The SIM-SOF Trial for Hepatitis C: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for The SIM-SOF Trial for Hepatitis C (NCT02168361), a randomized phase 4 study. The primary outcome is Proportion of Participants With Sustained Virologic Response 12 (SVR-12).

2. Clinical Question

This was a randomized comparison, but masking was none. The outcome is a binary response: each participant either met the registry’s response definition or did not. The posted counts are 54 of 58 for the all-oral arm and 18 of 24 for the interferon-containing arm. Those are the observed outcome counts, not a guarantee that the same proportions would occur in another group of patients.

The clinical question is therefore specific to these regimens, this population, and the stated post-therapy assessment. It does not by itself answer questions about other hepatitis C genotypes, other patient groups, other treatment durations, or outcomes beyond the registry’s reported measures.

3. Trial Design

The registry identifies this as a phase 4 randomized trial with a parallel-group design. Participants were assigned to the all-oral simeprevir-plus-sofosbuvir regimen or the peginterferon/ribavirin/sofosbuvir regimen. Masking was none, so the trial was open-label according to the registry record. Enrollment is listed as 93.

The regimens were each described as lasting 12 weeks. The registry’s study start is listed as 2013-12, and primary completion as 2014-12; the trial status is completed. The sponsor is the Center For Hepatitis C, Atlanta, GA. These administrative details describe the record but do not establish how randomization was generated, concealed, or implemented. Those details are not reported in the registry record.

The primary endpoint was assessed 12 weeks post-therapy. The primary-outcome population is defined as participants who received at least a single dose of medication. The posted arm counts for this outcome are 58 in the all-oral arm and 24 in the interferon-containing arm. The relationship between those outcome counts and the enrollment figure is not explained in the registry record; participant flow and the number assigned to each arm are not reported there.

The registry lists serum HCV RNA level as a secondary outcome and reports two outcome measures and one analysis. It does not report a detailed protocol, the method used to assign participants, the planned sample-size justification, or the trial’s original statistical analysis plan. Consequently, the design can be described from the registered characteristics, but further procedural details should not be inferred.

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

Analysis population for the primary outcome, as defined in the registry: All participants that received at least a single dose of medication

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.

Population: All participants that received at least a single dose of medication

6. Primary Endpoint

The registry lists the primary outcome as Proportion of Participants With Sustained Virologic Response 12 (SVR-12), measured over 12 weeks post-therapy.

The primary endpoint is the proportion of participants with sustained virologic response 12, assessed 12 weeks after therapy. The registry defines a response as undetectable virus in serum using a sensitive nucleic acid test at 3 months post-therapy. The result is binary at the participant level: the recorded outcome is whether each person met that definition.

A virologic endpoint gives a direct measure of whether virus was detectable at the specified assessment. Using a defined laboratory threshold and a stated follow-up time makes the outcome more reproducible than an undefined judgment of improvement. The timing matters: this endpoint describes status at the registry’s post-therapy assessment, not a measurement at the end of treatment or a guarantee about later status.

The endpoint is reported as counts of participants meeting the response definition: 54 in the all-oral arm and 18 in the interferon-containing arm. Their respective arm sizes are 58 and 24. The registry identifies the analysis population as everyone who received at least a single dose of medication, but does not provide further detail about how missing endpoint measurements were handled.

This endpoint does not, on its own, summarize safety, quality of life, or longer-term clinical outcomes. Serum HCV RNA level is listed as a secondary outcome, but numerical results for that measure are not reported in the registry record.

7. Results Posted in the Registry

• Interferon-containing Arm: 75.0% (18/24) versus 93.1% (54/58) on control; risk difference -18.1 percentage points (95% CI -36.6 to 0.4), risk ratio 0.81 (0.63–1.03); unadjusted two-proportion z-test p = 0.023.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is binary because each participant either had an undetectable serum virus result at the defined assessment or did not. For binary outcomes, the basic summaries are the number of participants with the event and the number assessed in each arm. In this trial, the event is sustained virologic response. The posted counts are 54 of 58 for all-oral therapy and 18 of 24 for the interferon-containing arm.

What does the risk difference describe?

The risk difference subtracts one arm’s event proportion from the other’s, with the sign depending on the comparison order. The reported comparison is the interferon-containing arm against the all-oral arm, and the estimated risk difference is -0.181. Because response is the event, this negative estimate describes a lower observed response proportion in the interferon-containing arm. The estimate is an absolute difference in proportions, rather than a relative comparison.

Absolute differences can be useful because they retain the scale of the event proportions. However, the estimate alone does not show how stable the result is across possible samples. It needs to be read with its confidence interval and the design limitations. The arm ordering must also be kept clear: changing the order reverses the sign but does not change the underlying comparison.

What does a confidence interval add?

A confidence interval describes statistical uncertainty around an estimate under the method’s assumptions. In repeated use of the same procedure, intervals constructed in this way have a stated coverage property. It is not a probability statement that the particular interval contains the true effect after the data have been observed. For this risk difference, the interval extends from a negative value to a positive value and includes zero. This means the posted interval is compatible with no difference as well as with values on either side of zero. Its width also indicates that the estimated difference is not highly precise.

The record also includes relative measures, a risk ratio and an odds ratio, each with an interval. Relative measures compare event occurrence on a ratio scale rather than a difference scale. The odds ratio compares the odds of response; the risk ratio compares the response proportions. These measures can look numerically different from an absolute difference because they use different scales. The additional measures do not change the underlying observed counts, and their interpretation depends on keeping the event and arm order in view.

How should a p-value be read?

The registry reports a Chi-squared test with p = .02. The unadjusted recalculation reports p = 0.023. A p-value is calculated under a model that specifies no association or difference and describes how unusual data at least as discrepant as those observed would be under that model. It does not give the probability that the null hypothesis is true. It also does not measure the size or importance of the observed difference.

Different procedures can yield different inferential summaries because they may use different statistics or assumptions. The record identifies the sponsor-reported procedure as Chi-squared, while the recalculated comparison is an unadjusted calculation from the posted summary statistics. The registry does not provide a fuller account of the sponsor’s implementation or the recalculation procedure beyond the reported summaries. The interval and p-values should therefore be treated as separate statistical descriptions, rather than forced into a single conclusion.

Why does over-dispersion matter?

Over-dispersion is a general issue in models for count or binary data when observed variability is greater than the model expects. A model that ignores extra variability can make standard errors too small and intervals too narrow. This endpoint is posted as a binary participant outcome, and the registry reports a Chi-squared analysis. It does not report an over-dispersion assessment or a model designed to account for it. Over-dispersion should not be assumed to have been present or absent in this trial.

What can be said about adjustment and analysis populations?

The primary outcome population is stated as participants who received at least one dose. That definition does not establish whether all randomized participants were included, how any missing endpoint values were treated, or whether the analysis was intention-to-treat. Those details are not reported in the registry record. The record also does not report adjusted estimates or covariates used in an adjusted model. Accordingly, the recalculated result is an unadjusted comparison of the posted summaries; it cannot account for unreported participant-level information.

These methods are useful for describing the observed result, but they do not eliminate uncertainty or limitations in the record. Statistical interpretation depends on the endpoint definition, the analyzed population, the comparison direction, and the assumptions behind the method. The posted counts and estimates should be read together with the open-label design and the missing detail about participant flow and missing outcomes.

10. Confidence Intervals and Precision

The risk-difference estimate is -0.181 for the comparison of the interferon-containing arm with the all-oral arm. Its confidence interval runs from a negative endpoint to a positive endpoint and includes zero. This is important because the data are compatible, under the interval method, with no difference as well as with a range of possible differences in either direction. The interval therefore does not support treating the point estimate as exact.

Precision is about the uncertainty around an estimate, not whether the estimate is clinically important. A narrower interval would indicate greater statistical precision under the same method; a wider interval indicates more uncertainty. The arm counts are 58 and 24, and the interval reaches across zero, illustrating that the observed point estimate should be interpreted with caution. No additional precision can be inferred from the point estimate alone.

The registry also provides risk-ratio and odds-ratio estimates with confidence intervals. These relative measures express the comparison on scales different from the risk difference. Each interval represents uncertainty for its own measure, so their endpoints should not be compared directly with the risk-difference interval. Together, these analyses describe the same underlying outcome from different statistical perspectives, but none removes uncertainty in the posted data.

The registry-reported Chi-squared p-value and the recalculated p-value are not substitutes for an interval. A p-value condenses evidence under a specified test, whereas an interval displays a range of effect values compatible with the data under a procedure. Because the risk-difference interval includes zero, the interval and p-value summaries do not give identical threshold-based impressions. The registry does not report enough detail to reconcile their methods fully.

11. 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, not total events. They are illustrations based on the observed effect, not the trial’s original design assumptions. The record lists a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set as a stated fraction of the observed effect. The original trial’s sample-size justification and design assumptions are not reported in the registry record.

For planning at 100% of the observed effect, the figures are 64 participants per arm for 80% power and 84 participants per arm for 90% power. Planning for 75% of the observed effect gives 100 participants per arm for 80% power and 133 for 90% power. Planning for 50% of the observed effect gives 193 participants per arm for 80% power and 258 for 90% power.

In plain terms, power is the chance that a planned study would detect an effect of the specified size if that effect were present, under the assumptions used in the calculation. The 80% and 90% columns describe two different target chances of detection; aiming for the higher target requires more participants in these calculations. Smaller effects also need more participants to distinguish them from random variation. These figures are not observed power.

The calculations use an effect derived from the observed comparison, so they should be treated as planning illustrations rather than as a prospective justification for this trial. They do not establish what the investigators planned, whether they conducted interim analyses, or whether the assumptions were considered appropriate for the original design.

12. 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 = 0.931; treatment proportion p₁ = 0.750; average p̄ = 0.841.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.5178 = 1.0148.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.5017 = 0.4222.
4. n = (1.0148 + 0.4222)² / (-0.1810)² = 63.0, rounded up to 64 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 <- 0.931034482758621                          # control proportion
p1 <- 0.75                          # 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(2168361)
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 = 64 (80% power), 84 (90% power)
 75% of observed effect: n per arm = 100 (80% power), 133 (90% power)
 50% of observed effect: n per arm = 193 (80% power), 258 (90% power)
power.prop.test: 63 
Simulated power at n = 64 per arm: 0.818 (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.

13. Analyses Reported by the Sponsor

The registry’s reported analysis compares the two outcome groups using a Chi-squared test and gives p = .02. The simple unadjusted recalculation from the posted summary statistics gives p = 0.023, alongside a risk-difference estimate of -0.181. These numbers are close, but they are not identical outputs: one is identified as the registry-reported Chi-squared result, and the other is a recalculation using the posted summaries.

The registry does not identify a discrepancy between its reported analysis and the recalculation. The sponsor-reported result should be understood as the analysis recorded for the trial; the recalculation is a supplementary, unadjusted way to inspect the posted counts. It does not replace the trial’s own analysis or provide a more complete analysis than participant-level data would allow.

The p-values alone do not explain the estimated size or uncertainty of the difference. The risk-difference interval includes zero, while the reported p-values are close to one another. Because full details of the sponsor’s statistical implementation are not reported in the registry record, the two inferential summaries cannot be reconciled beyond noting their values and methods as recorded.

14. Multiplicity, Missing Data and Analysis Populations

The registry lists one secondary outcome, serum HCV RNA level. It reports two outcome measures and one analysis, but does not provide a complete statistical analysis plan or specify a multiplicity adjustment. Multiplicity arises when several outcomes, time points, or comparisons are tested: the chance of at least one apparently unusual result can increase as the number of tests grows. That general concern cannot be quantified for this trial from the registry entry alone.

The primary endpoint is sustained virologic response 12, assessed 12 weeks post-therapy. The record does not explain whether any other endpoints or analyses were planned but not posted, or whether any adjustment for multiple testing was used. It is therefore not possible to determine from the record how the reported primary result fits into a prespecified hierarchy of outcomes or tests.

The primary-outcome population is defined as all participants who received at least a single dose of medication. The registry does not report the number randomized to each arm, a participant-flow account, the number with missing endpoint measurements, or the handling of missing data. The relationship between the enrollment figure of 93 and the arm-specific endpoint counts is not explained. No conclusion about the cause of that difference should be inferred.

The record also does not state whether the analysis followed intention-to-treat principles, whether participants were analyzed according to assigned regimen, or whether any participants were excluded after treatment began. Those are important distinctions in a randomized trial because the analysis population can affect the meaning of the comparison. The stated dose-based population is the available definition; further details are not reported in the registry record.

There is no reported information about interim analyses, stopping rules, or changes to the planned analysis. Their presence or absence should not be assumed. These omissions limit assessment of selective reporting, missing-data bias, and the full set of statistical decisions behind the posted result.

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: liver decompensation (4.2%).

The registry reports serious adverse events for 0 of 58 participants in the all-oral group and 1 of 24 in the interferon-containing group. It also reports other adverse events for 46 of 58 in the all-oral group and 22 of 24 in the interferon-containing group. These are counts within the groups recorded for safety; they should not be conflated with the primary efficacy outcome.

The listed top serious adverse-event term is liver decompensation, with a reported value of 4.2%. The registry does not specify in this summary how that term relates to individual participants or whether the term represents all serious events. The deaths field has no reported count, so deaths are not reported in the registry record.

These figures are descriptive. They do not establish that one regimen caused more or fewer adverse events, and they do not account for differences in exposure, follow-up, or event ascertainment. The open-label design and the limited safety detail in the registry are relevant when interpreting these counts. No comparative safety conclusion should be drawn from these figures alone.

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

The posted primary-outcome counts show that sustained virologic response was recorded for 54 of 58 participants in the all-oral arm and 18 of 24 in the interferon-containing arm. The reported risk difference is -0.181 when the interferon-containing arm is compared with the all-oral arm. This describes the observed contrast in the posted data; it is not a statement that the same result will occur in other populations or settings.

The uncertainty matters. The risk-difference confidence interval includes zero and spans values on both sides of it. The point estimate therefore should not be treated as a precise estimate of the underlying difference. The registry-reported p-value is .02, and the unadjusted recalculated p-value is 0.023; neither p-value tells how likely it is that a treatment effect is true or how important the observed difference is.

The result is tied to the registry’s response definition, the assessment 12 weeks post-therapy, and the participants included in the stated outcome population. It does not establish outcomes beyond that assessment. The registry lists serum HCV RNA level as a secondary outcome, but its numerical result is not reported in the registry record.

The trial was randomized, but it was unmasked. Randomization is a design feature intended to support fair comparison, while lack of masking can influence behavior, care, or outcome assessment in some settings. The record does not provide enough detail to assess those possibilities. Likewise, the absence of participant-flow and missing-data details limits assessment of how the posted analysis represents all randomized participants.

These results should not be generalized automatically to other hepatitis C genotypes, treatment combinations, treatment durations, or patient groups. The registry’s description focuses on genotype 1a infection with cirrhosis in its official title and genotype 1 infection with compensated cirrhosis in its brief summary. The statistical finding is evidence about this recorded comparison, not a universal treatment recommendation or a complete account of benefits and harms.

17. Why This Trial Matters Statistically

This trial offers a useful example of why a binary endpoint needs more than an event count or a p-value. The response counts describe what was observed in each arm, the risk difference expresses the absolute contrast, and the confidence interval communicates uncertainty around that contrast. Reading these summaries together gives a more complete statistical picture than relying on any single number.

It also demonstrates that different inferential summaries may not align neatly. The sponsor-reported Chi-squared p-value is .02, while the simple unadjusted recalculation gives p = 0.023 and a risk-difference interval that includes zero. This is a reason to examine the measure, method, and uncertainty rather than treating a threshold-based conclusion as the whole result. The record does not provide all details needed to reconcile the methods more fully.

The comparison is randomized but open-label, and the reported endpoint population is based on receipt of at least one dose. Incomplete information about participant flow, missing outcomes, multiplicity, and the original analysis plan limits what can be inferred about the robustness of the result. These are not minor statistical decorations: they help define what population and question the estimate actually represents.

Finally, planning illustrations derived from an observed effect are not a substitute for a prospective sample-size rationale. Their value is to show how the required participant count changes with the target effect and power assumptions, not to establish the adequacy of the trial’s original design. Clear separation of observed results, recalculated summaries, and planning scenarios is essential for sound interpretation.

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 gives limited information about the trial’s conduct and analysis. It states that the study was randomized and open-label, but does not report the randomization method, allocation concealment, or details of the analysis plan. The sample-size justification and original design assumptions are also not reported in the registry record.

The enrollment figure is 93, while the primary-outcome arm counts are 58 and 24. The record does not explain participant flow or the relationship between these figures. It also does not report how many endpoint values were missing or how missing observations were handled. The stated primary population includes people who received at least one dose, but that definition alone does not establish whether the analysis followed intention-to-treat principles.

The study was unmasked, which may matter for behavior, co-interventions, and the assessment of outcomes. The primary outcome uses a laboratory definition, but the registry does not provide further information about assessment procedures or quality control. The record lists serum HCV RNA level as a secondary outcome without posting its numerical results.

The record reports a Chi-squared p-value and a recalculated unadjusted p-value, but gives limited detail about the statistical implementation. The risk-difference interval includes zero, while the reported p-values are close to each other. Without a fuller analysis plan and participant-level data, the statistical summaries cannot resolve all questions about uncertainty, analytic choices, and missing information.

Safety information is also limited: serious and other adverse-event counts are reported, and liver decompensation is listed as a top serious term, but deaths have no reported count. The record does not provide enough detail to assess exposure-adjusted event rates, duration of safety follow-up, or the comparative meaning of these counts. These limitations narrow the conclusions that can be drawn from the registry record.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: The SIM-SOF Trial for Hepatitis C — NCT02168361.
• Registry record last updated 2016-03-14; status last verified 2016-03.
• Results first posted 2016-03-04.
• 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

NCT02168361 is a completed phase 4 randomized, parallel-group, open-label trial comparing simeprevir plus sofosbuvir with peginterferon, ribavirin, and sofosbuvir. Both regimens were described as lasting 12 weeks. The official title identifies chronic hepatitis C genotype 1a infection with cirrhosis; the brief summary describes genotype 1 infection with compensated cirrhosis.

The primary endpoint was sustained virologic response 12 weeks post-therapy, defined as undetectable serum virus using a sensitive nucleic acid test. The posted counts were 54 of 58 in the all-oral arm and 18 of 24 in the interferon-containing arm. The reported risk difference was -0.181, with a confidence interval that includes zero. The registry reports a Chi-squared p-value of .02; an unadjusted recalculation gives p = 0.023.

Participant flow, missing-data handling, multiplicity procedures, and the original sample-size rationale are not reported in the registry record. The available results describe this registered comparison and should be interpreted with those limitations in mind.