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1.
Annals of Laboratory Medicine ; : 67-75, 2019.
Article in English | WPRIM | ID: wpr-719646

ABSTRACT

BACKGROUND: We examined changes in hepatitis B core-related antigen (HBcrAg) during the four sequential phases of chronic hepatitis B virus (HBV) infection: hepatitis B e antigen (HBeAg)-positive chronic infection (EPCI) and hepatitis (EPCH), followed by HBeAg-negative chronic infection (ENCI) and hepatitis (ENCH). We compared the performance of serum HBcrAg, hepatitis B surface antigen (HBsAg), and HBV DNA in predicting EPCH and ENCH. METHODS: We enrolled 492 consecutive patients: 49 with EPCI, 243 with EPCH, 101 with ENCI, and 99 with ENCH. HBcrAg was detected by chemiluminescent enzyme immunoassays. HBsAg and HBeAg were detected by chemiluminescent microparticle immunoassays. HBV DNA was detected by real-time PCR. Predictive performance of HBcrAg, HBsAg, and HBV DNA was evaluated using ROC curves. RESULTS: Areas under ROC curves (AUCs) of HBcrAg, HBsAg, and HBV DNA for predicting EPCH were 0.738, 0.812, and 0.717, respectively; optimal cutoffs were ≤1.43×105 kU/mL, ≤1.89×104 IU/mL, and ≤3.97×107 IU/mL, with sensitivities and specificities of 66.3% and 77.6%, 65.0% and 93.9%, and 60.5% and 79.6%, respectively. AUCs of HBcrAg, HBsAg, and HBV DNA for predicting ENCH were 0.887, 0.581, and 0.978, respectively; optimal cutoffs were >26.8 kU/mL, >2.29×102 IU/mL, and >8.75×103 IU/mL, with sensitivities and specificities of 72.7% and 95.1%, 86.9% and 39.6%, and 89.9% and 92.1%, respectively. CONCLUSIONS: HBsAg and HBV DNA were the best predictors of EPCH and ENCH, respectively. HBcrAg is an important surrogate marker for predicting EPCH and ENCH.


Subject(s)
Humans , Area Under Curve , Biomarkers , DNA , Hepatitis B e Antigens , Hepatitis B Surface Antigens , Hepatitis B virus , Hepatitis B , Hepatitis B, Chronic , Hepatitis , Hepatitis, Chronic , Immunoassay , Immunoenzyme Techniques , Real-Time Polymerase Chain Reaction , ROC Curve
2.
Chinese Journal of Epidemiology ; (12): 1141-1145, 2003.
Article in Chinese | WPRIM | ID: wpr-246384

ABSTRACT

<p><b>OBJECTIVE</b>To set a quantitative criteria for determining the risks on cerebral vascular disease (CVD) so to identify that potential risk of an individual dying from CVD and to predict the individual risk of CVD.</p><p><b>METHODS</b>Data on case-control and cohort studies published during 1978 to 2003 was collected through retrieval of literatures, and data on surveillance of behavior exposure was provided by Chengdu Municipal Center for Disease Control and Prevention. Pooled odds ratio (OR) and relative risk (RR) of all risk factors for CVD were estimated using software for meta-analysis to enable the varied levels of risk factors be converted into risk fractions by statistical models.</p><p><b>RESULTS</b>A risk score conversion table (quantitative criteria for assessment) of main risk factors for CVD was developed for men and women aged 35 - 69 at an interval of five years, including smoking, passive smoking, hypertension, high blood cholesterol levels, body mass index, lack of physical activity, alcohol drinking, dietary fat consumption, milk intake, oral contraceptive use, past history of diabetes and CVD, family history of CVD etc. Individuals with all these risk factors had a risk score beyond 1.00, but was equal to or below 1.00 when without. The risk score would increase along with the rise of one's risk level.</p><p><b>CONCLUSION</b>Estimation of risk of dying from CVD was based on risk score conversion table of risk factors for CVD, which could be used to predict individual potential risk of dying from CVD in the following 10 years. Our data provides evidence that education to be strengthened to persuade people to change their unhealthy lifestyles and behaviors.</p>


Subject(s)
Female , Humans , Male , Alcoholism , Body Constitution , Case-Control Studies , Cerebrovascular Disorders , Epidemiology , China , Epidemiology , Cohort Studies , Contraceptives, Oral, Hormonal , Diabetes Complications , Exercise , Feeding Behavior , Hypertension , Odds Ratio , Risk Assessment , Risk Factors , Smoking , Urban Population
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