Impact of Cytomegalovirus DNAemia Below the Lower Limit of Quantification: Multistate Model in Lung Transplant Recipients

Abstract

Background Cytomegalovirus (CMV) infections following transplantation lead to significant morbidity. Identification of CMV DNAemia continually improves and now viral loads below the lower limit of quantification (LLOQ) are detectable. However, the clinical course of positive CMV qPCR <LLOQ is unknown. Methods This retrospective study included lung transplant recipients experiencing their first episode of positive CMV qPCR <LLOQ with all qPCR assays conducted using COBAS® AmpliPrep/COBAS® TaqMan®. A Markov-like multistate model was utilized to describe the course of CMV DNAemia <LLOQ. A multivariable model was employed to identify predictors of transitioning to a positive, quantifiable state. Results 100 patients with a CMV <LLOQ result were included, encompassing 1,248 transitions in the six months following first episode of CMV qPCR <LLOQ. There was an 97.8% probability of remaining <LLOQ or undetectable and a 2.2% probability of transitioning to a positive, quantifiable qPCR state. The multivariable regression model identified treatment for rejection, increasing body mass index, valganciclovir therapy, and increasing CMV qPCR viral load as being predictive of transitioning from CMV qPCR undetectable or <LLOQ into a positive, quantifiable CMV qPCR state. Conclusions Most patients did not transition into a positive, quantifiable CMV qPCR state following a first episode of positive CMV qPCR <LLOQ in this cohort of lung transplant recipients.

Keywords

• cmv
• cytomegalovirus
• transplantation
• lung transplantation
• pcr
• quantitative pcr
• polymerase chain reaction
• markov model
• lower limit of quantification
• quantifiable cmv qpcr
• valganciclovir
• rejection