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Metabolic tumor volume predicts overall survival and local control in patients with stage III non-small cell lung cancer treated in ACRIN 6668/RTOG 0235

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European Journal of Nuclear Medicine and Molecular Imaging Aims and scope Submit manuscript

Abstract

Purpose

To determine whether higher pre-treatment metabolic tumor volume (tMTV-pre) is associated with worse overall survival (OS) in patients with inoperable NSCLC treated with definitive chemoradiation (CRT).

Methods

This is a secondary analysis of the American College of Radiology Imaging Network (ACRIN) 6668/Radiation Therapy Oncology Group 0235 trial. Pre-treatment PET scans were performed on ACRIN-qualified scanners. Computer-aided MTV measurement was performed using RT_Image. Kaplan–Meier curves and Cox proportional hazards regression models were used to assess the association between tMTV and OS.

Results

Of the 250 patients enrolled on the study, 230 were evaluable for tMTV-pre. Patients with MTV-pre >32 mL (median value) vs. ≤32 mL had worse median OS (14.8 vs. 29.7 months, p < 0.001). As a continuous variable, higher tMTV-pre (per 10-mL increase) remained associated with worse OS (HR = 1.03, p < 0.001) after controlling for other variables. A significant interaction between radiation dose and tMTV-pre occurred for OS (p = 0.002), demonstrating that the negative prognostic impact of tMTV-pre decreased as radiotherapy dose increased. Among patients with tMTV-pre ≤32 mL, there was no difference in survival according to radiotherapy dose delivered (p = 0.694). However, median OS was inferior in patients with tMTV-pre >32 mL who received ≤60 Gy compared with those who received 61–69 Gy or ≥70 Gy (p = 0.001).

Conclusions

Higher tMTV-pre is associated with significantly worse OS in inoperable stage III NSCLC treated with definitive CRT. Our findings suggest that for patients with large tMTV-pre, achieving a therapeutic radiation dose may help maximize OS. Prospective studies are needed to confirm this finding.

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References

  1. Siegel R, Ma J, Zou Z, Jemal A. Cancer statistics, 2014. CA Cancer J Clin. 2014;64(1):9–29.

    Article  PubMed  Google Scholar 

  2. Brundage MD, Davies D, Mackillop WJ. Prognostic factors in non-small cell lung cancer: a decade of progress. Chest. 2002;122(3):1037–57.

    Article  PubMed  Google Scholar 

  3. Goldstraw P, Crowley J, Chansky K, et al. The IASLC lung cancer staging project: proposals for the revision of the TNM stage groupings in the forthcoming (seventh) edition of the TNM classification of malignant tumours. J Thorac Oncol Off Publ Int Assoc Study Lung Cancer. 2007;2(8):706–14.

    Google Scholar 

  4. Chen HH, Chiu NT, Su WC, Guo HR, Lee BF. Prognostic value of whole-body total lesion glycolysis at pretreatment FDG PET/CT in non-small cell lung cancer. Radiology. 2012;264(2):559–66.

    Article  PubMed  Google Scholar 

  5. Lee P, Bazan JG, Lavori PW, et al. Metabolic tumor volume is an independent prognostic factor in patients treated definitively for non-small-cell lung cancer. Clin Lung Cancer. 2012;13(1):52–8.

    Article  PubMed  Google Scholar 

  6. Lee P, Weerasuriya DK, Lavori PW, et al. Metabolic tumor burden predicts for disease progression and death in lung cancer. Int J Radiat Oncol Biol Phys. 2007;69(2):328–33.

    Article  PubMed  Google Scholar 

  7. Liao S, Penney BC, Wroblewski K, et al. Prognostic value of metabolic tumor burden on 18F-FDG PET in nonsurgical patients with non-small cell lung cancer. Eur J Nucl Med Mol Imaging. 2012;39(1):27–38.

    Article  CAS  PubMed  Google Scholar 

  8. Obara P, Pu Y. Prognostic value of metabolic tumor burden in lung cancer. Chin J Cancer Res. 2013;25(6):615–22.

    PubMed  PubMed Central  Google Scholar 

  9. Zhang H, Wroblewski K, Appelbaum D, Pu Y. Independent prognostic value of whole-body metabolic tumor burden from FDG-PET in non-small cell lung cancer. Int J Comput Assist Radiol Surg. 2013;8(2):181–91.

    Article  PubMed  Google Scholar 

  10. Paesmans M, Berghmans T, Dusart M, et al. Primary tumor standardized uptake value measured on fluorodeoxyglucose positron emission tomography is of prognostic value for survival in non-small cell lung cancer: update of a systematic review and meta-analysis by the European Lung Cancer Working Party for the International Association for the Study of Lung Cancer Staging Project. J Thorac Oncol Off Publ Int Assoc Study Lung Cancer. 2010;5(5):612–9.

    Google Scholar 

  11. Vesselle H, Freeman JD, Wiens L, et al. Fluorodeoxyglucose uptake of primary non-small cell lung cancer at positron emission tomography: new contrary data on prognostic role. Clin Cancer Res Off J Am Assoc Cancer Res. 2007;13(11):3255–63.

    Article  CAS  Google Scholar 

  12. Machtay M, Duan F, Siegel BA, et al. Prediction of survival by [18F]fluorodeoxyglucose positron emission tomography in patients with locally advanced non-small-cell lung cancer undergoing definitive chemoradiation therapy: results of the ACRIN 6668/RTOG 0235 trial. J Clin Oncol Off J Am Soc Clin Oncol. 2013;31(30):3823–30.

    Article  CAS  Google Scholar 

  13. Graves EE, Quon A, Loo Jr BW. RT_Image: an open-source tool for investigating PET in radiation oncology. Technol Cancer Res Treat. 2007;6(2):111–21.

    Article  PubMed  Google Scholar 

  14. Therneau TM, Grambsch PM. Modeling survival data : extending the Cox model. New York: Springer; 2000.

    Book  Google Scholar 

  15. Ohri N, Duan F, Machtay M, et al. Pretreatment FDG-PET metrics in stage III non-small cell lung cancer: ACRIN 6668/RTOG 0235. J Natl Cancer Inst. 2015;107 Suppl 4.

  16. Bradley JD, Ieumwananonthachai N, Purdy JA, et al. Gross tumor volume, critical prognostic factor in patients treated with three-dimensional conformal radiation therapy for non-small-cell lung carcinoma. Int J Radiat Oncol Biol Phys. 2002;52(1):49–57.

    Article  PubMed  Google Scholar 

  17. Werner-Wasik M, Swann RS, Bradley J, et al. Increasing tumor volume is predictive of poor overall and progression-free survival: secondary analysis of the Radiation Therapy Oncology Group 93–11 phase I-II radiation dose-escalation study in patients with inoperable non-small-cell lung cancer. Int J Radiat Oncol Biol Phys. 2008;70(2):385–90.

    Article  PubMed  Google Scholar 

  18. Bradley JD, Paulus R, Komaki R, et al. Standard-dose versus high-dose conformal radiotherapy with concurrent and consolidation carboplatin plus paclitaxel with or without cetuximab for patients with stage IIIA or IIIB non-small-cell lung cancer (RTOG 0617): a randomised, two-by-two factorial phase 3 study. Lancet Oncol. 2015;16(2):187–99.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Kong F-M MM, Bradley J, et al. RTOG 1106/ACRIN 6697: Randomized phase II trial of individualized adaptive radiotherapy using during-treatment FDG-PET/CT and modern technology in locally advanced non-small cell lung cancer. http://www.rtog.org/ClinicalTrials/ProtocolTable/StudyDetails.aspx?study=1106. 2011.

  20. Suissa S. Immortal time bias in pharmaco-epidemiology. Am J Epidemiol. 2008;167(4):492–9.

    Article  PubMed  Google Scholar 

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Acknowledgments

Dr. Duan and Mr. Snyder had access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Bazan, Loo

Acquisition, analysis or interpretation of data: Bazan, Loo, Duan, Snyder

Drafting of the manuscript: Bazan, Loo, Duan, Snyder

Critical revision of the manuscript for important intellectual content: All authors

Statistical analysis: Duan, Snyder

Author information

Authors and Affiliations

  1. Department of Radiation Oncology, The Ohio State University, 460 W. 10th Avenue, Columbus, OH, 43210, USA

    Jose G. Bazan

  2. Department of Biostatistics and Center for Statistical Sciences, Brown University School of Public Health, Providence, RI, USA

    Fenghai Duan

  3. Center for Statistical Sciences, Brown University School of Public Health, Providence, RI, USA

    Bradley S. Snyder

  4. ECOG-ACRIN Cancer Research Group, Philadelphia, PA, USA

    Dunstan Horng

  5. Department of Radiation Oncology, Stanford Cancer Institute, School of Medicine, Stanford University, 875 Blake Wilbur Drive, Stanford, CA, 94305-5847, USA

    Edward E. Graves & Billy W. Loo Jr

  6. Mallinckrodt Institute of Radiology and the Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, USA

    Barry A. Siegel

  7. Case Comprehensive Cancer Center and Case Western Reserve University, University Hospitals Seidman Cancer Center, Cleveland, OH, USA

    Mitchell Machtay

Authors
  1. Jose G. Bazan
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  2. Fenghai Duan
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  3. Bradley S. Snyder
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  4. Dunstan Horng
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  5. Edward E. Graves
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  6. Barry A. Siegel
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  7. Mitchell Machtay
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  8. Billy W. Loo Jr
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Corresponding authors

Correspondence to Jose G. Bazan or Billy W. Loo Jr.

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Funding

ACRIN receives funding from the National Cancer Institute through grants U01 CA079778 and UO1 CA080098.

Conflict of interest

Dr. Loo receives research support from Varian Medical Systems and RaySearch Laboratories, and is a board member of TibaRay, Inc. Authors Jose G. Bazan, Fenghai Duan, Bradley S. Snyder, Dunstan Horng, Edward E. Graves, Barry A. Siegel, and Mitchell Machtay declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

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Bazan, J.G., Duan, F., Snyder, B.S. et al. Metabolic tumor volume predicts overall survival and local control in patients with stage III non-small cell lung cancer treated in ACRIN 6668/RTOG 0235. Eur J Nucl Med Mol Imaging 44, 17–24 (2017). https://doi.org/10.1007/s00259-016-3520-4

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  • DOI: https://doi.org/10.1007/s00259-016-3520-4

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