A predictive model for risk of early grade >= 3 infection in patients with multiple myeloma not eligible for transplant: analysis of the FIRST trial
- Authors
- Dumontet, Charles; Hulin, Cyrille; Dimopoulos, Meletios A.; Belch, Andrew; Dispenzieri, Angela; Ludwig, Heinz; Rodon, Philippe; Van Droogenbroeck, Jan; Qiu, Lugui; Cavo, Michele; Van de Velde, Ann; Lahuerta, Juan Jose; Allangba, Olivier; Lee, Jae Hoon; Boyle, Eileen; Perrot, Aurore; Moreau, Philippe; Manier, Salomon; Attal, Michel; Roussel, Murielle; Mohty, Mohamad; Mary, Jean Yves; Civet, Alexandre; Costa, Bruno; Tinel, Antoine; Gaston-Mathe, Yann; Facon, Thierry
- Issue Date
- Jun-2018
- Publisher
- NATURE PUBLISHING GROUP
- Citation
- LEUKEMIA, v.32, no.6, pp.1404 - 1413
- Journal Title
- LEUKEMIA
- Volume
- 32
- Number
- 6
- Start Page
- 1404
- End Page
- 1413
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/3688
- DOI
- 10.1038/s41375-018-0133-x
- ISSN
- 0887-6924
- Abstract
- Infections are a major cause of death in patients with multiple myeloma. A post hoc analysis of the phase 3 FIRST trial was conducted to characterize treatment-emergent (TE) infections and study risk factors for TE grade >= 3 infection. The number of TE infections/month was highest during the first 4 months of treatment (defined as early infection). Of 1613 treated patients, 340 (21.1%) experienced TE grade >= 3 infections in the first 18 months and 56.2% of these patients experienced their first grade >= 3 infection in the first 4 months. Risk of early infection was similar regardless of treatment. Based on the analyses of data in 1378 patients through multivariate logistic regression, a predictive model of first TE grade >= 3 infection in the first 4 months retained Eastern Cooperative Oncology Group performance status and serum beta(2)-microglobulin, lactate dehydrogenase, and hemoglobin levels to define high-and low-risk groups showing significantly different rates of infection (24.0% vs. 7.0%, respectively; P < 0.0001). The predictive model was validated with data from three clinical trials. This predictive model of early TE grade >= 3 infection may be applied in the clinical setting to guide infection monitoring and strategies for infection prevention.
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