Effect of Alpha-Interferon Treatment in Patients with Hepatitis B e Antigen-Positive Chronic Hepatitis B

Hepatitis B is a common disease with an estimated prevalence of more than 300 million chronic carriers worldwide [1]. The relative risk for hepatocellular carcinoma is 98 for chronic carriers in Asia, where the disease is endemic [2]. The risk in nonendemic areas is less clearly defined [3, 4]. Only a small proportion of hepatitis B virus (HBV) carriers develop chronic active hepatitis, cirrhosis, or hepatocellular carcinoma [5]. Of adult carriers, 40% to 70% have evidence of active viral replication [6-9], and this group is at the highest risk for developing progressive liver disease [10-15]. Of these carriers, 15% to 20% develop cirrhosis within 5 years [16, 17]. Those with cirrhosis and chronic active hepatitis on liver biopsy have a 5-year survival rate of 55% [18]. It seems logical that the termination of viral replication should decrease the risk for developing progressive liver disease. In the past 15 years, investigators have therefore targeted for treatment the subgroup of patients with chronic HBV infection with ongoing viral replication, as indicated by the presence of hepatitis B e antigen (HBeAg) and HBV DNA in serum Figure 1 [19]. Many antiviral and immunomodulatory drugs have been tried without proven efficacy. Alpha-interferons in particular have been studied extensively. The preparations of -interferon used were either lymphoblastoid, leukocyte, or recombinant (recombinant -interferon 2a, 2b, and 2c). Early studies showed that a thrice-weekly schedule produced a response similar to that seen with daily dosing but caused fewer side effects [20], that treatment for less than 3 months was ineffective [21], and that recurrences of viral replication were observed after cessation of interferon [22]. Hence, most current trials use a thrice-weekly dosing schedule for at least 3 months with a follow-up period of at least 6 months. Figure 1. Natural history of chronic hepatitis B acquired in childhood. Long-term follow-up studies to assess sustained viral eradication are now being published, but the sample sizes are small and the duration of follow-up is still less than 10 years [23]. No study has assessed the effect of interferon therapy on the clinically relevant end points of liver failure, hepatocellular carcinoma, and death as the progression of this disease evolves over decades. Such a study would require large numbers of patients followed for long periods. All studies to date have assessed efficacy using intermediate outcomes such as loss of hepatitis B surface antigen (HBsAg), HBeAg, and HBV DNA. Most studies have failed to show statistically significant treatment effects, but favorable trends have frequently been observed. We therefore conducted a meta-analysis of randomized, controlled trials to examine the efficacy of interferon treatment in patients with chronic HBV infection as determined by the loss of HBsAg, HBeAg, and HBV DNA. Methods Literature Search The meta-analytic methods used in this study conform to those previously described [24, 25]. The English-language medical literature was searched for randomized, controlled trials of -interferon therapy for chronic HBV infection. Trials were identified by a computer-aided search of the National Library of Medicine MEDLINE database from January 1966 to June 1992 using the terms exp INTERFERON TYPE I and HEPATITIS B, by manual review of the references of trials and review articles, and by personal communication with colleagues who had coordinated such studies. Inclusion and Exclusion Criteria All prospective randomized, controlled trials of interferon for the treatment of patients with chronic HBV infection, the results of which were published as articles in peer-reviewed journals, were included. For the purpose of this study, patients were defined as having chronic HBV infection with active viral replication if they had HBsAg and HBeAg in serum for more than 6 months and a pretreatment liver biopsy result consistent with chronic HBV infection. Duplicate reports, as well as studies reported solely in abstracts, letters, and preliminary reports, were excluded. Other predetermined criteria excluded trials that enrolled only children (younger than 18 years), trials that treated predominantly HBeAg-negative patients or patients who were coinfected with delta hepatitis, and trials that had treatment periods of less than 3 months or had follow-up periods of less than 6 months. Trials that used interferon in combination with another immunomodulatory or antiviral agent were excluded; however, if these trials included an arm in which interferon alone was compared with a control group, the data from that arm were included. Outcome Analysis As noted above, intermediate outcomes such as loss of HBsAg, HBeAg, and HBV DNA were evaluated as primary outcomes (see Figure 1). Secondary outcomes examined included the development of antibodies to HBsAg [anti-HBs] and to HBeAg (anti-HBe), normalization of serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels, and improvement in histologic indices. Our analyses were based on intent to treat; thus, all patients who were lost to follow-up were considered to be treatment failures. Subgroup analyses were selected prospectively and were based on factors that have been hypothesized to affect the outcome of interferon therapy [26-29]. These factors include gender, sexual preference, coinfection with human immunodeficiency virus (HIV), pretreatment AST and ALT levels, degree of inflammatory activity on pretreatment biopsy specimens, ethnic origin, duration of therapy and follow-up, preparation of -interferon, and dose of interferon used. We arbitrarily defined a dosage of more than 15 MU/m2 per week or its equivalent as high-dose treatment. Variables were analyzed within trials whenever possible; if sufficient data were not available, variables were analyzed across trials. Subgroup analyses based on duration of disease, previous history of acute icteric hepatitis, and pretreatment HBV DNA levels were not done because sufficient data were not available. The P values were not adjusted for multiple subgroup analyses. Data Abstraction Data abstraction was done by two independent readers. Results were subsequently compared, and differences were settled by consensus. Raw data on treatment and control modalities and outcomes in each trial were recorded on standardized forms. Contamination, cointervention, patient compliance, and the number of patients who dropped out or who were lost to follow-up were also noted. The data form for each study was sent to the respective investigators for confirmation of raw data and for completion of relevant missing data. A second form was sent if a reply was not obtained within 2 months. Seven of 16 trial investigators responded. Only published data were used for the analyses of primary and secondary outcomes, but data from personal communication were used, when available, for subgroup analyses. Quality Assessment Assessment of study quality was done using the quality assessment system of Chalmers and colleagues [30] as modified by L'Abbe and associates [25]. Two independent appraisers, not involved with data abstraction, evaluated only the Materials and Methods and Results sections of each study and were blinded with respect to the study authors, journals of publication, and specific treatment modalities used. The appraisers subsequently met to resolve any disagreements on an item-by-item basis. A quality score, which ranged from 0.0 to 1.0 points, was generated for each trial based on the number of predetermined criteria that were satisfied (supplied on request). The effect of study quality was assessed using the quality scores in sensitivity analyses. Statistical Analysis The appropriateness of statistically combining selected randomized, controlled trials was assessed by evaluating the comparability of trial protocols, the clinical features of included patients, and outcome measures. An underlying assumption in combining individual study results to obtain a better estimate of the true treatment effect was that the differences in the results among the studies were due to sampling variation alone. To test this assumption, characteristics of treatment and control groups in each individual trial were graphed and visually inspected for imbalances in absolute and proportionate terms [25]. Chi-square tests of heterogeneity were also done [31]. All outcome data except paired biopsy results from each study were pooled using difference in proportions (DP) (the proportion of outcome of interest in the treated group [Pt] minus the proportion of outcome of interest in the control group [Pc]): DP = Pt Pc A positive value favored the treatment arm, and a negative number favored the control arm. The individual confidence intervals (CIs) were calculated using a simple normal approximation [30]. Primary outcome data were also expressed as the number of patients who need to be treated to have one outcome of interest (NNT), where NNT is equal to the inverse of the difference in proportions: NNT = 1/DP and the 95% CIs for NNT are the reciprocals of the 95% CI for DP [32, 33]. Data were pooled, and confidence intervals were calculated using the method of DerSimonian and Laird [31] with pooled study variance estimates. The P values for the pooled treatment effects were then calculated using the means and variances in a z-test. Our statistical method of analysis used differences in proportions instead of the log odds scale [24] or odds ratios as the primary analysis because of the presence of a large number of zero outcomes in the control groups. To confirm our results, the Freeman-Tukey transformation [34] and a nonparametric sign test [35, 36] were also done. Paired biopsy results were assigned a numeric score (better = 1, same = 0, worse = 1). Data were analyzed using ordinal logistic regression, and the results were expressed as an odds ratio: Pt - 1 Pt odds ratio =- Pc - 1 Pc with t