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Advancing precision medicine in immunoglobulin light-chain amyloidosis: a novel prognostic model incorporating multi-organ indicators

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Abstract

To develop a more accurate prognostic model that incorporates indicators of multi-organ involvement for immunoglobulin light-chain (AL) Amyloidosis patients. Biopsy-proven AL amyloidosis patients between January 1, 2012, and February 28, 2023, were enrolled and randomly divided into a training set and a test set at a ratio of 7:3. Prognostic indicators that comprehensively cover cardiac, renal, and hepatic involvement were identified in the training set by random survival forest (RSF). Then, RSF and Cox models were established. The Concordance index (C-index) and integrated brier scores (IBS) were applied to evaluate the models’ performance in the test set. Besides, the net reclassification index (NRI) and integrated discrimination improvement (IDI) were calculated. A total of 173 eligible patients were included. After a median follow-up of 25.9 (9.2, 50.3) months, 48 (27.7%) patients died. Creatine kinase-MB, estimated glomerular filtration rate ≤ 50 mL/min/1.73 m2, interventricular septum ≥ 15 mm, ejection fraction, alanine aminotransferase and Live involved were selected to develop prediction models. The RSF model based on the above indicators achieved C-index and IBS values of 0.834 (95% CI 0.725–0.915) and 0.151 (95% CI 0.1402–0.181), respectively. At last, the NRI and IDI of the RSF model were 0.301 (95% CI 0.048–0.546, P = 0.012) and 0.157 (95% CI 0.041–0.269, P < 0.001) at 5-year by comparing the RSF model with the Cox model which is based on the Mayo 2012 staging system. The RSF model that incorporates indicators of multi-organ involvement had a great performance, which may be helpful for physicians’ decision-making and more accurate overall survival prediction.

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Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

The authors would like to acknowledge all statisticians for participating in this study.

Funding

This work was supported by the National Natural Science Foundation of China (grants number 82170722, 82270715), Key Research and Development Plan of Shaanxi Province (grants number No.2023-ZDLSF-15), Research topic of clinical application of military medicine in Xijing Hospital (Reference number: JSYYZ05), Clinical research project of Fourth Military Medical University (grants number 2021LC2205), and Postdoctoral Lan Jian Sustentation Fund of the Fourth Military Medical University (grants number lj20220102).

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Author notes

  1. Yan Xing, Xiayin Li, and Jin Zhao have contributed equally to this work and share the first authorship.

Authors and Affiliations

  1. Department of Nephrology, Xijing Hospital, The Fourth Military Medical University, No.127 Chang Le West Road, Xi’an, 710032, Shaanxi, China

    Yan Xing, Xiayin Li, Jin Zhao, Hao Wu, Lijuan Zhao, Wanting Zheng & Shiren Sun

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  1. Yan Xing
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  7. Shiren Sun
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Contributions

Y. Xing and S. Sun: Conceptualization; Y. Xing, and J. Zhao: Methodology; X. Li and W. Zheng: Data curation; X. Li and Y. Xing: Writing- Original draft preparation; Y. Xing, X. Li, H. Wu and L. Zhao: Visualization and Supervision. S. Sun: Validation and Writing- Reviewing and Editing.

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Correspondence to Shiren Sun.

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Xing, Y., Li, X., Zhao, J. et al. Advancing precision medicine in immunoglobulin light-chain amyloidosis: a novel prognostic model incorporating multi-organ indicators. Intern Emerg Med (2024). https://doi.org/10.1007/s11739-024-03621-8

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