A clinical algorithm identifies high risk pediatric oncology and bone marrow transplant patients likely to benefit from treatment of adenoviral infection

Background: Adenoviral infections cause morbidity and mortality in blood and marrow transplantation and pediatric oncology patients. Cidofovir is active against adenovirus, but must be used judiciously because of its nephrotoxicity and unclear indications. Therefore, before introducing cidofovir use during an adenoviral outbreak, we developed a clinical algorithm to distinguish low risk patients from those who merited cidofovir therapy because of significant adenoviral disease and high risk for death. OBJECTIVE: This study was conducted to determine whether the algorithm accurately predicted severe adenovirus disease and whether selective cidofovir treatment was beneficial. STUDY DESIGN: A retrospective analysis of a pediatric oncology/blood and marrow transplantation cohort prealgorithm and postalgorithm implementation was performed. Results: Twenty patients with adenovirus infection were identified (14 high risk and 6 low risk). All low-risk patients cleared their infections without treatment. Before algorithm implementation, all untreated high-risk patients died, 4 out of 5 (80%), from adenoviral infection. In contrast, cidofovir reduced adenovirus-related mortality in the high-risk group postalgorithm implementation (9 patients treated, 1 patient died; RR 0.14, P<0.05) and all treated high-risk patients cleared their virus. Conclusions: The clinical algorithm accurately identified patients at high risk for severe fatal adenoviral disease who would benefit from selective use of cidofovir.