Comparative Trial of Entecavir Versus Adefovir in the Treatment of Chronic Hepatitis B Infection: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Comparative Trial of Entecavir Versus Adefovir in the Treatment of Chronic Hepatitis B Infection (NCT00096785), a randomized phase 3 study. The primary outcome is Change From Baseline in Hepatitis B Virus DNA (HBV DNA) by Polymerase Chain Reaction (PCR) Assay at Week 12.

2. Clinical Question

The registry record describes a comparison of antiviral activity in adults with chronic hepatitis B who had not previously been treated with an antiviral medicine. The central statistical question is whether the mean change in serum HBV DNA from baseline to Week 12 differed between participants assigned to entecavir and those assigned to adefovir. The endpoint is expressed in log10 copies/mL, and a negative change represents a reduction in measured HBV DNA.

This is a laboratory-outcome comparison, not a direct comparison of symptoms, complications, or long-term clinical events. The registry also lists Week 48 viral-load outcomes and ALT normalization as secondary outcomes. Those measures broaden the description of antiviral and biochemical responses, but the primary question remains the Week 12 change in HBV DNA.

3. Trial Design

This was a randomized, open-label, parallel-group phase 3 trial. Participants were assigned to entecavir or adefovir, with no masking reported. The registry record gives total enrollment as 69. The primary endpoint summaries include 33 participants in each group and are defined for as-randomized participants who completed 12 weeks of treatment. The record does not explain the difference between total enrollment and the primary endpoint group counts.

The trial focused on nucleoside-naive adults with chronic hepatitis B. Its stated purpose was to evaluate antiviral activity and efficacy of entecavir compared with adefovir in adults not previously treated with an antiviral medicine. The primary outcome was measured at Week 12, while the registry also lists a Week 48 change in HBV DNA and Week 48 outcomes for undetectable viral load and ALT normalization.

Randomization can reduce systematic differences between groups at baseline, on average, but it does not ensure that groups are identical in a trial of this size. Open-label assignment means masking was not used; the record does not state whether outcome assessment or laboratory procedures were separately blinded. The registry lists entecavir and adefovir as the interventions, but treatment schedules and dose details are not reported in the intervention descriptions. The arm descriptions are also not reported in the registry record.

Enrollment, allocation, treatment duration, and analysis-population details should be read separately. The registry status is completed, but the number completing treatment beyond the specified Week 12 primary population, participant flow, and reasons for withdrawal are not reported in the registry record.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Before assignment: 132 enrolled; 63 not randomized (59 did not meet study criteria, 3 withdrew consent, 1 lost to follow-up). 1 randomized to adefovir (ADV) received entecavir (ETV) throughout treatment, \& is counted in the ADV group for primary efficacy analysis, not included in the secondary efficacy analyses, \& counted in the ETV group in safety analyses.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: As-randomized participants who completed 12 weeks of treatment

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

6. Primary Endpoint

The registry lists the primary outcome as Change From Baseline in Hepatitis B Virus DNA (HBV DNA) by Polymerase Chain Reaction (PCR) Assay at Week 12, measured over Baseline, Week 12.

The primary endpoint is the mean change in serum HBV DNA from baseline to Week 12, measured by polymerase chain reaction and expressed in log10 copies/mL. The registry defines the change as Week 12 minus baseline and specifies that a negative value means improvement. The outcome is adjusted for baseline in the description, although the exact statistical model used for that adjustment is not reported in the registry record.

HBV DNA is a laboratory measure of the amount of hepatitis B virus genetic material detected in serum. In general, measuring change from baseline helps describe how a continuous marker shifts during treatment while accounting for where participants started. A continuous measure also retains information about the size of changes rather than reducing every result to a threshold category.

This endpoint is used to compare the groups’ average short-term virologic changes. It does not directly measure symptoms, quality of life, liver complications, or long-term health outcomes. Nor does a group mean describe every participant’s response: individual changes can vary around the mean. The registry’s primary population is as-randomized participants who completed 12 weeks of treatment, so the reported mean is not described as an analysis of every enrolled participant regardless of completion.

7. Results Posted in the Registry

• Adefovir: mean -4.52 versus -6.23 on control; difference 1.71 (95% CI 0.86 to 2.56), standardized effect d = 0.97; z-test p = <0.001.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Change From Baseline in HBV DNA by PCR Assay at Week 48

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard errors.
• Result:
  • Adefovir: mean -5.08 versus -7.28 on control; difference 2.20 (95% CI 1.10 to 3.30), standardized effect d = 0.98; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Adefovir than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Viral Load Undetectable (HBV DNA <300 Copies/mL)

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Adefovir: 18.8% (6/32) versus 57.6% (19/33) on control; risk difference -38.8 percentage points (95% CI -60.4 to -17.2), risk ratio 0.33 (0.15–0.71); unadjusted two-proportion z-test p = 0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically lower for Adefovir than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Alanine Aminotransferase (ALT) Normalization

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Adefovir: 62.5% (20/32) versus 75.8% (25/33) on control; risk difference -13.3 percentage points (95% CI -35.5 to 9.0), risk ratio 0.82 (0.59–1.15); unadjusted two-proportion z-test p = 0.247.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Adefovir and the control. The interval gives the range of effects that remain compatible with the data.

Across the posted secondary outcomes, the viral-marker results are directionally consistent with the primary Week 12 comparison: the Week 48 average HBV DNA change and the count meeting the undetectable viral-load definition both show a pattern favoring entecavir on those measures. ALT normalization is less clearly separated in the posted summaries. This broad pattern offers additional description of laboratory outcomes over the trial’s reported follow-up, but it is not a single combined measure and does not establish that every secondary outcome has the same certainty.

The secondary outcomes differ in their definitions and statistical scales. A continuous change in HBV DNA, a count meeting a threshold, and a count with ALT normalization each answer a distinct question. Their estimates should therefore be interpreted on their own terms rather than pooled informally into one overall conclusion. The registry lists additional exploratory viral-kinetics outcomes, but numerical results for those outcomes are not reported in the registry record.

Unadjusted secondary results carry less weight when many outcomes are examined because the chance of at least one apparently notable result can increase across multiple tests. This is a general statistical concern; it does not establish that any particular result is false. The registry does not report a multiplicity strategy, and the listed secondary analyses do not include reported inferential analyses. Their p-values should accordingly be treated as unadjusted evidence, not as confirmatory results protected by a stated family-wise testing plan.

The secondary findings can help describe whether the primary pattern is echoed by other laboratory measures, but they cannot replace the prespecified primary question or resolve limitations in the analysis population and missing-data reporting. Long-term clinical outcomes and patient-centered outcomes are not among the posted numerical secondary results.

Secondary outcomes registered for this trial, for reference (only those above were recalculated):

• Change From Baseline in HBV DNA by PCR Assay at Week 48
• Viral Load Undetectable (HBV DNA <300 Copies/mL)
• Alanine Aminotransferase (ALT) Normalization
• HBV DNA Viral Kinetics Estimates of Exponential Decay Model - Efficacy in Blocking Virus Production and de Novo Infections
• HBV DNA Viral Kinetics Estimates of Exponential Decay Model - Viral Clearance Rate and Infected Cell Death Rate
• HBV DNA Viral Kinetics Estimates of Exponential Decay Model - Half-Life of Free Virus
• HBV DNA Viral Kinetics - Spline Model
• Summary of Safety - Most Frequent (> 10%) Adverse Events (AEs), Serious Adverse Events (SAEs), Discontinuations Due to AEs, and Deaths

9. Statistical Interpretation

10. Statistical Methods Explained

The statistical summaries describe a randomized parallel-group comparison, with entecavir as the reference group for the posted mean difference and adefovir as the comparison group. Randomization is a design feature intended to support fair comparisons by allocating participants without choosing their treatment based on their characteristics. It does not remove the need to examine how outcomes were defined, who was included in the analysis, and how uncertainty was quantified.

What does a mean change represent?

For a continuous outcome, a mean is the arithmetic average of the observed values in a group. Here the values are changes in HBV DNA from baseline to Week 12, in log10 copies/mL. A negative change indicates a lower measured value at Week 12 than at baseline. The group mean gives a compact description of the average change, but it can conceal variation: participants may have changes that are larger or smaller than the average.

The mean difference compares the two group means on the same measurement scale. The posted primary contrast is 1.71 log10 copies/mL for adefovir relative to entecavir. Since the group means are both negative and the adefovir value is less negative, the positive contrast indicates a larger average reduction in the entecavir group. This interpretation depends on the order of subtraction; the value is not an absolute amount of virus and is not a participant-level result.

How should standard errors be read?

The reported spreads for the primary means are standard errors: 0.247 for entecavir and 0.357 for adefovir. A standard error describes uncertainty in an estimated mean, rather than the spread of individual participant outcomes. In general, a smaller standard error means the estimate is more precise under the model and sampling assumptions. Standard errors should not be mistaken for standard deviations, which describe participant-to-participant variability. The registry record does not give the standard deviations for the primary endpoint.

For the Week 48 continuous endpoint, the reported standard errors are 0.327 for entecavir and 0.455 for adefovir. These summarize uncertainty around the group means, not the range of individual HBV DNA changes. Standard errors alone do not fully specify how the analysis was performed; the registry does not report the model details or all assumptions used to estimate them.

What does a confidence interval add?

A confidence interval expresses uncertainty around an estimated effect using a range of values compatible with the data and the method used to construct the interval. In general, intervals that exclude zero for a difference are consistent with a nonzero difference under the interval’s assumptions. The primary reported interval lies above zero. Its confidence level and the exact interval procedure are not reported in the registry record, so those details should not be assumed. The p-value and interval convey related but different information: the interval indicates a range of effect estimates, while the p-value summarizes compatibility with a specified null model.

What does the binary analysis describe?

The Week 48 undetectable viral-load outcome is expressed as a participant count at the threshold HBV DNA <300 copies/mL. A risk difference is a contrast between the proportions meeting that definition in the two groups; the posted comparison is oriented as adefovir relative to entecavir. The count and denominator are important because they show how many participants contributed to each group summary. The registry reports a p-value of 0.001 for this comparison, but no adjusted secondary analysis is listed.

ALT normalization is also a binary outcome, recorded as counts at Week 48. For this result the reported unadjusted p-value is 0.247. A non-small p-value does not demonstrate that the groups are identical. It indicates that the data do not provide strong evidence against the tested no-difference model under the analysis used. Interpretation should also consider the estimate’s uncertainty and the number of outcomes assessed.

Why can over-dispersion matter?

In general, over-dispersion occurs when observed variability is larger than a statistical model expects. If a model assumes less variability than the data contain, standard errors can be too small and inferential results can appear more precise than warranted. This is a general consideration for count and binary-outcome modeling, not a claim that over-dispersion occurred in this trial. The registry record does not report a model assessment for over-dispersion.

The record lists no reported secondary analyses, and it does not describe covariate adjustment, missing-data procedures, or multiplicity adjustment. The reported p-values are identified as unadjusted. These omissions limit what can be concluded about the full statistical analysis plan and how robust the results are to alternative analysis choices.

11. Confidence Intervals and Precision

The primary mean estimates have reported standard errors of 0.247 log10 copies/mL for entecavir and 0.357 log10 copies/mL for adefovir. The posted mean difference is 1.71, and its reported interval lies above zero. Together with the unadjusted p-value of <0.001, this indicates that the observed difference is estimated with enough precision to distinguish its direction from zero under the reported analysis. The registry does not state the confidence level or interval-construction method.

Precision is not the same as clinical importance. An interval describes uncertainty about a group-level effect on the measured scale; it does not show how much participants’ individual responses varied, and it does not address outcomes that were not measured. The primary endpoint population includes participants who completed 12 weeks of treatment, so uncertainty estimates do not account for any unknown impact of missing outcomes unless the underlying analysis handled them in a way not described in the registry.

The secondary Week 48 continuous comparison also has a reported interval that lies above zero, alongside an unadjusted p-value of <0.001. For ALT normalization, the reported risk-difference interval includes zero and the unadjusted p-value is 0.247. The undetectable viral-load comparison has an unadjusted p-value of 0.001. These results differ in both outcome type and uncertainty, and should not be treated as interchangeable estimates of one common effect.

Confidence intervals are generally useful because they convey a range of plausible effects rather than only a threshold-based significance result. Here, exact interval endpoints with more than three decimal places are not repeated; the direction and whether the interval includes zero are sufficient to describe the reported precision without implying more detail than is appropriate. The record does not report adjusted intervals accounting for multiple secondary outcomes.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning figures are participants per arm for the continuous and binary outcomes discussed in the record; they are not total event counts. For the primary Week 12 comparison, planning for 100% of the observed effect gives 17 participants per arm for 80% power and 23 participants per arm for 90% power. Planning for 75% of the observed effect gives 30 participants per arm for 80% power and 40 participants per arm for 90% power. Planning for 50% of the observed effect gives 67 participants per arm for 80% power and 90 participants per arm for 90% power.

These are planning illustrations based on the observed effect, not the trial’s original design calculations. The listed assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation; the effect to detect is the stated fraction of the observed effect. The original sample-size justification and design assumptions are not reported in the registry record.

In plain terms, the 80% column gives the estimated number of participants per arm for a design with an 80% chance of detecting the specified effect if that effect is real and the planning assumptions hold. The 90% column uses a higher target chance of detection and consequently gives a larger planned group size. Smaller effects are harder to distinguish from random variation, so planning to detect smaller effects requires more participants per arm. These figures are not observed power: they do not measure the probability that this completed trial detected a true effect.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = 1.710; pooled standard deviation σ = 1.763.
2. n = 2 × (1.96 + 0.842)² × 1.763² / 1.710² = 16.7, rounded up to 17 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
delta <- 1.71                      # observed difference in means
sigma <- 1.76339360325482                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(96785)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 17 (80% power), 23 (90% power)
 75% of observed effect: n per arm = 30 (80% power), 40 (90% power)
 50% of observed effect: n per arm = 67 (80% power), 90 (90% power)
power.t.test: 17.7 
Simulated power at n = 17 per arm: 0.781 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Multiplicity, Missing Data and Analysis Populations

The registry identifies a primary Week 12 HBV DNA change and lists multiple secondary outcomes, including Week 48 HBV DNA change, undetectable viral load, ALT normalization, several viral-kinetics measures, and safety summaries. Considering multiple endpoints creates a multiplicity issue: when many hypotheses are tested, some may appear statistically notable by chance even if there is no underlying effect. In general, a prespecified testing hierarchy or adjustment can help control that issue. The registry record does not report a multiplicity plan, adjustment method, or hierarchy among secondary outcomes.

The posted Week 12 comparison and numerical secondary comparisons are marked unadjusted. The registry lists no reported analyses for the secondary outcomes, while numerical summaries are available for some of them. It is therefore not possible to establish from the registry record which secondary results were intended as formal hypothesis tests, whether other planned tests were omitted, or how the trial’s full analysis plan treated repeated testing.

The primary endpoint population is described as as-randomized participants who completed 12 weeks of treatment. This specifies an analysis population, but it is not equivalent to knowing how missing outcome data were handled. The registry does not report the number of participants with missing Week 12 values, reasons for missingness, imputation methods, sensitivity analyses, or a participant-flow account. The Week 48 summaries have denominators of 33 and 32 for continuous HBV DNA and binary outcomes; the reason the adefovir denominator differs from the entecavir denominator is not reported in the registry record.

Randomization describes assignment, but it does not by itself establish that every randomized participant was included in every analysis. The registry does not report a complete intention-to-treat analysis, a per-protocol analysis, or sensitivity analyses for departures from the stated completion population. These gaps constrain assessment of whether missing data or analysis choices could affect the estimates. They do not show that a particular bias occurred; they mean that the available record does not resolve it.

15. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: alanine aminotransferase increased (3.0%), rib fracture (3.0%).

The registry’s serious-adverse-event summary lists 2 of 33 participants at risk in the ADV 10 mg group and 1 of 36 at risk in the ETV 0.5 mg group. These are group-level event summaries with their stated at-risk denominators. They should not be read as proof that one treatment is safer: the counts are limited, the record does not provide a comparative safety analysis, and the event categories and observation details are not fully described.

The most frequent serious-event terms listed are alanine aminotransferase increased and rib fracture, each reported as 3.0%. The record also lists other adverse events for 16 of 33 participants in the ADV group and 17 of 36 in the ETV group. Definitions and detailed event-level information are not reported in the registry record, so these summaries should not be interpreted as a complete account of severity, duration, or causality.

Deaths are not reported in the registry record. This is different from a confirmed report of zero deaths. The safety summaries describe what was recorded, not whether an event was caused by treatment or how risks compare in populations beyond this trial.

16. What the Result Does, and Does Not, Mean

The primary result describes a difference between group averages in change in a laboratory marker over 12 weeks. The entecavir group mean was -6.23 log10 copies/mL and the adefovir group mean was -4.52 log10 copies/mL; the posted mean difference was 1.71, with an unadjusted p-value of <0.001. These statistics support the conclusion that the observed average changes differed under the reported comparison. They do not say that every participant experienced a reduction or that each participant’s change matched the group mean.

The result does not, on its own, establish effects on symptoms, liver complications, mortality, quality of life, or long-term disease outcomes. HBV DNA change is a laboratory endpoint, and the registry does not provide numerical results for the listed exploratory viral-kinetics measures. The Week 48 secondary summaries add information about laboratory outcomes, but the record does not report long-term follow-up beyond those listed outcomes.

A statistically notable result is not automatically a statement about clinical importance. The record does not give a threshold for a clinically meaningful difference in HBV DNA, nor does it link the observed mean difference to an individual-level benefit. The open-label design, specified completion population, and unreported missing-data procedures also matter when judging how fully the group comparison represents all randomized participants.

Finally, the findings apply to the population and trial conditions described in the registry: nucleoside-naive adults with chronic hepatitis B assigned to entecavir or adefovir in this randomized comparison. The record does not provide enough detail to extend the result to different populations, regimens, or treatment settings. Statistical evidence about this measured endpoint should not be presented as a recommendation about treatment choice.

17. Why This Trial Matters Statistically

This trial illustrates how a randomized comparison can quantify a difference in a continuous laboratory endpoint while preserving the direction and magnitude of the group means. Because the endpoint is change from baseline, the sign has a direct interpretation: negative values indicate lower HBV DNA at follow-up than at baseline. Reporting both group means and a between-group contrast makes clear that the contrast is not the same as either group’s change considered alone.

It also demonstrates why uncertainty measures matter. Standard errors describe precision of the means, while an interval around the difference conveys uncertainty about the comparison. A p-value alone cannot show the range of effects compatible with the data. The interpretation is stronger when these quantities are read together and remains tied to the endpoint scale and analysis population.

The record is also a useful example of the distinction between a primary result and exploratory or secondary evidence. Viral-load outcomes show a pattern aligned with the primary laboratory comparison, whereas ALT normalization is less clearly separated. Without a reported multiplicity plan, secondary p-values should not be treated as a set of independent confirmatory claims. Similarly, safety counts are descriptive and cannot establish comparative safety by themselves.

Finally, the record highlights that a completed trial entry may still leave important statistical details unavailable. The analysis model, missing-data procedures, original sample-size rationale, and handling of multiple outcomes are not reported in the registry record. Recognizing such omissions is part of interpreting results responsibly: it distinguishes what the posted estimates show from what remains uncertain about their analysis and broader implications.

18. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

Several limitations specific to this record affect interpretation. The trial was open-label, with no masking reported. Although HBV DNA is a laboratory measure, the record does not state whether laboratory assessment was blinded or whether other outcome assessments were protected from knowledge of assignment. The arm descriptions are blank, and the intervention descriptions do not provide dose or schedule details.

The primary endpoint is defined for participants who completed 12 weeks of treatment, while total enrollment is 69 and the primary endpoint summaries include 33 participants per group. Participant flow, reasons for noncompletion, and the handling of missing primary outcome data are not reported in the registry record. The Week 48 summaries include 33 entecavir and 32 adefovir participants; the reason for this denominator difference is also not reported.

The analysis model and baseline-adjustment procedure are not described in detail. The registry does not report the original sample-size justification, covariate adjustment, sensitivity analyses, or the confidence level used for the reported intervals. It also does not report a multiplicity strategy despite listing multiple secondary outcomes. These omissions limit evaluation of model assumptions and the confirmatory status of secondary findings.

The posted outcomes emphasize virologic and biochemical measures. Numerical results for the listed viral-kinetics outcomes are not reported in the registry record, and the record does not provide long-term clinical outcomes. The available summaries therefore cannot answer questions about clinical events or persistence beyond the reported follow-up. These limitations describe gaps in the registry record; they do not establish that a particular design or analysis error occurred.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Comparative Trial of Entecavir Versus Adefovir in the Treatment of Chronic Hepatitis B Infection — NCT00096785.
• Registry record last updated 2010-08-10; status last verified 2010-06.
• Results first posted 2010-01-06.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

22. Record Summary

The registry describes NCT00096785 as a completed, randomized, open-label, parallel-group phase 3 comparison of entecavir and adefovir in adults with chronic hepatitis B who had not previously received antiviral treatment. Total enrollment is 69. The primary endpoint is mean change in HBV DNA from baseline to Week 12 among as-randomized participants who completed 12 weeks.

The primary group means are -6.23 log10 copies/mL for entecavir and -4.52 log10 copies/mL for adefovir. The posted mean difference is 1.71, with an unadjusted p-value of <0.001. Week 48 secondary summaries include HBV DNA change, undetectable viral load, and ALT normalization. The record also lists exploratory viral-kinetics and safety outcomes.

Multiplicity procedures, missing-data methods, detailed analysis models, and the original sample-size justification are not reported in the registry record. Deaths are not reported in the registry record.