- Email: [email protected]
[474] FACTORS ASSOCIATED WITH SEROCLEARANCE OF HEPATITIS B e ANTIGEN: A LONG-TERM FOLLOW-UP STUDY
POSTERS
S180
ing marker of blood donations (in-house real time PCR, sensitivity 528 TUimL). HBV genotype was assessed by DNA sequencing. Results: During the first part ofthe study, 15545 donations were included. Six of them (0.04%) were HBsAg positive in the routine screening and were excluded from further analysis. For the remaining 15539 donations, 651 (4.2%) were anti-HBc positive, most of them (606/651; 93%) with detectable levels of anti-HBs. HBVDNA could be analyzed in 618 antiHBc positive donations and six of them were positive in the limit of sensitivity of our PCR technique, accounting for 0.97% of anti-HBc positive donors. All six donations were positive for anti-HBs, with antibody levels ranging from 5 to more than 1000 mUTimL. One immune-competent and one immune-suppressed recipients of OBI blood components could be followed up and both tested negative for HBsAg and anti-HBc. In the second part of the study and after HBV DNA screening was implemented in routine, we identified 11 HBV DNA positive HBsAg negative BD out of 223576 donations (li20000 aprox.). All were anti-HBc positive and, except one, also anti-HBs positive. HBV genotype could be assessed in 8 donors (2 HBV-A; 6 HBV-D). Conclusions: Current prevalence of exposure to HBV (anti-HBc) among our blood donors is 4.2%. Occult HBV infection is frequent, but infectivity of OBI blood components is still uncertain.
14741 FACTORS ASSOCIATED WITH SEROCLEARANCE OF HEPATITIS B e ANTIGEN: A LONG-TERM FOLLOW-UP STUDY C.A. Chen’, P.J. Chen’, H.1. Yang’,’, U.H. Iloeje3 J. Su3, C.L. Jen’,’, S.H. Yeh’, S.N. Lu4, S.L.. YOU',^, C.J. Chen’,2. ’National Taiwan lJniwrsity, Taipei; ’Genomics Research Centev, Acadenzia Sinica, Taipei, Taiwan; 3Bristol-Mj~ersSquihh Pharmaceutical Research Institute, Wallingfbrd, C% USA; Kaohsinng Chang-Gnng Memorial Hospital, Kaohsinng, Taiwan E-mail: r948420 [email protected] Background and Aims: The seroclearance of hepatitis B e antigen (HBeAg) is usually associated with low HBV replication and slow disease progression. It is a favorable sign for patients with chronic hepatitis B. However, the mechanism of HBeAg seroclearance remains incompletely clear. The aim of this long-term follow-up study was to examine factors associated with HBeAg seroclearance. Methods: There were 440 HBeAg-seropositive and anti-HCV-seronegative men and women enrolled from seven townships in Taiwan between 1991 and 1992 in this analysis. Their serum samples at cohort entry were tested for HBeAg, ALT, HBVDNA level and genotype. The HBeAg status in last follow-up samples was also tested. Logistic regression analysis was used to derive multivariate-adjusted odds ratio (OR) and 95% confidence interval (CI) for factors associated with HBeAg seroclearance. Results: Follow-up period, HBV genotype and serum ALT and HBV DNA levels at study entry were significantly associated with HBeAg seroclearance. The multivariate-adjusted OR (95% CT) of HBeAg seroclearance was 5.42 (2.41-12.19) and 10.57 (4.57-22.50), respectively, for follow-up periods of 5-9 years and 2 1 0 years versus 1 5 years; 2.21 (1.12-4.33) for serum ALT level at study entry 2 4 5 TU versus <45 TU; 0.26 (0.14-0.47) for HBV genotype C versus genotype B; and 0.18 (0.05-0.61) for serum HBV DNA level at study entry 2107 versus
14751 A RISK FUNCTION NOMOGRAM FOR PREDICTING HCC IN PATIENTS WITH CHRONIC HEPATITIS B: THE REVEAL.-HBV STUDY S.L. You’, C.J. Chen’,2, H.T. Yang’,2, U.H. Tloeje3, J. Su3, C.L. M. Sherman4, Y.F. Laiw’, P.J. Chen2. ’Genonzics Research Center, Academia Sinica, Taipei; ’National Tui~lanUniwrsity, Taipei, 0.C.; Bristol-Myers Squihb Pharnzaceutical Research Institute, Tai~lan-R. Wallingfbrd,C% USA; University of‘ Toronto, Toronto, ON, Canada; Chang Gung Menzorial Hospital And University, Taipei, Tai~lan-R.O.C. E-mail: [email protected]
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Background: Counseling CHB patients of their individual risk of progressing to liver complications is a clinical challenge. Our objective was to develop a simple risk function nomogram using non-invasive clinical information in CHB infected subjects. Methods: Variables with a priori plausibility as risk factors were used (Gender, age, cigarette smoking, alcohol consumption, family history of HCC, ALT, HBeAg, HBVDNA, HBV genotype, BCP and precore mutations). Cox proportional hazards models were used to train models. Regression coetficients derived from the Cox models were converted into integer risk scores and the predicted risks of HCC over 5 and 10 years calculated for various risk scores. The risk scores and the predicted 5 and 10-year HCC risks were translated into normograms. The predictive accuracy was evaluated using Receiver Operator Characteristic (ROC) curve and area under the ROC curve (AUROC); and the calibration chart. Results: 3644 subjects were included. The mean follow-up time was 11 years. Of eight different computer generated models, the best model had an AUROC of 0.8601 (5yr HCC prediction) and 0.8649 (10yr HCC prediction). Males were at higher risk of HCC development than females. For all HBV DNA levels, genotype C patients had a higher risk of HCC than genotype B patients. The resulting nomogram derived from the model had good calibration ability and the predicted risk approximated the actual risk. Multiple Cox proportional hazards model for gender, age, alcohol conwmption, ALT, HBeAg, and the combinations of HBV DNA and Genotype (Model 5 )
Male gender (referent: female) Age (I-yr increment) Alcohol consumption yes (referent: no) ALT 2 45 U/L (referent: <45) HBeAg(+) (referent: -) HBV DNA/genotype (referent: <100/not tested) loo-< 1 0 4 1 ~ loo-< 104/c 1051~ 1051~ >IO’/B 2I 0 5 1 ~ Family history of HCC yes (referent: no)
(I
HR 95%CI
P value
1.13734 0.09078 0.54473 0.55669 0.96885
3.1 1.10 1.7 1.7 2.6
2.0-4.8 1.08-1.12 1.2-2.5 1.1-2.7 1.7-4.1
<0.0001 <0.0001 0.0040 0.0104 <0.0001
0.80015 1.34494 1.10636 2.15516 1.95725 2.39034 0.76773
2.2 3.8 3.0 8.6 7.1 10.9 2.2
0.9-5.3 1.6-9.3 1.3-6.9 3.6-20.9 3.4-14.8 5.0-24.1 1.2-3.8
0.0700 0.0028 0.0088 <0.0001 <0.0001 <0.0001 0.0067
Conclusions: The predictive model has good characteristics as shown by the AUROC The combination of HBVDNA 210,000 copiesimL and genotype C had the highest HCC nsk The denved nomogram, once validated, should simplify the communication of individual HCC nsk using non-invasive variables.
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ing marker of blood donations (in-house real time PCR, sensitivity 528 TUimL). HBV genotype was assessed by DNA sequencing. Results: During the first part ofthe study, 15545 donations were included. Six of them (0.04%) were HBsAg positive in the routine screening and were excluded from further analysis. For the remaining 15539 donations, 651 (4.2%) were anti-HBc positive, most of them (606/651; 93%) with detectable levels of anti-HBs. HBVDNA could be analyzed in 618 antiHBc positive donations and six of them were positive in the limit of sensitivity of our PCR technique, accounting for 0.97% of anti-HBc positive donors. All six donations were positive for anti-HBs, with antibody levels ranging from 5 to more than 1000 mUTimL. One immune-competent and one immune-suppressed recipients of OBI blood components could be followed up and both tested negative for HBsAg and anti-HBc. In the second part of the study and after HBV DNA screening was implemented in routine, we identified 11 HBV DNA positive HBsAg negative BD out of 223576 donations (li20000 aprox.). All were anti-HBc positive and, except one, also anti-HBs positive. HBV genotype could be assessed in 8 donors (2 HBV-A; 6 HBV-D). Conclusions: Current prevalence of exposure to HBV (anti-HBc) among our blood donors is 4.2%. Occult HBV infection is frequent, but infectivity of OBI blood components is still uncertain.
14741 FACTORS ASSOCIATED WITH SEROCLEARANCE OF HEPATITIS B e ANTIGEN: A LONG-TERM FOLLOW-UP STUDY C.A. Chen’, P.J. Chen’, H.1. Yang’,’, U.H. Iloeje3 J. Su3, C.L. Jen’,’, S.H. Yeh’, S.N. Lu4, S.L.. YOU',^, C.J. Chen’,2. ’National Taiwan lJniwrsity, Taipei; ’Genomics Research Centev, Acadenzia Sinica, Taipei, Taiwan; 3Bristol-Mj~ersSquihh Pharmaceutical Research Institute, Wallingfbrd, C% USA; Kaohsinng Chang-Gnng Memorial Hospital, Kaohsinng, Taiwan E-mail: r948420 [email protected] Background and Aims: The seroclearance of hepatitis B e antigen (HBeAg) is usually associated with low HBV replication and slow disease progression. It is a favorable sign for patients with chronic hepatitis B. However, the mechanism of HBeAg seroclearance remains incompletely clear. The aim of this long-term follow-up study was to examine factors associated with HBeAg seroclearance. Methods: There were 440 HBeAg-seropositive and anti-HCV-seronegative men and women enrolled from seven townships in Taiwan between 1991 and 1992 in this analysis. Their serum samples at cohort entry were tested for HBeAg, ALT, HBVDNA level and genotype. The HBeAg status in last follow-up samples was also tested. Logistic regression analysis was used to derive multivariate-adjusted odds ratio (OR) and 95% confidence interval (CI) for factors associated with HBeAg seroclearance. Results: Follow-up period, HBV genotype and serum ALT and HBV DNA levels at study entry were significantly associated with HBeAg seroclearance. The multivariate-adjusted OR (95% CT) of HBeAg seroclearance was 5.42 (2.41-12.19) and 10.57 (4.57-22.50), respectively, for follow-up periods of 5-9 years and 2 1 0 years versus 1 5 years; 2.21 (1.12-4.33) for serum ALT level at study entry 2 4 5 TU versus <45 TU; 0.26 (0.14-0.47) for HBV genotype C versus genotype B; and 0.18 (0.05-0.61) for serum HBV DNA level at study entry 2107 versus
14751 A RISK FUNCTION NOMOGRAM FOR PREDICTING HCC IN PATIENTS WITH CHRONIC HEPATITIS B: THE REVEAL.-HBV STUDY S.L. You’, C.J. Chen’,2, H.T. Yang’,2, U.H. Tloeje3, J. Su3, C.L. M. Sherman4, Y.F. Laiw’, P.J. Chen2. ’Genonzics Research Center, Academia Sinica, Taipei; ’National Tui~lanUniwrsity, Taipei, 0.C.; Bristol-Myers Squihb Pharnzaceutical Research Institute, Tai~lan-R. Wallingfbrd,C% USA; University of‘ Toronto, Toronto, ON, Canada; Chang Gung Menzorial Hospital And University, Taipei, Tai~lan-R.O.C. E-mail: [email protected]
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Background: Counseling CHB patients of their individual risk of progressing to liver complications is a clinical challenge. Our objective was to develop a simple risk function nomogram using non-invasive clinical information in CHB infected subjects. Methods: Variables with a priori plausibility as risk factors were used (Gender, age, cigarette smoking, alcohol consumption, family history of HCC, ALT, HBeAg, HBVDNA, HBV genotype, BCP and precore mutations). Cox proportional hazards models were used to train models. Regression coetficients derived from the Cox models were converted into integer risk scores and the predicted risks of HCC over 5 and 10 years calculated for various risk scores. The risk scores and the predicted 5 and 10-year HCC risks were translated into normograms. The predictive accuracy was evaluated using Receiver Operator Characteristic (ROC) curve and area under the ROC curve (AUROC); and the calibration chart. Results: 3644 subjects were included. The mean follow-up time was 11 years. Of eight different computer generated models, the best model had an AUROC of 0.8601 (5yr HCC prediction) and 0.8649 (10yr HCC prediction). Males were at higher risk of HCC development than females. For all HBV DNA levels, genotype C patients had a higher risk of HCC than genotype B patients. The resulting nomogram derived from the model had good calibration ability and the predicted risk approximated the actual risk. Multiple Cox proportional hazards model for gender, age, alcohol conwmption, ALT, HBeAg, and the combinations of HBV DNA and Genotype (Model 5 )
Male gender (referent: female) Age (I-yr increment) Alcohol consumption yes (referent: no) ALT 2 45 U/L (referent: <45) HBeAg(+) (referent: -) HBV DNA/genotype (referent: <100/not tested) loo-< 1 0 4 1 ~ loo-< 104/c 1051~ 1051~ >IO’/B 2I 0 5 1 ~ Family history of HCC yes (referent: no)
(I
HR 95%CI
P value
1.13734 0.09078 0.54473 0.55669 0.96885
3.1 1.10 1.7 1.7 2.6
2.0-4.8 1.08-1.12 1.2-2.5 1.1-2.7 1.7-4.1
<0.0001 <0.0001 0.0040 0.0104 <0.0001
0.80015 1.34494 1.10636 2.15516 1.95725 2.39034 0.76773
2.2 3.8 3.0 8.6 7.1 10.9 2.2
0.9-5.3 1.6-9.3 1.3-6.9 3.6-20.9 3.4-14.8 5.0-24.1 1.2-3.8
0.0700 0.0028 0.0088 <0.0001 <0.0001 <0.0001 0.0067
Conclusions: The predictive model has good characteristics as shown by the AUROC The combination of HBVDNA 210,000 copiesimL and genotype C had the highest HCC nsk The denved nomogram, once validated, should simplify the communication of individual HCC nsk using non-invasive variables.