Publication Details

AFRICAN RESEARCH NEXUS

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medicine

Blood Parasite Load as an Early Marker to Predict Treatment Response in Visceral Leishmaniasis in Eastern Africa

Clinical Infectious Diseases, Volume 73, No. 5, Year 2021

Background: To expedite the development of new oral treatment regimens for visceral leishmaniasis (VL), there is a need for early markers to evaluate treatment response and predict long-term outcomes. Methods: Data from 3 clinical trials were combined in this study, in which Eastern African VL patients received various antileishmanial therapies. Leishmania kinetoplast DNA was quantified in whole blood with real-time quantitative polymerase chain reaction (qPCR) before, during, and up to 6 months after treatment. The predictive performance of pharmacodynamic parameters for clinical relapse was evaluated using receiver-operating characteristic curves. Clinical trial simulations were performed to determine the power associated with the use of blood parasite load as a surrogate endpoint to predict clinical outcome at 6 months. Results: The absolute parasite density on day 56 after start of treatment was found to be a highly sensitive predictor of relapse within 6 months of follow-up at a cutoff of 20 parasites/mL (area under the curve 0.92, specificity 0.91, sensitivity 0.89). Blood parasite loads correlated well with tissue parasite loads (ρ=0.80) and with microscopy gradings of bone marrow and spleen aspirate smears. Clinical trial simulations indicated a > 80% power to detect a difference in cure rate between treatment regimens if this difference was high (> 50%) and when minimally 30 patients were included per regimen. Conclusions: Blood Leishmania parasite load determined by qPCR is a promising early biomarker to predict relapse in VL patients. Once optimized, it might be useful in dose finding studies of new chemical entities.
Statistics
Citations: 16
Authors: 16
Affiliations: 9
Identifiers
Research Areas
Genetics And Genomics
Health System And Policy
Study Design
Cohort Study
Study Approach
Quantitative