Incidence and prediction of HBsAg seroclearance in a prospective multi‐ethnic HBeAg‐negative chronic hepatitis B cohort

Background and Aims Achieving HBsAg loss is an important landmark in the natural history of chronic hepatitis B (CHB). A more personalized approach to prediction of HBsAg loss is relevant in counseling patients. This study sought to develop and validate a prediction model for HBsAg loss based on qua...

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Veröffentlicht in:Hepatology (Baltimore, Md.) Md.), 2022-03, Vol.75 (3), p.709-723
Hauptverfasser: Terrault, Norah A., Wahed, Abdus S., Feld, Jordan J., Cooper, Stewart L., Ghany, Mark G., Lisker‐Melman, Mauricio, Perrillo, Robert, Sterling, Richard K., Khalili, Mandana, Chung, Raymond T., Rosenthal, Philip, Fontana, Robert J., Sarowar, Arif, Lau, Daryl T. Y., Wang, Junyao, Lok, Anna S., Janssen, Harry L. A.
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container_end_page 723
container_issue 3
container_start_page 709
container_title Hepatology (Baltimore, Md.)
container_volume 75
creator Terrault, Norah A.
Wahed, Abdus S.
Feld, Jordan J.
Cooper, Stewart L.
Ghany, Mark G.
Lisker‐Melman, Mauricio
Perrillo, Robert
Sterling, Richard K.
Khalili, Mandana
Chung, Raymond T.
Rosenthal, Philip
Fontana, Robert J.
Sarowar, Arif
Lau, Daryl T. Y.
Wang, Junyao
Lok, Anna S.
Janssen, Harry L. A.
description Background and Aims Achieving HBsAg loss is an important landmark in the natural history of chronic hepatitis B (CHB). A more personalized approach to prediction of HBsAg loss is relevant in counseling patients. This study sought to develop and validate a prediction model for HBsAg loss based on quantitative HBsAg levels (qHBsAg) and other baseline characteristics. Methods The Hepatitis B Research Network (HBRN) is a prospective cohort including 1240 untreated HBeAg‐negative patients (1150 adults, 90 children) with median follow‐up of 5.5 years. Incidence rates of HBsAg loss and hepatitis B surface antibody (anti‐HBs) acquisition were determined, and a predictor score of HBsAg loss using readily available variables was developed and externally validated. Results Crude incidence rates of HBsAg loss and anti‐HBs acquisition were 1.6 and 1.1 per 100 person‐years (PY); 67 achieved sustained HBsAg loss for an incidence rate of 1.2 per 100 PY. Increased HBsAg loss was significantly associated with older age, non‐Asian race, HBV phenotype (inactive CHB vs. others), HBV genotype A, lower HBV‐DNA levels, and lower and greater change in qHBsAg. The HBRN‐SQuARe (sex,∆quantHBsAg, age, race) score predicted HBsAg loss over time with area under the receiver operating characteristic curve (AUROC) (95% CIs) at 1 and 3 years of 0.99 (95% CI: 0.987–1.00) and 0.95 (95% CI 0.91–1.00), respectively. In validation in another cohort of 1253 HBeAg‐negative patients with median follow‐up of 3.1 years, HBRN SQuARe predicted HBsAg loss at 1 and 3 years with AUROC values of 0.99 (0.98–1.00) and 0.88 (0.77–0.99), respectively. Conclusion HBsAg loss in predominantly untreated patients with HBeAg‐negative CHB can be accurately predicted over a 3‐year horizon using a simple validated score (HBRN SQuARe). This prognostication tool can be used to support patient care and counseling.
doi_str_mv 10.1002/hep.32231
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Y. ; Wang, Junyao ; Lok, Anna S. ; Janssen, Harry L. A.</creator><creatorcontrib>Terrault, Norah A. ; Wahed, Abdus S. ; Feld, Jordan J. ; Cooper, Stewart L. ; Ghany, Mark G. ; Lisker‐Melman, Mauricio ; Perrillo, Robert ; Sterling, Richard K. ; Khalili, Mandana ; Chung, Raymond T. ; Rosenthal, Philip ; Fontana, Robert J. ; Sarowar, Arif ; Lau, Daryl T. Y. ; Wang, Junyao ; Lok, Anna S. ; Janssen, Harry L. A.</creatorcontrib><description>Background and Aims Achieving HBsAg loss is an important landmark in the natural history of chronic hepatitis B (CHB). A more personalized approach to prediction of HBsAg loss is relevant in counseling patients. This study sought to develop and validate a prediction model for HBsAg loss based on quantitative HBsAg levels (qHBsAg) and other baseline characteristics. Methods The Hepatitis B Research Network (HBRN) is a prospective cohort including 1240 untreated HBeAg‐negative patients (1150 adults, 90 children) with median follow‐up of 5.5 years. Incidence rates of HBsAg loss and hepatitis B surface antibody (anti‐HBs) acquisition were determined, and a predictor score of HBsAg loss using readily available variables was developed and externally validated. Results Crude incidence rates of HBsAg loss and anti‐HBs acquisition were 1.6 and 1.1 per 100 person‐years (PY); 67 achieved sustained HBsAg loss for an incidence rate of 1.2 per 100 PY. Increased HBsAg loss was significantly associated with older age, non‐Asian race, HBV phenotype (inactive CHB vs. others), HBV genotype A, lower HBV‐DNA levels, and lower and greater change in qHBsAg. The HBRN‐SQuARe (sex,∆quantHBsAg, age, race) score predicted HBsAg loss over time with area under the receiver operating characteristic curve (AUROC) (95% CIs) at 1 and 3 years of 0.99 (95% CI: 0.987–1.00) and 0.95 (95% CI 0.91–1.00), respectively. In validation in another cohort of 1253 HBeAg‐negative patients with median follow‐up of 3.1 years, HBRN SQuARe predicted HBsAg loss at 1 and 3 years with AUROC values of 0.99 (0.98–1.00) and 0.88 (0.77–0.99), respectively. Conclusion HBsAg loss in predominantly untreated patients with HBeAg‐negative CHB can be accurately predicted over a 3‐year horizon using a simple validated score (HBRN SQuARe). This prognostication tool can be used to support patient care and counseling.</description><identifier>ISSN: 0270-9139</identifier><identifier>EISSN: 1527-3350</identifier><identifier>DOI: 10.1002/hep.32231</identifier><identifier>PMID: 34743343</identifier><language>eng</language><publisher>United States: Wolters Kluwer Health, Inc</publisher><subject>Adult ; Age Factors ; Child ; Ethnicity - statistics &amp; numerical data ; Female ; Follow-Up Studies ; Genotypes ; Hepatitis B ; Hepatitis B Antibodies - analysis ; Hepatitis B Antibodies - blood ; Hepatitis B e antigen ; Hepatitis B surface antigen ; Hepatitis B Surface Antigens - analysis ; Hepatitis B Surface Antigens - blood ; Hepatitis B Surface Antigens - immunology ; Hepatitis B virus - genetics ; Hepatitis B, Chronic - diagnosis ; Hepatitis B, Chronic - immunology ; Hepatology ; Humans ; Incidence ; Interferon ; Male ; Phenotypes ; Prediction models ; Predictive Value of Tests ; Prognosis ; Serologic Tests - methods ; Serologic Tests - statistics &amp; numerical data ; Sustained Virologic Response</subject><ispartof>Hepatology (Baltimore, Md.), 2022-03, Vol.75 (3), p.709-723</ispartof><rights>2021 American Association for the Study of Liver Diseases.</rights><rights>2022 by the American Association for the Study of Liver Diseases.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3881-861f42f53e93ccb45ba03618cadef5c2f4f294ce179165a173f0254acdc040003</citedby><cites>FETCH-LOGICAL-c3881-861f42f53e93ccb45ba03618cadef5c2f4f294ce179165a173f0254acdc040003</cites><orcidid>0000-0002-8637-2475 ; 0000-0001-9178-9139 ; 0000-0003-4139-1987 ; 0000-0003-4143-1950</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fhep.32231$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fhep.32231$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34743343$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Terrault, Norah A.</creatorcontrib><creatorcontrib>Wahed, Abdus S.</creatorcontrib><creatorcontrib>Feld, Jordan J.</creatorcontrib><creatorcontrib>Cooper, Stewart L.</creatorcontrib><creatorcontrib>Ghany, Mark G.</creatorcontrib><creatorcontrib>Lisker‐Melman, Mauricio</creatorcontrib><creatorcontrib>Perrillo, Robert</creatorcontrib><creatorcontrib>Sterling, Richard K.</creatorcontrib><creatorcontrib>Khalili, Mandana</creatorcontrib><creatorcontrib>Chung, Raymond T.</creatorcontrib><creatorcontrib>Rosenthal, Philip</creatorcontrib><creatorcontrib>Fontana, Robert J.</creatorcontrib><creatorcontrib>Sarowar, Arif</creatorcontrib><creatorcontrib>Lau, Daryl T. Y.</creatorcontrib><creatorcontrib>Wang, Junyao</creatorcontrib><creatorcontrib>Lok, Anna S.</creatorcontrib><creatorcontrib>Janssen, Harry L. A.</creatorcontrib><title>Incidence and prediction of HBsAg seroclearance in a prospective multi‐ethnic HBeAg‐negative chronic hepatitis B cohort</title><title>Hepatology (Baltimore, Md.)</title><addtitle>Hepatology</addtitle><description>Background and Aims Achieving HBsAg loss is an important landmark in the natural history of chronic hepatitis B (CHB). A more personalized approach to prediction of HBsAg loss is relevant in counseling patients. This study sought to develop and validate a prediction model for HBsAg loss based on quantitative HBsAg levels (qHBsAg) and other baseline characteristics. Methods The Hepatitis B Research Network (HBRN) is a prospective cohort including 1240 untreated HBeAg‐negative patients (1150 adults, 90 children) with median follow‐up of 5.5 years. Incidence rates of HBsAg loss and hepatitis B surface antibody (anti‐HBs) acquisition were determined, and a predictor score of HBsAg loss using readily available variables was developed and externally validated. Results Crude incidence rates of HBsAg loss and anti‐HBs acquisition were 1.6 and 1.1 per 100 person‐years (PY); 67 achieved sustained HBsAg loss for an incidence rate of 1.2 per 100 PY. Increased HBsAg loss was significantly associated with older age, non‐Asian race, HBV phenotype (inactive CHB vs. others), HBV genotype A, lower HBV‐DNA levels, and lower and greater change in qHBsAg. The HBRN‐SQuARe (sex,∆quantHBsAg, age, race) score predicted HBsAg loss over time with area under the receiver operating characteristic curve (AUROC) (95% CIs) at 1 and 3 years of 0.99 (95% CI: 0.987–1.00) and 0.95 (95% CI 0.91–1.00), respectively. In validation in another cohort of 1253 HBeAg‐negative patients with median follow‐up of 3.1 years, HBRN SQuARe predicted HBsAg loss at 1 and 3 years with AUROC values of 0.99 (0.98–1.00) and 0.88 (0.77–0.99), respectively. Conclusion HBsAg loss in predominantly untreated patients with HBeAg‐negative CHB can be accurately predicted over a 3‐year horizon using a simple validated score (HBRN SQuARe). This prognostication tool can be used to support patient care and counseling.</description><subject>Adult</subject><subject>Age Factors</subject><subject>Child</subject><subject>Ethnicity - statistics &amp; numerical data</subject><subject>Female</subject><subject>Follow-Up Studies</subject><subject>Genotypes</subject><subject>Hepatitis B</subject><subject>Hepatitis B Antibodies - analysis</subject><subject>Hepatitis B Antibodies - blood</subject><subject>Hepatitis B e antigen</subject><subject>Hepatitis B surface antigen</subject><subject>Hepatitis B Surface Antigens - analysis</subject><subject>Hepatitis B Surface Antigens - blood</subject><subject>Hepatitis B Surface Antigens - immunology</subject><subject>Hepatitis B virus - genetics</subject><subject>Hepatitis B, Chronic - diagnosis</subject><subject>Hepatitis B, Chronic - immunology</subject><subject>Hepatology</subject><subject>Humans</subject><subject>Incidence</subject><subject>Interferon</subject><subject>Male</subject><subject>Phenotypes</subject><subject>Prediction models</subject><subject>Predictive Value of Tests</subject><subject>Prognosis</subject><subject>Serologic Tests - methods</subject><subject>Serologic Tests - statistics &amp; numerical data</subject><subject>Sustained Virologic Response</subject><issn>0270-9139</issn><issn>1527-3350</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kc9OGzEQxi3UqqTQAy-ALHGhhwX_ze4eA6INElI5wNlyvOPEaGMHe7cV4tJH6DP2STohtAeknqzx_ObTN_MRcsTZGWdMnK9gcyaFkHyPTLgWdSWlZu_IhImaVS2X7T75WMoDY6xVovlA9qWqlZRKTsjzdXShg-iA2tjRTYYuuCGkSJOn84syW9ICObkebLZbKkRqEUtlA8h9B7oe-yH8_vkLhlUMDmdgtsQywtK-9N0qp20DTeLHEAq9oC6tUh4OyXtv-wKfXt8Dcv_l6u5yXt18-3p9ObupnGwaXjVT7pXwWkIrnVsovbBMTnnjbAdeO-GVF61ywOuWT7XltfRMaGVd55jCneUBOd3pou3HEcpg1qE46HsbIY3FCN1qznFcIXryBn1IY47ozoipaEQr8LxIfd5RDu9QMnizyWFt85PhzGwTMbiseUkE2eNXxXGxhu4f-TcCBM53wI_Qw9P_lcz86nYn-QdvIJbX</recordid><startdate>202203</startdate><enddate>202203</enddate><creator>Terrault, Norah A.</creator><creator>Wahed, Abdus S.</creator><creator>Feld, Jordan J.</creator><creator>Cooper, Stewart L.</creator><creator>Ghany, Mark G.</creator><creator>Lisker‐Melman, Mauricio</creator><creator>Perrillo, Robert</creator><creator>Sterling, Richard K.</creator><creator>Khalili, Mandana</creator><creator>Chung, Raymond T.</creator><creator>Rosenthal, Philip</creator><creator>Fontana, Robert J.</creator><creator>Sarowar, Arif</creator><creator>Lau, Daryl T. 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A.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Immunology Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><jtitle>Hepatology (Baltimore, Md.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Terrault, Norah A.</au><au>Wahed, Abdus S.</au><au>Feld, Jordan J.</au><au>Cooper, Stewart L.</au><au>Ghany, Mark G.</au><au>Lisker‐Melman, Mauricio</au><au>Perrillo, Robert</au><au>Sterling, Richard K.</au><au>Khalili, Mandana</au><au>Chung, Raymond T.</au><au>Rosenthal, Philip</au><au>Fontana, Robert J.</au><au>Sarowar, Arif</au><au>Lau, Daryl T. Y.</au><au>Wang, Junyao</au><au>Lok, Anna S.</au><au>Janssen, Harry L. A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Incidence and prediction of HBsAg seroclearance in a prospective multi‐ethnic HBeAg‐negative chronic hepatitis B cohort</atitle><jtitle>Hepatology (Baltimore, Md.)</jtitle><addtitle>Hepatology</addtitle><date>2022-03</date><risdate>2022</risdate><volume>75</volume><issue>3</issue><spage>709</spage><epage>723</epage><pages>709-723</pages><issn>0270-9139</issn><eissn>1527-3350</eissn><abstract>Background and Aims Achieving HBsAg loss is an important landmark in the natural history of chronic hepatitis B (CHB). A more personalized approach to prediction of HBsAg loss is relevant in counseling patients. This study sought to develop and validate a prediction model for HBsAg loss based on quantitative HBsAg levels (qHBsAg) and other baseline characteristics. Methods The Hepatitis B Research Network (HBRN) is a prospective cohort including 1240 untreated HBeAg‐negative patients (1150 adults, 90 children) with median follow‐up of 5.5 years. Incidence rates of HBsAg loss and hepatitis B surface antibody (anti‐HBs) acquisition were determined, and a predictor score of HBsAg loss using readily available variables was developed and externally validated. Results Crude incidence rates of HBsAg loss and anti‐HBs acquisition were 1.6 and 1.1 per 100 person‐years (PY); 67 achieved sustained HBsAg loss for an incidence rate of 1.2 per 100 PY. Increased HBsAg loss was significantly associated with older age, non‐Asian race, HBV phenotype (inactive CHB vs. others), HBV genotype A, lower HBV‐DNA levels, and lower and greater change in qHBsAg. The HBRN‐SQuARe (sex,∆quantHBsAg, age, race) score predicted HBsAg loss over time with area under the receiver operating characteristic curve (AUROC) (95% CIs) at 1 and 3 years of 0.99 (95% CI: 0.987–1.00) and 0.95 (95% CI 0.91–1.00), respectively. In validation in another cohort of 1253 HBeAg‐negative patients with median follow‐up of 3.1 years, HBRN SQuARe predicted HBsAg loss at 1 and 3 years with AUROC values of 0.99 (0.98–1.00) and 0.88 (0.77–0.99), respectively. Conclusion HBsAg loss in predominantly untreated patients with HBeAg‐negative CHB can be accurately predicted over a 3‐year horizon using a simple validated score (HBRN SQuARe). This prognostication tool can be used to support patient care and counseling.</abstract><cop>United States</cop><pub>Wolters Kluwer Health, Inc</pub><pmid>34743343</pmid><doi>10.1002/hep.32231</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0002-8637-2475</orcidid><orcidid>https://orcid.org/0000-0001-9178-9139</orcidid><orcidid>https://orcid.org/0000-0003-4139-1987</orcidid><orcidid>https://orcid.org/0000-0003-4143-1950</orcidid><oa>free_for_read</oa></addata></record>
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subjects Adult
Age Factors
Child
Ethnicity - statistics & numerical data
Female
Follow-Up Studies
Genotypes
Hepatitis B
Hepatitis B Antibodies - analysis
Hepatitis B Antibodies - blood
Hepatitis B e antigen
Hepatitis B surface antigen
Hepatitis B Surface Antigens - analysis
Hepatitis B Surface Antigens - blood
Hepatitis B Surface Antigens - immunology
Hepatitis B virus - genetics
Hepatitis B, Chronic - diagnosis
Hepatitis B, Chronic - immunology
Hepatology
Humans
Incidence
Interferon
Male
Phenotypes
Prediction models
Predictive Value of Tests
Prognosis
Serologic Tests - methods
Serologic Tests - statistics & numerical data
Sustained Virologic Response
title Incidence and prediction of HBsAg seroclearance in a prospective multi‐ethnic HBeAg‐negative chronic hepatitis B cohort
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