Hepatitis B Core-Related Antigen to Indicate High Viral Load: Systematic Review and Meta-Analysis of 10,397 Individual Participants
Bibliographic record
Abstract
BACKGROUND & AIMS: To eliminate hepatitis B virus (HBV) infection, scale-up of testing and treatment in resource-limited countries is crucial. However, access to nucleic acid testing to quantify HBV DNA, an essential test to examine treatment eligibility, remains severely limited. We assessed the performance of a novel immunoassay, HBV core-related antigen (HBcrAg), as a low-cost (less than US $15/assay) alternative to nucleic acid testing to indicate clinically important high viremia in chronic HBV patients infected with different genotypes. METHODS: We searched Medline, Embase, Scopus, and Web of Science databases through June 27, 2018. Three reviewers independently selected studies measuring HBV DNA and HBcrAg in the same blood samples. We contacted authors to provide individual participant data (IPD). We randomly allocated each IPD to a derivation or validation cohort. We applied optimal HBcrAg cut-off values derived from the derivation set to the validation set to estimate sensitivity/specificity. RESULTS: Of 74 eligible studies, IPD were obtained successfully for 60 studies (81%). Meta-analysis included 5591 IPD without antiviral therapy and 4806 treated with antivirals. In untreated patients, the pooled area under the receiver operating characteristic curve and optimal cut-off values were as follows: 0.88 (95% CI, 0.83-0.94) and 3.6 log U/mL to diagnose HBV DNA level of 2000 IU/mL or greater; and 0.96 (95% CI, 0.94-0.98) and 5.3 log U/mL for 200,000 IU/mL or greater, respectively. In the validation set, the sensitivity and specificity were 85.2% and 84.7% to diagnose HBV DNA level of 2000 IU/mL or greater, and 91.8% and 90.5% for 200,000 IU/mL or greater, respectively. The performance did not vary by HBV genotypes. In patients treated with anti-HBV therapy the correlation between HBcrAg and HBV DNA was poor. CONCLUSIONS: HBcrAg might be a useful serologic marker to indicate clinically important high viremia in treatment-naïve, HBV-infected patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.027 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".