Prognostic outcomes of cytomegalovirus reactivation after autologous stem cell transplantation

Abstract

Background: Cytomegalovirus (CMV) reactivation is a common complication in patients undergoing allogeneic stem cell transplantation. However, the incidence of CMV reactivation is low after autologous stem cell transplantation (auto-SCT), and the prognostic value of CMV reactivation remains controversial. Moreover, reports on late CMV reactivation after auto-SCT are limited. We aimed to analyze the association between CMV reactivation and survival outcomes and develop a predictive model for late CMV reactivation in patients undergoing auto-SCT. Methods: Data of 201 patients who underwent SCT at the Korea University Medical Center from 2007 to 2018 were collected. We analyzed prognostic factors for survival outcomes after auto-SCT and risk factors for late CMV reactivation using a receiver operating characteristic curve. Then, we developed a predictive risk model for late CMV reactivation based on results of the risk factor analysis. Results: Early CMV reactivation was significantly associated with better overall survival (OS) (hazard ratio [HR], 0.329; P = 0.045) in patients with multiple myeloma; however, no significant differences were observed in patients with lymphoma. For late CMV reactivation, a serum lactate dehydrogenase level greater than the upper limit of normal (HR, 2.251; P = 0.027) and late CMV reactivation (HR, 2.964; P = 0.047) were independent risk factors for poor OS, while lymphoma diagnosis (vs. multiple myeloma; HR, 0.389; P = 0.016) was an independent risk factor for good OS. In risk factor analysis for late CMV reactivation, T-cell lymphoma diagnosis (odds ratio [OR], 8.499; P = 0.029), ≥ two prior chemotherapies (OR, 8.995; P = 0.027), failure to achieve complete response (CR) after transplantation (OR, 7.124; P = 0.031), and early CMV reactivation (OR, 12.853; P = 0.007) were significantly associated with late CMV reactivation. To develop the predictive risk model for late CMV reactivation, a score (1 to 1.5) was assigned for each of the above-mentioned variables. The optimal cutoff value (1.75 points) was calculated using the receiver operating characteristic curve. The predictive risk model showed good discrimination, with an area under the curve of 0.872 (standard error, 0.062; P < 0.001). Conclusions: Late CMV reactivation was an independent risk factor for inferior OS, whereas early CMV reactivation was associated with better survival in patients with multiple myeloma. This risk prediction model could be helpful in identifying high-risk patients who require monitoring for late CMV reactivation and potentially benefit from prophylactic or preemptive therapy.