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Volume-based predictive biomarkers of sequential FDG-PET/CT for sunitinib in cancer of unknown primary: identification of the best benefited patients

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

Abstract

Purpose

To test the performance of sequential 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) in predicting survival after sunitinib therapies in patients with cancer of unknown primary (CUP).

Methods

CUP patients were enrolled for sequential PET/CT scanning for sunitinib and a control group. Univariate and multivariate analysis were applied to test the efficacy of sunitinib therapy in CUP patients. Next, sequential analyses involving PET/CT parameters were performed to identify and validate sensitive PET/CT biomarkers for sunitinib therapy. Finally, time-dependent receiver operating characteristic (TDROC) analyses were performed to compare the predictive accuracy.

Results

Multivariate analysis proved that sunitinib group had significantly improved survival (p < 0.01) as compared to control group. After cycle 2 of therapy, multivariate analysis identified volume-based PET/CT parameters as sensitive biomarkers for sunitinib (p < 0.01). TDROC curves demonstrated whole-body total lesion glycolysis reduction (Δ WTLG) and follow-up WTLG to have good accuracy for efficacy prediction. This evidence was validated after cycle 4 of therapy with the same method.

Conclusion

Sunitinib therapy proved effective in treatment of CUP. PET/CT volume-based parameters may help predict outcome of sunitinib therapy, in which Δ WTLG and follow-up WTLG seem to be sensitive biomarkers for sunitinib efficacy. Patients with greater reduction and lower WTLG at follow-up seem to have better survival outcome.

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Author notes

    Authors and Affiliations

    1. Department of Orthorpedic Oncology, Changzheng Hospital, Second Military Medical University, 415 Fengyang Road, Shanghai, 200003, China

      Yifei Ma, Wei Xu & Jianru Xiao

    2. Department of Pathology, Changzheng Hospital, Second Military Medical University, 415 Fengyang Road, Shanghai, 200003, China

      Yifei Ma & Hongyu Yu

    3. Department of Geriatrics, Tianjin Medical University General Hospital, Laboratory of Neuro-Trauma and Neurodegenerative Disorder, Geriatrics Institute, Tianjin, 300352, China

      Ruojing Bai

    4. Department of Neuro-oncology, Neurosurgery Institute, Beijing, 100000, China

      Yiming Li

    5. Department of PET/CT Radiology, Panorama Medical Imaging Center, Shanghai, China

      Chunshan Yang

    6. Department of PET/CT Radiology Center, Number 85 Hospital of PLA, 1328 Huashan Road, Shanghai, 200004, China

      Chunshan Yang, Huazheng Shi & Jian Zhang

    7. Department of Stomatology, The First People’s Hospital of Shangqiu, Shangqiu, 476100, Henan Province, China

      Jidong Li

    8. Department of Radiology, Changzheng Hospital, Second Military Medical University, 415 Fengyang Road, Shanghai, 200003, China

      Chenguang Wang

    Authors
    1. Yifei Ma
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    2. Wei Xu
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    3. Ruojing Bai
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    5. Hongyu Yu
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    Corresponding authors

    Correspondence to Hongyu Yu or Jianru Xiao.

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    Funding

    This study was supported by the joint taking program of key disease (Grant 2014ZYJB0103) and the Shanghai Youth Science and Technology Talent Sailing Program (Grant 14YF1405900).

    Conflicts of interest

    None.

    Ethical approval

    All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional review board and with the principles of the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

    Informed consent

    All patients gave informed consent to the treatment, PET/CT scanning and participation in study.

    Additional information

    Yifei Ma, Wei Xu contributed equally to this work.

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    Ma, Y., Xu, W., Bai, R. et al. Volume-based predictive biomarkers of sequential FDG-PET/CT for sunitinib in cancer of unknown primary: identification of the best benefited patients. Eur J Nucl Med Mol Imaging 44, 199–205 (2017). https://doi.org/10.1007/s00259-016-3504-4

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    • DOI: https://doi.org/10.1007/s00259-016-3504-4

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