Pilot Study Using Machine Learning to Identify Immune Profiles for the Prediction of Early Virological Relapse After Stopping Nucleos(t)ide Analogues in HBeAg-Negative CHB.
Cast your vote
You can rate an item by clicking the amount of stars they wish to award to this item.
When enough users have cast their vote on this item, the average rating will also be shown.
Your vote was cast
Thank you for your feedback
Thank you for your feedback
Lopez Alfonso, Juan Carlos
Kraft, Anke R M
Meyer Hermann, Michael
Höner Zu Siederdissen, Christoph
MetadataShow full item record
AbstractTreatment with nucleos(t)ide analogues (NAs) may be stopped after 1-3 years of hepatitis B virus DNA suppression in hepatitis B e antigen (HBeAg)-negative patients according to Asian Pacific Association for the Study of Liver and European Association for the Study of Liver guidelines. However, virological relapse (VR) occurs in most patients. We aimed to analyze soluble immune markers (SIMs) and use machine learning to identify SIM combinations as predictor for early VR after NA discontinuation. A validation cohort was used to verify the predictive power of the SIM combination. In a post hoc analysis of a prospective, multicenter therapeutic vaccination trial (ABX-203, NCT02249988), hepatitis B surface antigen, hepatitis B core antigen, and 47 SIMs were repeatedly determined before NA was stopped. Forty-three HBeAg-negative patients were included. To detect the highest predictive constellation of host and viral markers, a supervised machine learning approach was used. Data were validated in a different cohort of 49 patients treated with entecavir. VR (hepatitis B virus DNA ≥ 2,000 IU/mL) occurred in 27 patients. The predictive value for VR of single SIMs at the time of NA stop was best for interleukin (IL)-2, IL-17, and regulated on activation, normal T cell expressed and secreted (RANTES/CCL5) with a maximum area under the curve of 0.65. Hepatitis B core antigen had a higher predictive power than hepatitis B surface antigen but lower than the SIMs. A supervised machine-learning algorithm allowed a remarkable improvement of early relapse prediction in patients treated with entecavir. The combination of IL-2, monokine induced by interferon γ (MIG)/chemokine (C-C motif) ligand 9 (CCL9), RANTES/CCL5, stem cell factor (SCF), and TNF-related apoptosis-inducing ligand (TRAIL) was reliable in predicting VR (0.89; 95% confidence interval: 0.5-1.0) and showed viable results in the validation cohort (0.63; 0.1-0.99). Host immune markers such as SIMs appear to be underestimated in guiding treatment cessation in HBeAg-negative patients. Machine learning can help find predictive SIM patterns that allow a precise identification of patients particularly suitable for NA cessation.
CitationHepatol Commun. 2020 Nov 5;5(1):97-111. doi: 10.1002/hep4.1626. PMID: 33437904.
AffiliationCiiM, Zentrum für individualisierte Infektionsmedizin, Feodor-Lynen-Str.7, 30625 Hannover.
The following license files are associated with this item:
- Creative Commons
- Hepatitis B virus-specific T cell responses after stopping nucleos(t)ide analogue therapy in HBeAg-negative chronic hepatitis B.
- Authors: Rinker F, Zimmer CL, Höner Zu Siederdissen C, Manns MP, Kraft ARM, Wedemeyer H, Björkström NK, Cornberg M
- Issue date: 2018 Sep
- Limited sustained response after stopping nucleos(t)ide analogues in patients with chronic hepatitis B: results from a randomised controlled trial (Toronto STOP study).
- Authors: Liem KS, Fung S, Wong DK, Yim C, Noureldin S, Chen J, Feld JJ, Hansen BE, Janssen HLA
- Issue date: 2019 Dec
- Improving the prediction of relapse after nucleos(t)ide analogue discontinuation in patients with chronic hepatitis B.
- Authors: Song DS, Jang JW, Yoo SH, Kwon JH, Nam SW, Bae SH, Choi JY, Yoon SK
- Issue date: 2021 Jan 8
- Clinical outcomes and predictors for relapse after cessation of oral antiviral treatment in chronic hepatitis B patients.
- Authors: Jung KS, Park JY, Chon YE, Kim HS, Kang W, Kim BK, Kim SU, Kim do Y, Han KH, Ahn SH
- Issue date: 2016 Aug
- Hepatitis B surface antigen quantification at hepatitis B e antigen seroconversion predicts virological relapse after the cessation of entecavir treatment in hepatitis B e antigen-positive patients.
- Authors: Qiu YW, Huang LH, Yang WL, Wang Z, Zhang B, Li YG, Su TT, Zhou HY, Xu W, Wang XD, Dai YP, Gan JH
- Issue date: 2016 Feb