Serum specimens (327) from patients with chronic hepatitis B were evaluated for hepatitis B virus (HBV) DNA using three commercial assays--Chiron Quantiplex (CA), Digene Hybrid Capture (DA) and Abbott HBV DNA assay (AA). The HBV DNA values obtained following evaluation were used to compare the linearity, responsiveness and precision of each assay and to determine the conversion between the three different assay values. The comparison was accomplished using a new statistical approach termed the multi-measurement method (MMM). MMM is a minimal bias, non-linear regression technique that allows simultaneous multiassay performance evaluation as well as assay value interconversion. MMM analysis demonstrated that the CA was more sensitive and responsive than either the DA or the AA. Both the CA and DA were more precise than the AA. Validation of the MMM results was performed using two additional data sets of 551 and 100 specimens, respectively. MMM is a novel statistical tool that has a broad application for the generation of statistically normalized laboratory data and for interassay standardization.

Therapy with interferon-alpha has been reported to induce remissions in 35% of patients with chronic hepatitis B. The ability to identify patients likely to respond would be helpful in making recommendations for treatment. In this statistical analysis we included 82 patients with chronic hepatitis B who received interferon-alpha in clinical trials at the National Institutes of Health between 1984 and 1991. A response was defined as the loss of hepatitis B virus (HBV) DNA and hepatitis B e antigen (HBeAg) within 1 year of therapy. Multiple clinical parameters measured at pretreatment (month 0) and after the first month (month 1) of therapy were selected by stepwise regression to support the development of the prognostic models: the two-stage logistic regression model and a neural network that utilized higher-order non-linear interactions between variables. Among the 82 patients, 24 (29%) were responders. The two-stage logistic model using pretreatment variables: sex, hepatic fibrosis and alanine aminotransferase (ALT) levels correctly identified 61% of responders and 76% of non-responders. When HBV DNA at month 1 along with sex, initial ALT and fibrosis was included, the resultant model correctly identified 69% of responders and 77% of non-responders. The neural network, by incorporating interactions between variables, correctly identified 77% and 86% of responders, and 87% and 92% of non-responders, using pretreatment factors alone and the combination of pretreatment and month 1 factors respectively. Hence, the neural network was more accurate than the simple logistic regression model in predicting a response to interferon-alpha in chronic hepatitis B. The universality of these models needs to be further verified.

The aim of this study was to evaluate the Chiron branched DNA (bDNA) assay for detection of serum hepatitis B virus (HBV) DNA in patients with chronic hepatitis B lacking hepatitis B e antigen (HBeAg) and undergoing interferon (IFN) therapy. Results obtained with the bDNA assay were compared with those obtained using the Abbott liquid hybridization (LH) assay and the polymerase chain reaction (PCR). Serial samples (274) from 34 patients were analysed. Analysis of variance results indicated that bDNA values were more significantly correlated than LH values with both PCR positive/negative results (probability of artifact (Prob > F) = 0.7 and 0.09 for LH and bDNA assays, respectively) and presence/absence of precore mutations (Prob > F = 0.21 and 0.001 for LH and bDNA assays, respectively). Both bDNA and LH results correlated highly with alanine aminotransferase (ALT) values (both had Prob > F values of 0.0) while PCR was not correlated with ALT (Prob > F = 0.05). In 26 evaluable patients, a model based on a generalized Knodell score was used to predict response to IFN therapy, as defined by normalization of ALT values during therapy. This model discriminated well between non-responders and responders. The bDNA results correlated well with the generalized Knodell score, while the LH results did not (Prob > F = 0.04 and 0.19 for the bDNA and LH assays, respectively). In conclusion, the bDNA assay appears to be useful for quantification of HBV DNA levels in HBeAg-negative chronic hepatitis as it correlates with biochemical and histological indications of disease severity as well as with response to IFN therapy.

To develop prognostic models for identifying children with hepatitis B who are likely to respond to interferon-alpha (IFN-alpha) or to spontaneously seroconvert, we evaluated results of a multinational controlled trial comprising 70 children with chronic hepatitis B who received IFN-alpha and 74 children who did not receive therapy. Prognostic models were developed using SMILES (similarity of least squares), which is a data analysis network that incorporates multidimensional relationships in the clinical data of complex diseases. Commonly collected clinical data included age, gender, serum aminotransferase (aspartate aminotransferase [AST] and alanine aminotransferase [ALT]) and hepatitis B virus (HBV) DNA levels, and IFN-alpha dose. Additional data included pretreatment directional information (e.g. increases or decreases in serum aminotransferase and HBV DNA levels), liver biopsy results, race and transmission mode. Using data available prior to initiation of treatment, the SMILES models achieved prospective predictions of 89% for responders, 96% for non-responders, 100% for seroconverters and 93% for non-seroconverters. Although not predictive by themselves, the variables that had the greatest impact on predictions for IFN-alpha response were HBV DNA pretreatment direction, baseline HBV DNA, IFN-alpha dose and gender. The variables that had the greatest impact on predictions for spontaneous seroconversion were ALT pretreatment direction, baseline HBV DNA level, age and AST pretreatment direction. Therefore, these models may be useful in determining, in children with hepatitis B, the likelihood of response to IFN-alpha and spontaneous seroconversion.

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