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Optimal PET-based radiomic signature construction based on the cross-combination method for predicting the survival of patients with diffuse large B-cell lymphoma

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Abstract

Purpose

To develop and externally validate models incorporating a PET radiomics signature (R-signature) obtained by the cross-combination method for predicting the survival of patients with diffuse large B-cell lymphoma (DLBCL).

Methods

A total of 383 patients with DLBCL from two medical centres between 2011 and 2019 were included. The cross-combination method was used on three types of PET radiomics features from the training cohort to generate 49 feature selection-classification candidates based on 7 different machine learning models. The R-signature was then built by selecting the optimal candidates based on their progression-free survival (PFS) and overall survival (OS). Cox regression analysis was used to develop the survival prediction models. The calibration, discrimination, and clinical utility of the models were assessed and externally validated.

Results

The R-signatures determined by 12 and 31 radiomics features were significantly associated with PFS and OS, respectively (P<0.05). The combined models that incorporated R-signatures, metabolic metrics, and clinical risk factors exhibited significant prognostic superiority over the clinical models, PET-based models, and the National Comprehensive Cancer Network International Prognostic Index in terms of both PFS (C-index: 0.801 vs. 0.732 vs. 0.785 vs. 0.720, respectively) and OS (C-index: 0.807 vs. 0.740 vs. 0.773 vs. 0.726, respectively). For external validation, the C-indices were 0.758 vs. 0.621 vs. 0.732 vs. 0.673 and 0.794 vs. 0.696 vs. 0.781 vs. 0.708 in the PFS and OS analyses, respectively. The calibration curves showed good consistency, and the decision curve analysis supported the clinical utility of the combined model.

Conclusion

The R-signature could be used as a survival predictor for DLBCL, and its combination with clinical factors may allow for accurate risk stratification.

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Data availability

The datasets generated and analysed during the current study are available from the Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School, and the Jiangsu Province Hospital, the First Affiliated Hospital of Nanjing Medical University.

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Funding

This work was partially supported by fundings for Clinical Trials from the Affiliated Drum Tower Hospital, Medical School of Nanjing University under Grant No. 2021-LCYJ-MS-04.

This work was also partially supported by fundings for the Key Project of Medical Science and Technology of Nanjing under Grant No.ZKX21011.

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Authors and Affiliations

  1. Department of Nuclear Medicine, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, 210000, China

    Chong Jiang, Yue Teng & Zhengyang Zhou

  2. The Key Laboratory of Broadband Wireless Communication and Sensor Network Technology (Ministry of Education), Nanjing University of Posts and Telecommunications, Nanjing, China

    Ang Li, Xiangjun Huang & Jianxin Chen

  3. Department of Nuclear Medicine, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, China

    Chongyang Ding

  4. Department of Hematology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, 210000, China

    Jingyan Xu

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  1. Chong Jiang
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  2. Ang Li
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  3. Yue Teng
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Contributions

Chong Jiang, Ang Li, Yue Teng, Xiangjun Huang, and Chongyang Ding collected data and analysed data; Jingyan Xu, Jianxin Chen, and Zhengyang Zhou participated in the research design; Chong Jiang and Ang Li contributed to the writing of the manuscript, discussed data, and supervised the study, and all authors performed data analysis and interpretation and read and approved the final version of the article.

Corresponding authors

Correspondence to Jianxin Chen, Jingyan Xu or Zhengyang Zhou.

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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 Helsinki declaration and its later amendments or comparable ethical standards.

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Chong Jiang and Ang Li are co-first authors. They contributed equally to the work.

This article is part of the Topical Collection on Hematology

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Jiang, C., Li, A., Teng, Y. et al. Optimal PET-based radiomic signature construction based on the cross-combination method for predicting the survival of patients with diffuse large B-cell lymphoma. Eur J Nucl Med Mol Imaging 49, 2902–2916 (2022). https://doi.org/10.1007/s00259-022-05717-9

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