Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Background: Hepatitis B core-related antigen (HBcrAg), a novel serum biomarker reflecting the activity of intrahepatic covalently closed circular DNA (cccDNA), has generated conflicting evidence regarding its clinical utility for predicting post-antiviral therapy relapse in chronic hepatitis B (CHB) patients.
Methods: We systematically analyzed 13 studies (15 cohorts, = 1529 patients) from PubMed, Web of Science, Wanfang, and CNKI (through April 2025). A bivariate model evaluated HBcrAg's predictive performance for relapse outcomes, including virological relapse, clinical relapse, and hepatitis flares.
Results: HBcrAg demonstrated a pooled sensitivity of 0.81 (95% CI: 0.75-0.86) and specificity of 0.72 (95% CI: 0.67-0.76) for relapse prediction, with a diagnostic odds ratio of 10.66 (95% CI: 7.36-15.42) and summary AUC of 0.83 (95% CI: 0.80-0.86). Subgroup analysis identified threshold effects as the primary source of heterogeneity, which resolved (I < 13%) after excluding studies with outlier cutoff values. Meta-regression established that HBcrAg's predictive value was unaffected by age, sex, hepatitis B e antigen status, or detection methods ( > 0.05).
Conclusions: HBcrAg is validated as a robust non-invasive biomarker to optimize treatment cessation strategies, with high sensitivity providing strong negative predictive value in CHB populations. Future research should prioritize multi-marker models to enhance prediction accuracy.
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Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12299212 | PMC |
http://dx.doi.org/10.3390/v17070929 | DOI Listing |