ORIGINAL RESEARCH article
Front. Oncol.
Sec. Hematologic Malignancies
Construction and validation of a simple, scoreable model for predicting infection risk in patients with multiple myeloma:A Retrospective Single-Center Study
Provisionally accepted
- Jishou University First Affiliated Hospital, Jishou, China
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Objective This study aims to identify the risk factors for infection in patients with multiple myeloma and to develop a predictive model for infection. Methods We retrospectively analyzed the clinical data of 180 multiple myeloma patients undergoing chemotherapy at the First Affiliated Hospital of Jishou University from January 2017 to December 2022. A predictive model for infection events was constructed based on this data. Results In the modeling group, 34 out of 90 patients (37.78%) experienced infections, while in the validation group, 40 out of 90 patients (44.44%) were reported to have infections. Binary logistic regression analysis revealed that the levels of C-reactive protein, fasting blood glucose, lactate dehydrogenase, the ECOG score, and the percentage of bone marrow plasma cells were independent risk factors for infection in patients with multiple myeloma (P < 0.05). The infection prediction model developed using these variables demonstrated good accuracy, with the area under the ROC curve for the modeling group being 0.827 (95% CI: 73.66% - 91.78%) and for the validation group being 0.760 (95% CI: 65.97% - 85.93%). Conclusion This study confirms that C-reactive protein levels, fasting blood glucose levels, lactate dehydrogenase levels, ECOG scores, and the percentage of bone marrow plasma cells are significant risk factors for infection in patients with multiple myeloma. Clinical Significance This infection prediction model possesses transformative potential: it empowers clinicians to move from reactive care to proactive, preemptive intervention, reshaping the future of infection management in this vulnerable population.
Keywords: Multiple Myeloma, Infection, Scoring model, Risk factors, Predicting infection
Received: 25 Jul 2025; Accepted: 07 Nov 2025.
Copyright: © 2025 Tu, Yang, Min, Fan, Hu, Tian, Li and Song. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Min Li, lucyminmin@163.com
Kui Song, js_hematology@163.com
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