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A prognostication system based on clinical parameters and [18F]-FDG PET/CT in patients with newly diagnosed multiple myeloma

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Abstract

Purpose

This study aimed to assess prognosis of patients with newly diagnosed multiple myeloma (NDMM) by combining [18F]-FDG positron emission tomography (PET)/CT parameters and clinical indices.

Methods

Clinical data and PET/CT parameters of 133 NDMM patients were retrospectively analyzed for associations between clinical indices and PET/CT parameters. Independent predictors of progression-free survival (PFS) and overall survival (OS) were determined. A new prognostic prediction system (NPPS) was constructed based on our findings. Prediction effectiveness was compared among the NPPS, International Staging System (ISS), Revised ISS (R-ISS), and R2-ISS.

Results

Prevalence of elevated β2-microglobulin, serum creatinine (sCr), serum calcium (sCa), and C-reactive protein concentrations was higher in patients with higher SUVmax (≥ 5.3). Prevalence of elevated sCa, sCr, and extramedullary disease (EMD) was higher in patients with a higher number of focal lesions (≥ 10). SUVmax, serum free-light chain (sFLC) ratio, and EMD were independent predictors of PFS and OS. The NPPS used SUVmax, sFLC ratio, and EMD could effectively predict OS and was more effective at prognostication than the ISS, R-ISS, and R2-ISS.

Conclusions

[18F]-FDG PET/CT parameters play a significant role in predicting prognosis in NDMM patients. The NPPS based on SUVmax, sFLC ratio, and EMD outperformed the ISS, R-ISS, and R2-ISS in prognostication.

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Data availability

Not applicable.

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Funding

This work was supported by the National Natural Science Foundation of China (No. 82030052).

Author information

Author notes

  1. Junlong Li and Xiao Zhang contribute equally to this work.

Authors and Affiliations

  1. Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277 Jiefang Ave, Wuhan, 430022, Hubei Province, China

    Junlong Li, Xiao Zhang, Chunxia Qin, Xun Sun, Xiaojun Xu, Guoxiang Cao, Yongkang Gai, Chunyan Sun, Yu Hu & Xiaoli Lan

  2. Hubei Province Key Laboratory of Molecular Imaging, No. 1277 Jiefang Ave, Wuhan, 430022, Hubei Province, China

    Junlong Li, Xiao Zhang, Chunxia Qin, Xun Sun, Xiaojun Xu, Guoxiang Cao, Yongkang Gai & Xiaoli Lan

  3. Key Laboratory of Biological Targeted Therapy, The Ministry of Education, Wuhan, China

    Junlong Li, Xiao Zhang, Chunxia Qin, Xun Sun, Xiaojun Xu, Guoxiang Cao, Yongkang Gai & Xiaoli Lan

  4. Department of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277 Jiefang Ave, Wuhan, 430022, Hubei Province, China

    Chunyan Sun & Yu Hu

Authors
  1. Junlong Li
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  2. Xiao Zhang
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  3. Chunxia Qin
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  4. Xun Sun
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  7. Yongkang Gai
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  9. Yu Hu
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  10. Xiaoli Lan
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Contributions

X. L. conceived and designed the study devised and supervised the project. X. Z. and J. L. finished the clinical experiments and wrote the manuscript. C. S. and Y. H. provided clinical data. Y. G. synthesized the probe and completed the examination. C. Q. and X. S. analyzed the image data. J. L., X. Z., G. C., and X. X. contributed to patient clinical data analysis.

Corresponding author

Correspondence to Xiaoli Lan.

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Ethical approval

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

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The requirement for informed consent was waived.

Conflict of interest

The authors declare no competing interests.

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This article is part of the Topical Collection on Hematology.

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Cite this article

Li, J., Zhang, X., Qin, C. et al. A prognostication system based on clinical parameters and [18F]-FDG PET/CT in patients with newly diagnosed multiple myeloma. Eur J Nucl Med Mol Imaging 50, 1665–1670 (2023). https://doi.org/10.1007/s00259-022-06088-x

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  • DOI: https://doi.org/10.1007/s00259-022-06088-x

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