Publication Details

AFRICAN RESEARCH NEXUS

SHINING A SPOTLIGHT ON AFRICAN RESEARCH

medicine

Toward measuring Schistosoma response to praziquantel treatment with appropriate descriptors of egg excretion

PLoS Neglected Tropical Diseases, Volume 9, No. 6, Article e0003821, Year 2015

Background The control of schistosomiasis emphasizes preventive chemotherapy with praziquantel, which aims at decreasing infection intensity and thus morbidity in individuals, as well as transmission in communities. Standardizing methods to assess treatment efficacy is important to compare trial outcomes across settings, and to monitor program effectiveness consistently. We compared customary methods and looked at possible complementary approaches in order to derive suggestions for standardizing outcome measures. Methodology/Principal Findings We analyzed data from 24 studies conducted at African, Asian, and Latin American sites, enrolling overall 4,740 individuals infected with Schistosoma mansoni, S. haematobium, or S. japonicum, and treated with praziquantel at doses of 40–80 mg/kg. We found that groupbased arithmetic and geometric means can be used interchangeably to express egg reduction rates (ERR) only if treatment efficacy is high (>95%). For lower levels of efficacy, ERR estimates are higher with geometric than arithmetic means. Using the distribution of individual responses in egg excretion, 6.3%, 1.7% and 4.3% of the subjects treated for S. haematobium, S. japonicum and S. mansoni infection, respectively, had no reduction in their egg counts (ERR = 0). The 5th, 10th, and 25th centiles of the subjects treated for S. haematobium had individual ERRs of 0%, 49.3%, and 96.5%; the corresponding values for S. japonicum were 75%, 99%, and 99%; and for S. mansoni 18.2%, 65.3%, and 99.8%. Using a single rather than quadruplicate Kato-Katz thick smear excluded 19% of S. mansoni-infected individuals. Whilst the effect on estimating ERR was negligible by individual studies, ERR estimates by arithmetic means were 8% lower with a single measurement.

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Citations: 35
Authors: 16
Affiliations: 19
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Research Areas
Cancer
Infectious Diseases