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Methods for the Field Evaluation of Quantitative G6PD Diagnostics: a Review

Overview
Journal Malar J
Publisher Biomed Central
Specialty Tropical Medicine
Date 2017 Sep 13
PMID 28893237
Citations 36
Authors
Affiliations
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Abstract

Individuals with glucose-6-phosphate dehydrogenase (G6PD) deficiency are at risk of severe haemolysis following the administration of 8-aminoquinoline compounds. Primaquine is the only widely available 8-aminoquinoline for the radical cure of Plasmodium vivax. Tafenoquine is under development with the potential to simplify treatment regimens, but point-of-care (PoC) tests will be needed to provide quantitative measurement of G6PD activity prior to its administration. There is currently a lack of appropriate G6PD PoC tests, but a number of new tests are in development and are likely to enter the market in the coming years. As these are implemented, they will need to be validated in field studies. This article outlines the technical details for the field evaluation of novel quantitative G6PD diagnostics such as sample handling, reference testing and statistical analysis. Field evaluation is based on the comparison of paired samples, including one sample tested by the new assay at point of care and one sample tested by the gold-standard reference method, UV spectrophotometry in an established laboratory. Samples can be collected as capillary or venous blood; the existing literature suggests that potential differences in capillary or venous blood are unlikely to affect results substantially. The collection and storage of samples is critical to ensure preservation of enzyme activity, it is recommended that samples are stored at 4 °C and testing occurs within 4 days of collection. Test results can be visually presented as scatter plot, Bland-Altman plot, and a histogram of the G6PD activity distribution of the study population. Calculating the adjusted male median allows categorizing results according to G6PD activity to calculate standard performance indicators and to perform receiver operating characteristic (ROC) analysis.

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