Affiliation:
1. Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne
2. Menzies School of Health Research and Charles Darwin University
3. Infectious Disease Society Kota Kinabalu Sabah-Menzies School of Health Research Clinical Research Unit
4. Department of Medicine, University of Cambridge School of Clinical Medicine
5. Clinical Research Centre, Queen Elizabeth II Hospital, Ministry of Health
6. QIMR Berghofer Medical Research Institute
Abstract
Abstract
Background
The incidence of zoonotic Plasmodium knowlesi infections in humans is rising in Southeast Asia, leading to clinical studies to monitor the efficacy of antimalarial treatments for knowlesi malaria. One of the key outcomes of antimalarial drug efficacy is parasite clearance. For P. falciparum, parasite clearance is typically estimated using a two-stage method, that involves estimating parasite clearance for individual patients followed by pooling of individual estimates to derive population estimates. An alternative approach is Bayesian hierarchical modelling which simultaneously analyses all parasite-time patient profiles to determine parasite clearance. This study compared these methods for estimating parasite clearance in P. knowlesi treatment efficacy studies, with typically fewer parasite measurements per patient due to high susceptibility to antimalarials.
Methods
Using parasite clearance data from 714 patients with knowlesi malaria and enrolled in three trials, we compared the Worldwide Antimalarial Resistance Network (WWARN) Parasite Clearance Estimator (PCE) standard two-stage approach and Bayesian hierarchical modelling. Both methods estimate the parasite clearance rate from a model that incorporates a lag phase, slope, and tail phase for the parasitaemia profiles.
Results
The standard two-stage approach successfully estimated the parasite clearance rate for 678 patients, with 36 (5%) patients excluded due to an insufficient number of available parasitaemia measurements. The Bayesian hierarchical estimation method was applied to the parasitaemia data of all 714 patients. Overall, the Bayesian method estimated a faster population mean parasite clearance (0.36/hour, 95% credible interval [0.1759, 0.6524]) compared to the standard two-stage method (0.26/hour, 95% confidence interval [0.1093, 0.4596]), with better model fits (compared visually). The artemisinin-based combination therapies were more effective in treating P. knowlesi than chloroquine, as determined by both methods, with a mean estimated parasite clearance half-life of 2.5 and 3.6 hours respectively using the standard two-stage method, and 1.8 and 2.9 hours using the Bayesian method.
Conclusion
For clinical studies of P. knowlesi with frequent parasite measurements, we recommend the standard two-stage approach (WWARN’s PCE) as this method is straightforward to implement. For studies with fewer parasite measurements per patient, the Bayesian approach should be considered. Regardless of method used, artemisinin combination therapies are more efficacious than chloroquine.
Publisher
Research Square Platform LLC
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