Comparison of measles IgG enzyme immunoassays (EIA) versus plaque reduction neutralization test (PRNT) for measuring measles serostatus: a systematic review of head-to-head analyses of measles IgG EIA and PRNT
Bibliographic record
Abstract
BACKGROUND: As countries move towards or achieve measles elimination status, serosurveillance is an important public health tool. However, a major challenge of serosurveillance is finding a feasible, accurate, cost-effective, and high throughput assay to measure measles antibody concentrations and estimate susceptibility in a population. We conducted a systematic review to assess, characterize, and - to the extent possible - quantify the performance of measles IgG enzyme-linked assays (EIAs) compared to the gold standard, plaque reduction neutralization tests (PRNT). METHODS: We followed the PRISMA statement for a systematic literature search and methods for conducting and reporting systematic reviews and meta-analyses recommended by the Cochrane Screening and Diagnostic Tests Methods Group. We identified studies through PubMed and Embase electronic databases and included serologic studies detecting measles virus IgG antibodies among participants of any age from the same source population that reported an index (any EIA or multiple bead-based assays, MBA) and reference test (PRNT) using sera, whole blood, or plasma. Measures of diagnostic accuracy with 95% confidence intervals (CI) were abstracted for each study result, where reported. RESULTS: We identified 550 unique publications and identified 36 eligible studies for analysis. We classified studies as high, medium, or low quality; results from high quality studies are reported. Because most high quality studies used the Siemens Enzygnost EIA kit, we generate individual and pooled diagnostic accuracy estimates for this assay separately. Median sensitivity of the Enzygnost EIA was 92.1% [IQR = 82.3, 95.7]; median specificity was 96.9 [93.0, 100.0]. Pooled sensitivity and specificity from studies using the Enzygnost kit were 91.6 (95%CI: 80.7,96.6) and 96.0 (95%CI: 90.9,98.3), respectively. The sensitivity of all other EIA kits across high quality studies ranged from 0% to 98.9% with median (IQR) = 90.6 [86.6, 95.2]; specificity ranged from 58.8% to 100.0% with median (IQR) = 100.0 [88.7, 100.0]. CONCLUSIONS: Evidence on the diagnostic accuracy of currently available measles IgG EIAs is variable, insufficient, and may not be fit for purpose for serosurveillance goals. Additional studies evaluating the diagnostic accuracy of measles EIAs, including MBAs, should be conducted among diverse populations and settings (e.g., vaccination status, elimination/endemic status, age groups).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".