The Effects of Adding TCM-700C on the Standard Combination Treatment for Patients With Genotype 1 Hepatitis C Infection: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for The Effects of Adding TCM-700C on the Standard Combination Treatment for Patients With Genotype 1 Hepatitis C Infection (NCT00556504), a randomized phase 2 study. The primary outcome is Sustained Virologic Response (SVR).

2. Clinical Question

This is a comparison of add-on treatments: both arms received conventional combination treatment, and the randomized difference was TCM-700C versus placebo. The endpoint focuses on virologic status after treatment has ended, rather than only at the end of active combination treatment. The registry describes the study as phase II and randomized, with quadruple masking and a parallel-group model. Those design features define the intended comparison, but do not by themselves establish how the endpoint was analyzed or how missing results were handled beyond the endpoint rules in the record.

3. Trial Design

The registry describes a completed phase II, randomized, quadruple-masked, parallel-group trial. Enrollment was 84. The listed start was 2007-07 and primary completion was 2011-01. TCM Biotech International Corp. is named as the sponsor. The registry record does not report a detailed protocol description, randomization method, allocation concealment procedures, or the definitions of the masking roles.

Participants were assigned to TCM-700C or placebo as an add-on to peginterferon and ribavirin. The primary outcome counts show 42 participants in each arm. This is consistent with the record’s randomized comparison and equal arm counts, but the record does not state that equal allocation was a design assumption or describe how assignment was generated.

There is a naming difference in the recorded combination treatment: the brief summary refers to peginterferon α-2b, whereas the intervention list and arm descriptions refer to peginterferon alfa-2a. The registry record does not explain the difference, so it cannot be resolved from the posted information.

The primary completion date and completed status describe the registry’s study record. They do not supply details about recruitment flow, withdrawals, protocol deviations, or the timing and conduct of analyses. A sample-size justification for the original trial, its target effect, and its planned significance level are not reported in the registry record. Nor are interim analyses or a detailed statistical analysis plan reported.

The randomized design is relevant because it is intended to make the assigned add-on treatment the basis for comparing arms. Interpretation still depends on how participants were analyzed, how missing outcomes were treated, and whether the reported comparison followed a prespecified plan. Those details are not all available in the record. The stated SVR definition does include rules for missing HCV RNA measurements and for a missing or detectable Week 72 result.

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.

Overall Study

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 Sustained Virologic Response (SVR), measured over 24 weeks after the termination of combinational drug treatment (up to 72 weeks).

The primary endpoint was the number of participants with sustained virologic response (SVR), assessed 24 weeks after combination drug treatment ended, at Week 72. SVR was defined as no detectable HCV RNA in serum at that time. This endpoint therefore asks whether a participant remained without detectable virus through the post-treatment assessment, rather than whether HCV RNA was absent only at the end of treatment.

The registry’s definition includes longitudinal and missing-data rules. A participant counted as a sustained responder at a given week only if HCV RNA was negative at that week and at all subsequent weeks through Week 72. If a measurement was missing between visits, the last non-missing HCV RNA result was carried forward. If the Week 72 measurement was missing or above the limit of detection, the participant was classified as a non-responder, even if earlier measurements had been undetectable. HCV RNA was to be tested with a commercially available real-time polymerase-chain-reaction assay, named as the Roche Cobas TaqMan HCV assay kit.

In general, a post-treatment endpoint can describe response after the treatment period has finished, while its interpretation depends on the endpoint definition and follow-up measurement. Here, the registry’s explicit rules determine how the final classification is made. The record does not provide further detail about assay thresholds, endpoint adjudication, or whether any alternative endpoint definitions were planned.

7. Results Posted in the Registry

• TCM-700C: 64.3% (27/42) versus 69.0% (29/42) on control; risk difference -4.8 percentage points (95% CI -24.9 to 15.4), risk ratio 0.93 (0.69–1.26); unadjusted two-proportion z-test p = 0.643.

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.

Virologic Response

• 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:
  • TCM-700C: 81.0% (34/42) versus 73.8% (31/42) on control; risk difference 7.1 percentage points (95% CI -10.7 to 25.0), risk ratio 1.10 (0.87–1.38); unadjusted two-proportion z-test p = 0.434.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between TCM-700C and the control. The interval gives the range of effects that remain compatible with the data.

ALT Response

• 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:
  • TCM-700C: 76.2% (32/42) versus 71.4% (30/42) on control; risk difference 4.8 percentage points (95% CI -14.0 to 23.5), risk ratio 1.07 (0.83–1.38); unadjusted two-proportion z-test p = 0.620.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between TCM-700C and the control. The interval gives the range of effects that remain compatible with the data.

Sustained ALT Response

• 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:
  • TCM-700C: 61.9% (26/42) versus 64.3% (27/42) on control; risk difference -2.4 percentage points (95% CI -23.0 to 18.3), risk ratio 0.96 (0.69–1.34); unadjusted two-proportion z-test p = 0.821.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between TCM-700C and the control. The interval gives the range of effects that remain compatible with the data.

The posted secondary outcomes cover response at the end of combination treatment and sustained response after treatment, including virologic and ALT-related measures. Across these outcomes, the estimates do not all point in the same direction. Their confidence intervals are broad and include no difference, so they do not form a consistent, precise pattern that would materially clarify the primary comparison.

These outcomes complement the primary SVR endpoint by describing response at other times or using ALT-related measures. They are not interchangeable with SVR: their timing and definitions differ. In general, agreement across distinct endpoints can provide context, but it is most informative when outcomes and analyses are prespecified and their relationships are understood. The registry record does not report a testing hierarchy, a multiplicity adjustment, or inferential analyses for the posted secondary outcomes.

Unadjusted secondary results carry less weight because several outcomes may be examined. General statistical explanation: when multiple hypotheses are tested, chance alone can produce apparently notable findings more often than when only one hypothesis is tested. A planned adjustment or hierarchy can address that issue, but the registry record does not report such a plan. Secondary estimates should consequently be treated as descriptive or exploratory rather than as separate confirmation of the primary result.

The registry lists six secondary outcome labels, while quantitative results are posted for three secondary endpoints in the record summarized by these results. The remaining named outcomes cannot be evaluated from quantitative comparisons in the record. No conclusions about those outcomes should be inferred from the results that are available.

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

• Virologic Response
• ALT Response
• Sustained ALT Response
• Combined ALT and Virologic Response
• Immune Cell Normalization
• Immune Cell Normalization

9. Statistical Interpretation

10. Statistical Methods Explained

For a binary endpoint, each participant is classified into one of two outcome categories, such as having or not having SVR. The posted arm counts give the number classified with the outcome and the number assessed in each arm. Here the primary outcome is recorded as counts among 42 participants in each group. In general, such counts can be expressed as risks or proportions, but interpretation should retain the denominator and the endpoint definition because both determine what the observed result means.

The principal contrast is a risk difference: the outcome risk in the TCM-700C arm minus the outcome risk in the placebo arm. A value of zero corresponds to equal observed risks, while a value on either side indicates the direction of the estimated difference. The primary risk difference is -0.048. This signed contrast is useful because it is expressed on the absolute-risk scale, but it does not by itself indicate precision. That is why it is read alongside its confidence interval.

General statistical explanation: a confidence interval describes a range of values compatible with the observed data under the method’s assumptions. It is not a guarantee that the true effect lies in the particular calculated interval, and it does not remove uncertainty. For a risk difference, an interval that includes zero means that the data are compatible with no difference as well as with differences in either direction within the interval. The registry record provides the primary interval but does not report the method used to construct it.

A p-value is also conditional on a statistical model and a null hypothesis. In general, it describes how unusual data at least as inconsistent with that null hypothesis would be if the null model and its assumptions were true. It is not the probability that the null hypothesis is true, nor does it quantify clinical importance. The posted primary p-value is unadjusted. The exact test, sidedness, and any covariate adjustment are not reported in the registry record, so the p-value should not be attributed to a specific test or analysis procedure.

Other relative measures can describe a binary comparison. A risk ratio compares the risks, while an odds ratio compares the odds. These measures use different scales and need not have the same numerical values or intuitive interpretation as a risk difference. Their estimates and intervals are included in the posted comparison results, but they should not be treated as independent replications of the primary finding: they are alternative summaries of the same arm outcomes.

The registry defines SVR using measurements over time and specifies how certain missing measurements are classified. Intermediate missing HCV RNA results are filled using the last non-missing result. A missing or detectable result at Week 72 is classified as non-response. In general, carrying a prior value forward can make the final classification depend on an earlier measurement, and treating a missing endpoint as failure can affect the estimated response proportion. The registry record does not report sensitivity analyses that assess how alternative missing-data assumptions would change the result.

General explanation: randomization is intended to balance measured and unmeasured characteristics across groups on average, supporting interpretation of an arm comparison. It does not ensure identical groups in a particular trial, especially when the sample is limited, and it does not resolve missing outcome data or departures from assigned treatment. The record identifies randomized allocation and equal primary outcome counts, but it does not describe the randomization sequence, concealment, adherence, or analysis population in detail.

Masking can reduce the potential for expectations to influence care, outcome measurement, or assessment, depending on which parties are masked and how masking is maintained. The registry labels the trial quadruple-masked but does not define the four roles or report whether masking was assessed. The label alone therefore cannot establish how masking operated in practice.

For the sample-size planning illustrations, the stated assumptions are a two-sided significance level of 0.05, equal allocation between arms, and a normal approximation. The effect to detect is a stated fraction of the observed effect. These assumptions are used for planning illustrations and are not reported as the trial’s original design assumptions. The registry record does not report the original sample-size justification, planned target effect, or a planned power calculation for this trial.

General explanation: power is the probability that a specified design and analysis would detect an effect of a stated size under particular assumptions. It depends on the effect being targeted, the outcome rate, sample size, significance criterion, and analysis method. A planning calculation using an effect estimated from the same trial is not a retrospective measure of whether the trial had adequate power. It is especially sensitive to uncertainty in a small trial’s observed effect.

The registry lists several secondary outcomes, including virologic and ALT response measures, and posts quantitative results for some of them. It does not report their inferential analyses in the record. Multiple outcomes create a general multiplicity concern: if many hypotheses are tested, the chance of at least one apparently notable result can increase. Whether and how to adjust depends on a prespecified testing strategy. Such a strategy is not reported, so no adjustment or confirmatory hierarchy should be assumed.

11. Confidence Intervals and Precision

The primary risk-difference estimate is -0.048, with a 95% confidence interval from -0.249 to 0.154. This interval includes zero and extends in both directions. It is therefore consistent with a range of possibilities, rather than tightly locating the difference at the point estimate. The interval’s breadth is important: the estimated direction alone is not enough to describe the evidence.

In general, a confidence interval communicates precision as well as direction. A narrower interval indicates that the estimate is more tightly bounded under the method’s assumptions; a wider interval leaves more uncertainty. An interval that crosses zero does not establish that the arms are equivalent. It also does not prove that there is no difference. To make an equivalence or non-inferiority claim, a trial would need a suitable prespecified margin and corresponding analysis, which are not reported in the registry record.

The arm counts were 27 of 42 for TCM-700C and 29 of 42 for placebo. With 42 participants in each arm, the primary estimate rests on a limited number of observations. The interval should be read as a range of effect sizes compatible with the data and the unreported interval method, not as a clinical threshold or a probability distribution over possible effects.

The relative measures also have intervals: the risk ratio was 0.931 with an interval from 0.688 to 1.261, and the odds ratio was 0.807 with an interval from 0.325 to 2.003. These are alternative scales for summarizing the same comparison; they do not supply additional independent evidence. The record does not state how these intervals were constructed.

Precision is distinct from whether a p-value meets a conventional threshold. The primary unadjusted p-value is 0.643, but the interval is more informative about the range of differences compatible with the estimate. Neither statistic alone resolves the uncertainties arising from the sample size, the analysis details not reported in the registry record, or the stated endpoint rules.

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 sample-size planning figures are participants per arm, not total participants across both arms and not total events. The registry’s stated planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, a normal approximation, and an effect to detect equal to the stated fraction of the observed effect. The original trial’s own sample-size assumptions and justification are not reported in the registry record.

The 80% power column gives the estimated number of participants per arm for a planning scenario that would have an 80% probability of detecting the specified effect, under the listed assumptions. The 90% power column gives the corresponding per-arm planning number for a 90% probability. These are design illustrations, not descriptions of the trial’s achieved power. This is not observed power.

Rows for planning at 100%, 75%, and 50% of the observed effect describe different assumed effect sizes. A smaller effect is harder to distinguish from chance variation, so it generally requires more participants to reach the same planned power under the same assumptions. These calculations use the observed effect as a reference, but the observed estimate is uncertain and may differ from the underlying effect.

The figures should therefore be read as conditional planning examples rather than as evidence that a larger trial would necessarily reproduce the observed result. They do not revise the trial’s actual enrollment of 84 or establish what the original investigators intended. The record does not provide an original target sample size or explain whether enrollment followed a prespecified power calculation.

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, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.690; treatment proportion p₁ = 0.643; average p̄ = 0.667.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6667 = 1.3066.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6658 = 0.5604.
4. n = (1.3066 + 0.5604)² / (-0.0476)² = 1,537.2, rounded up to 1,538 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
p0 <- 0.69047619047619                          # control proportion
p1 <- 0.642857142857143                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^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 (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(556504)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 1,538 (80% power), 2,058 (90% power)
 75% of observed effect: n per arm = 2,709 (80% power), 3,626 (90% power)
 50% of observed effect: n per arm = 6,039 (80% power), 8,084 (90% power)
power.prop.test: 1537.2 
Simulated power at n = 1,538 per arm: 0.800 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-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 record does not report a statistical analysis plan, a prespecified hierarchy for primary and secondary hypotheses, or a multiplicity adjustment. The primary endpoint is identified, but the record does not state whether it was the sole confirmatory test or how secondary analyses were intended to influence interpretation. The posted primary p-value is unadjusted, and no secondary inferential analyses are reported in the registry record.

In general, multiplicity matters when several outcomes, time points, or comparisons are tested. Without a prespecified strategy, a nominal p-value from an individual secondary comparison does not account for the broader set of analyses that may have been considered. This does not make the estimates unusable; it means their evidential role is weaker and should be described cautiously.

The SVR definition gives specific missing-data rules. If a value was missing between visits, the last non-missing HCV RNA value was carried forward. If Week 72 was missing or above the detection limit, the participant was classified as a non-responder, even if all earlier results had been undetectable. These rules are part of the endpoint definition in the registry. The record does not report the number of missing measurements, the number classified as non-responders because Week 72 was missing, or sensitivity analyses using other assumptions.

The primary results list 42 participants in each arm, but the record does not give a detailed account of the analysis population or participant flow. It does not report whether the analysis was intention-to-treat, per-protocol, or based on another population definition. Safety populations are separately identified for adverse events, with 41 in the TCM-700C group and 42 in the placebo group. The registry record does not explain the difference between the TCM-700C primary count and safety population count.

Interim analyses, handling of protocol deviations, and adjustment for baseline characteristics are not reported in the registry record. These absences limit the ability to reconstruct the full analysis process, but they do not alter the arithmetic of the posted arm counts and comparison estimates.

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: urinary infection (4.9%), fever/pain (4.9%), anemia (2.4%), hearing impairment (2.4%), rhinorhea (2.4%).

The safety results report serious adverse events for 9 of 41 participants in the TCM-700C safety population and 6 of 42 in the placebo safety population. The record lists urinary infection and fever/pain at 4.9% each in the serious-event terms, and anemia, hearing impairment, rhinorhea, and neuritic depression at 2.4% each. These are the terms and percentages recorded for serious adverse events; the registry does not provide further detail about event timing, recurrence, severity grading, or attribution.

These counts are descriptive observations within the listed safety populations. They do not by themselves establish that an event was caused by the add-on, or that the groups differ reliably in underlying safety risk. The counts are small, and no inferential safety comparison is reported in the registry record. Death counts are not reported in the registry record.

General statistical explanation: safety comparisons depend on how events are defined and collected, the number of participants exposed, the duration of observation, and whether multiple events in one participant are counted separately. The registry’s listed counts do not resolve those details. They should be read as a record of reported serious adverse events, not as a complete characterization of comparative safety.

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

The posted primary result is a randomized comparison of TCM-700C and placebo as add-ons to combination treatment. SVR was recorded for 27 of 42 participants in the TCM-700C group and 29 of 42 in the placebo group. The estimated risk difference was -0.048, with a 95% confidence interval from -0.249 to 0.154. These data describe the trial’s observed outcomes and leave substantial uncertainty about the size and direction of the underlying difference.

The result does not establish that the add-on improves SVR, nor does it establish that the add-on has no effect. A confidence interval that includes zero is not proof of equivalence. The record does not provide an equivalence or non-inferiority margin, and the trial’s original sample-size justification is not reported. The unadjusted p-value of 0.643 should not be interpreted as the probability that the treatments are the same or that the observed result is due to chance.

The endpoint definition and missing-data rules matter to the meaning of the counts. Intermediate missing HCV RNA values were carried forward from the last non-missing value, while a missing or detectable Week 72 result counted as non-response. The record does not report how many participants were affected by these rules or how alternative missing-data methods would change the comparison.

The secondary outcomes and serious adverse event counts provide additional descriptive context, but do not supply definitive answers beyond the primary result. Secondary inferential analyses and a multiplicity plan are not reported. The safety counts do not establish causation, and death counts are not reported in the registry record.

The trial’s randomized, masked, parallel design is relevant to the intended comparison, but the registry does not describe all implementation and analysis details. The posted findings should therefore be interpreted as estimates from this trial, with uncertainty, rather than as a definitive determination of treatment effect or a guide to individual medical decisions.

17. Why This Trial Matters Statistically

This trial is statistically instructive because it reports a randomized comparison with binary outcomes and an absolute risk-difference estimate. The primary arm counts make the direction of the observed result transparent, while the confidence interval shows why a point estimate alone can be misleading. The interval includes zero and extends across differences in both directions, highlighting the distinction between an observed estimate and a precise conclusion.

The record also defines its primary endpoint using a sequence of HCV RNA measurements and explicit rules for missing results. That makes clear that endpoint interpretation is not just a matter of counting negative Week 72 tests: earlier and missing measurements are incorporated according to stated rules. Such rules can affect classification and should be considered alongside the reported counts.

The secondary outcomes illustrate another general issue: multiple endpoints can create a larger interpretive burden than a single primary comparison. Without a reported testing hierarchy or multiplicity plan, secondary results are less suited to confirmatory claims. Likewise, planning calculations based on the observed effect are examples for future design, not evidence of the study’s original planning or its achieved power.

Finally, the registry record leaves important statistical details unreported, including the original sample-size justification, the specific inferential methods, and the defined analysis population. Distinguishing what the results estimate from what the record does not document is central to a careful reading of clinical trial evidence.

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.

The registry record does not provide enough detail to reconstruct the trial’s complete statistical plan. The original sample-size justification, target effect, planned power, interim analyses, primary test, confidence-interval method, and any covariate adjustment are not reported. The sample-size illustrations based on the observed effect cannot stand in for the original design rationale.

The reported primary counts are 42 participants in each arm, but detailed participant flow and the analysis population are not described. The safety populations differ in their listed size, and the record does not explain the difference between the TCM-700C primary count and safety count. The number of missing SVR measurements and the impact of the stated missing-data rules are also not reported.

The registry identifies the study as quadruple-masked but does not say which roles were masked or how masking was maintained. The brief summary names peginterferon α-2b, whereas the intervention descriptions name peginterferon alfa-2a; the record does not resolve that discrepancy. These omissions and inconsistencies make it harder to evaluate implementation and analysis choices from the registry alone.

The available secondary outcomes do not include reported inferential analyses or a multiplicity strategy. The record also gives limited detail about serious adverse event collection and no death counts. These are limits on interpretation of the registry record, not evidence that a particular method or event was absent from the underlying study.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: The Effects of Adding TCM-700C on the Standard Combination Treatment for Patients With Genotype 1 Hepatitis C Infection — NCT00556504.
• Registry record last updated 2014-08-07; status last verified 2014-07.
• Results first posted 2014-07-08.
• 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

NCT00556504 is a completed, randomized, quadruple-masked, parallel-group phase II trial sponsored by TCM Biotech International Corp. It enrolled 84 participants with genotype 1 chronic hepatitis C and compared TCM-700C with placebo as an add-on to peginterferon and ribavirin.

The primary endpoint was sustained virologic response 24 weeks after combination treatment ended. SVR was recorded for 27 of 42 participants in the TCM-700C arm and 29 of 42 in the placebo arm. The posted risk difference was -0.048, with a 95% confidence interval from -0.249 to 0.154 and an unadjusted p-value of 0.643.

The interval leaves uncertainty about the direction and size of the difference. The registry record does not report the original sample-size rationale, detailed inferential methods, analysis population, or multiplicity plan. The endpoint’s missing-data rules are stated, but the number of affected participants and sensitivity analyses are not reported.