Retrospective analysis reveals risk-based testing improves cost-effectiveness in adenovirus management for transplant patients, indicating potential benefits over routine monitoring.
Adenovirus infection (AdVi) causes significant morbidity and mortality in allogeneic hematopoietic stem cell transplantation (allo-HCT) recipients. This retrospective study of 131 patients (2020-2024) compared systematic monitoring in high-risk patients versus symptom-based testing in standard-risk patients. The 1-year incidence of AdV DNAemia was 19.8%, with AdV disease at 5.3%, being higher in the routine monitoring cohort (26%) than in the symptom-based cohort (11%, p = 0.031). Neither infection nor monitoring strategy impacted outcomes. The machine learning model identified predictive factors for early AdV DNAemia: age (50-65 years), diagnosis of acute leukemia or myelodysplastic syndrome, transplant from an HLA-matched unrelated or haploidentical donor, and non-myeloablative conditioning. Cost-effectiveness analysis showed that risk-based testing was optimal (€149 per additional detected case), while universal monitoring was excessively costly (€1006 per additional detected case). In conclusion, although AdVi was common, routine monitoring did not improve outcomes and was financially burdensome, suggesting that a machine learning-driven risk-based testing strategy enhances cost-effectiveness while ensuring timely AdV detection and intervention.
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Giménez et al. (2025) studied this question.
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