Ilesh V. Jani Instituto Nacional de Saúde Mozambique Field Evaluations of Point-Of-Care Virologic Technologies for Early Infant Diagnosis Ilesh V. Jani Instituto Nacional de Saúde Mozambique

What are we trying to find out with a field evaluation? Is the performance of the new test (or testing algorithm) worse/as good as/better than the current diagnostic option? Is the new test (or testing algorithm) worse/as good as/better for patients? Is the new test (or testing algorithm) worse/as good as/better for health systems?

Some factors that influence the quality and the impact of diagnostic test evaluations Study design Measured outcomes Risk of bias Study settings Precision of evidence Data analysis and publication Adapted from: Schünemann et al (2008); BMJ

1 & 2. Study design and measured outcomes Randomised controlled trials are the best way to evaluate new tests “Accuracy/Precision” studies are more prone to bias but have been the only “viable” option for EID tests Test evaluations should measure patient-important outcomes Evaluations should measure (or infer) system-important outcomes From: Schünemann et al (2008); BMJ

3. Risk of bias Consecutive patients under routine conditions No “enrichment” by disease or biomarker status Well defined inclusion/exclusion criteria Blinding of test results

4. Study settings Study sites – differences between type of health facilities where study takes place and those where test will be deployed Study population – differences between infants studied and those for whom test is intended Test operators – differences between type of operators in the study and those who will use it in the health system

4. Study settings – how to select study sites? Annual EID Volume per Site – Mozambique 2012 60 sites account for 50% of annual volume Weekly EID Volume per Site – Mozambique 2012 More than 10 samples per week (n=16) Less than 2 samples per week (n=460)

5. Precision of evidence Wide confidence intervals impact the quality of evidence Low number of HIV+ children in studies Implications for length, size and budget of studies Sensitivity and specificity of a POC NAT EID Assay From: Jani et al (2014); JAIDS

6. Data analysis and publication Data analysis should consider: Analytical performance Analytical performance of the test at a single time point vs. within a testing algorithm Operational performance Potential increase in access to tests and treatment Potential decrease in diagnostic delays and associated risks, including reduced anxiety and loss to follow up Cost-efficiency issues Budget impact Publication bias

6. Data analysis – balance test performance with access issues A point-of-care assay with a lower sensitivity may still effectively reach more infants due to lower rates of loss to follow up EID program indicators in Mozambique are reaching a plateau due to health system limitations

Final remarks Deployment of novel EID assays should be informed by high quality evaluations under field conditions Evaluations should measure patient-important and system-important outcomes Decisions about the incorporation of new EID assays in health systems should take into consideration other factors then just test performance

Acknowledgements Ministério da Saúde, Moçambique Instituto Nacional de Saúde, Moçambique Clinton Health Access Initiative