Non-relapse mortality in allogeneic haemopoietic stem cell transplantation (alloHSCT) is driven by acute graft-versus-host disease (aGVHD) and infection. The MAGIC Algorithm Probability (MAP) composite biomarker score is based on serum ST2 and REG3a levels at day(D) 7 post-transplant and predicts aGVHD-related mortality. While changes in MAP score predict aGVHD treatment response, their post-transplant predictive value and association with infection-related NRM (iNRM), independent of GVHD, are unclear. We evaluated the association of D0-21 MAP change (MAPΔ) versus D7 MAP with 6-month NRM (6mNRM) and developed a risk stratification model using random forest analysis and recursive partitioning. We prospectively enrolled 101 adult alloHSCT recipients from 2022-2024. Serum was collected weekly from D0-21 to derive MAPΔ. Associations with 6-month NRM were assessed using generalized linear and random forest modelling. 6mNRM was 14.8%, with 80% (12/15) of deaths attributed to infection without prior aGVHD. Both MAPΔ ≥0.055 and D7 MAP ≥0.16 were significantly associated with 6mNRM (p0.0001), with MAPΔ showing superior predictive accuracy (Receiver Operator Characteristic AUC 0.934 vs. 0.779). In multivariable analysis, MAPΔ (OR 45; 95% CI 10.6-318; p=0.01), but not D7 MAP, was an independent predictor of 6mNRM. A classification tree incorporating MAPΔ, D7 MAP, and age-adjusted comorbidity index stratified patients into low, intermediate, and high-risk groups. MAPΔ was a powerful, independent predictor of 6mNRM, which was driven by infection rather than aGVHD in this cohort. We propose a tool based on MAPΔ to assess iNRM, which may guide interventions and clinical trial design. Further validation in larger cohorts is warranted.
Tan et al. (Thu,) studied this question.
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