa A, Edwardes MDd, Forrester JE. Statistical Analysis of Correlated Data Using Generalized Estimating Equations: An Orientation. American journal of epidemiology. 2003;157(4):364–75. doi: 10.1093/aje/kwf215 12578807

Článek vyšel v časopise


2019 Číslo 9

Nejčtenější v tomto čísle

Tomuto tématu se dále věnují…


Zvyšte si kvalifikaci online z pohodlí domova

Antiseptika a prevence ve stomatologii
nový kurz
Autoři: MUDr. Ladislav Korábek, CSc., MBA

Citikolin v neuroprotekci a neuroregeneraci: od výzkumu do klinické praxe nejen očních lékařů
Autoři: MUDr. Petr Výborný, CSc., FEBO

Zánětlivá bolest zad a axiální spondylartritida – Diagnostika a referenční strategie
Autoři: MUDr. Monika Gregová, Ph.D., MUDr. Kristýna Bubová

Diagnostika a léčba deprese pro ambulantní praxi
Autoři: MUDr. Jan Hubeňák, Ph.D

Význam nemocničního alert systému v době SARS-CoV-2
Autoři: doc. MUDr. Helena Lahoda Brodská, Ph.D., prim. MUDr. Václava Adámková

Všechny kurzy
Kurzy Doporučená témata