مراجعة PREreview لDiagnostic accuracy of a single-reaction, pan-lineage Lassa virus RT-PCR at two Nigerian laboratories: a retrospective and prospective cohort study
- نُشرت
- DOI
- 10.5281/zenodo.24095257
- الترخيص
- CC BY 4.0
This study evaluates PANDAA LASV, a single-reaction RT-PCR assay for detecting Lassa virus, using 296 clinical samples from two Nigerian laboratories. The assay showed 98.6% sensitivity and 99.4% specificity compared with RealStar RT-PCR (the current standard). Only three samples remained discordant after repeat testing; performance was similar across both sites.
I think this is a meaningful contribution given Lassa virus has substantial genetic variation, making it difficult to develop a single assay that detects different lineages. The study provides promising clinical evidence that a single-reaction test could perform comparably to the current two-reaction method, while potentially reducing laboratory costs and workload.
Major issues
Although PANDAA is designed to detect all seven Lassa virus lineages, the clinical samples mainly represented lineages II and III. The authors should be more cautious about generalizing their findings to other lineages without additional clinical evidence.
Initially, 18 samples had conflicting results between the two assays, but only three remained discordant after repeat testing. Interestingly, 14 samples initially positive by RealStar became negative upon retesting. Without a third independent assay, it is difficult to determine whether these differences resulted from testing variability or false positives. I think this deserves more discussion because it directly affects how we interpret the reported sensitivity and specificity.
The study was funded by Aldatu Biosciences, the developer of PANDAA LASV, and the corresponding author is affiliated with the company. This does not necessarily undermine the findings, but independent validation would make the results more convincing!
Minor issues
The authors mention that PANDAA could reduce costs, turnaround time, and laboratory workload. However, these outcomes were not actually measured.
Competing interests
The author declares that they have no competing interests.
Use of Artificial Intelligence (AI)
The author declares that they did not use generative AI to come up with new ideas for their review.