OGX-427 in Metastatic Castrate-Resistant Prostate Cancer With Prostate-Specific Antigen Progression While Receiving Abiraterone: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for OGX-427 in Metastatic Castrate-Resistant Prostate Cancer With Prostate-Specific Antigen Progression While Receiving Abiraterone (NCT01681433), a randomized phase 2 study. The primary outcome is Progression-Free Survival.

2. Clinical Question

3. Trial Design

The registry identifies this as a randomized Phase II study with a crossover model and no masking. The study is titled the Pacific Clinical Trial and is also identified as Hoosier Oncology Group GU12-159. Its stated objective was to evaluate adding OGX-427 to continuing abiraterone acetate and prednisone in men with metastatic castrate-resistant prostate cancer and PSA progression.

Arm A received OGX-427 together with continuation of abiraterone acetate and prednisone. Arm B continued abiraterone acetate and prednisone. The posted primary outcome is a fixed-time measure: the number of participants alive without progression at Day 60 (±7 days). The record lists 36 participants in each arm for that outcome. Overall enrollment is recorded as 72.

The registry gives a study start of 2012-12 and a primary completion date of 2017-06-21. The current status is terminated; a reason for termination is not reported in the registry record. Although the model is described as crossover, the timing and procedures for any crossover, including how it relates to the Day 60 comparison, are not reported in the registry record. Further details about allocation procedures, follow-up, and the conduct of the study are also not reported in the registry record. The posted comparison is therefore best read as the recorded arm-level result for the stated primary outcome, without assuming unreported design or analysis details.

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

Reasons for not completing this period:

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 Progression-Free Survival, measured over 60 days.

The primary endpoint is the number of participants alive without progression at Day 60 (±7 days), with the stated comparison asking whether the proportion is greater in Arm A than in Arm B. The posted outcome counts are 12 in Arm A and 6 in Arm B, with 36 participants recorded in each arm for this measure.

This is a binary, fixed-time outcome: each participant is counted according to whether the specified status was observed within the stated assessment window. It is not a report of how long each participant remained progression-free, nor does it describe the timing of progression across follow-up. A fixed-time proportion can provide a direct comparison at a clinically specified assessment point, while keeping the outcome definition focused on status at that point. In general, such an endpoint is useful when the research question concerns the proportion reaching a defined status by a particular time.

The registry does not report detailed criteria for progression, the assessment schedule, how deaths or missing assessments were handled, or the endpoint analysis population. Those details matter for interpreting exactly how participants were classified. PSA Response is listed as a secondary outcome, but the posted primary comparison concerns being alive without progression at Day 60.

7. Results Posted in the Registry

• Experimental: Arm A: 33.3% (12/36) versus 16.7% (6/36) on control; risk difference 16.7 percentage points (95% CI -3.0 to 36.3), risk ratio 2.00 (0.84–4.75); unadjusted two-proportion z-test p = 0.102.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is binary: participants are counted according to whether they were observed alive without progression at Day 60 (±7 days). The registry reports a count for each arm and a risk-difference comparison. This format gives both a direct description of the observed data and an estimate of the difference between the arm-level proportions.

What does a risk difference describe?

In general, a risk difference subtracts one group's event proportion from the other group's event proportion. It expresses the comparison on an absolute scale, rather than as a ratio. For this outcome, the posted estimate is 0.167, with the direction indicating a higher observed proportion in Arm A. The estimate should be read alongside its uncertainty interval and the underlying counts. A point estimate alone does not show how precisely the comparison is known.

How should the relative measures be read?

The registry also reports a risk ratio of 2.0 and an odds ratio of 2.5. In general, a risk ratio compares proportions directly, whereas an odds ratio compares odds. These measures use different scales and can give different numerical descriptions of the same binary data. Neither measure eliminates uncertainty or establishes a causal effect. Their reported intervals include values on both sides of no relative difference, so they do not provide a precise direction of effect.

What does the p-value tell the reader?

The listed unadjusted p-value is 0.102. In general, a p-value describes how unusual data at least as inconsistent with a null model would be if that model and the test assumptions held. It is not a measure of effect size, and it does not give the probability that the null hypothesis is true. Nor does a p-value above a conventional threshold prove the absence of a meaningful effect. The registry does not report the statistical test used, the confidence-interval method, or an adjusted analysis. No additional test details should be inferred.

Why do confidence intervals matter?

In general, a confidence interval communicates uncertainty around an estimate. It gives a range of values compatible with the observed data under the interval method and its assumptions. Here, the risk-difference interval spans negative and positive values, including no difference. That means the observed estimate is not sharply separated from the possibility of no difference. The interval should not be interpreted as a range containing a fixed probability that the true effect lies within it.

What is the importance of dispersion?

This outcome is a count of participants with a binary status, not a continuous measurement or an event-rate measure. The registry reports no dispersion statistic for the arm-level counts. In general, over-dispersion matters when count data vary more than a model assumes; it can make standard errors and confidence intervals too small if ignored. That concern does not justify imposing a count model on this fixed-time binary outcome. The registry does not report model diagnostics or enough methods detail to assess such issues in its own analysis.

How should the design affect interpretation?

Randomization is intended in general to make comparison groups more comparable at the start of a trial, but it does not prevent chance imbalance or resolve missing data and outcome-assessment concerns. The registry says that this study was randomized, unmasked, and used a crossover model. It does not report randomization procedures, masking was absent, or crossover details. Because the primary outcome is stated for a fixed assessment point, the registry's missing explanation of how crossover relates to the endpoint is an important limitation when interpreting the comparison.

The registry lists no analysis entries, while a comparison with an unadjusted p-value and effect estimates is posted. The detailed statistical plan, analysis population, missing-data procedures, and any adjustments are not reported in the registry record. Accordingly, the posted estimates can be described, but the analysis cannot be fully reproduced or evaluated from the record alone.

10. Confidence Intervals and Precision

The risk-difference estimate is 0.167, and its confidence interval extends from a negative value to a positive value. Because zero lies within that interval, the data do not pin down the direction of the risk difference with precision. The interval is compatible with a lower proportion in Arm A as well as a higher proportion, including no difference. This uncertainty is important even though the observed counts are 12 of 36 in Arm A and 6 of 36 in Arm B.

The reported risk ratio is 2.0 and odds ratio is 2.5, but their confidence intervals are broad and include values on either side of no relative difference. These relative measures provide another description of the comparison, not independent confirmation of a treatment effect. The unadjusted p-value of 0.102 likewise does not quantify the size or practical importance of an effect.

In general, an interval is wider when the data provide less precise information and narrower when they provide more, subject to the method and assumptions used. The registry does not state the confidence-interval method or report enough analysis details to assess its assumptions. As a result, the interval is useful for conveying uncertainty, but the record does not support a more detailed assessment of its construction. The fixed-time counts also do not convey uncertainty about outcomes at other times or the full progression-free survival experience.

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 sample-size figures are planning illustrations expressed as participants per arm, not total events. They use the observed effect as a starting point and show planning for 100%, 75%, and 50% of that observed effect. For the 80% power column, the listed participants per arm are 105, 177, and 372, respectively. For the 90% power column, they are 140, 236, and 498, respectively.

In plain language, 80% power means that, under the stated planning assumptions and if the effect being planned for were the true effect, the design would have an 80% chance of detecting an effect at the stated significance level. The 90% column describes a corresponding 90% chance under those assumptions. These are not guarantees for any particular study. This is not observed power.

The stated 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. Smaller effects need more participants to be detected with the same planned power, which is why the required participants per arm rise as the assumed fraction decreases. The registry's own original sample-size assumptions and justification are not reported in the registry record; these calculations are separate planning illustrations based on the observed effect, not a reconstruction of the trial's 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 = 0.167; treatment proportion p₁ = 0.333; average p̄ = 0.250.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6124 = 1.2002.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6009 = 0.5058.
4. n = (1.2002 + 0.5058)² / (0.1667)² = 104.8, rounded up to 105 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 <- 0.166666666666667                          # control proportion
p1 <- 0.333333333333333                          # 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(1681433)
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 = 105 (80% power), 140 (90% power)
 75% of observed effect: n per arm = 177 (80% power), 236 (90% power)
 50% of observed effect: n per arm = 372 (80% power), 498 (90% power)
power.prop.test: 104.8 
Simulated power at n = 105 per arm: 0.805 (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. Multiplicity, Missing Data and Analysis Populations

The registry lists PSA Response as a secondary outcome and indicates one secondary outcome is posted. It also records 7 outcome measures and no analysis entries. The primary comparison has an unadjusted p-value, but the record does not report a multiplicity strategy, a hierarchy of outcomes, or a prespecified approach to interpreting several statistical tests. When multiple outcomes or analyses are examined, the chance of at least one apparently unusual result can increase; in general, multiplicity procedures are used to address that issue. No adjustment should be assumed for this result.

Missing-data handling is not reported in the registry record. The record does not state whether all randomized participants had an assessment at Day 60, how unavailable assessments were classified, or whether any imputation or sensitivity analysis was used. These details can affect the interpretation of a fixed-time proportion. The posted endpoint counts and denominators describe the recorded comparison, but they do not explain whether those data include every participant assigned to each arm.

The analysis population is also not reported in the registry record. It is therefore not possible to determine from the record whether the comparison followed an intention-to-treat principle, included only participants meeting other criteria, or used another population definition. The registry's crossover designation adds a further unanswered question: the record does not explain how any crossover was accounted for in the primary analysis.

The registry does not report interim analyses, stopping boundaries, or detailed statistical-plan procedures. These omissions do not establish that such procedures were or were not used; they mean the record does not document them. The result should therefore be interpreted as the posted unadjusted comparison, without attributing unreported choices about missing data, analysis populations, or multiplicity.

14. Safety Results

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

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 0% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: dehydration (5.6%), infections and infestations (5.4%), hematuria (3.6%), urinary retention (3.6%), generalized muscle weakness (2.8%).

The registry reports serious adverse events for Arm A among 56 participants at risk, with 12 affected, and for Arm B among 36 participants at risk, with 6 affected. Other adverse events are reported for 56 participants at risk in Arm A, with 51 affected, and 36 at risk in Arm B, with 32 affected. Deaths are reported as 8 in Arm A and 6 in Arm B. These are descriptive counts; the record does not provide an adjusted comparison or enough context to attribute events to a treatment.

The serious-event denominators do not match the 36 participants listed in each arm for the primary outcome. The registry does not explain this difference, so the safety counts should be read using their stated at-risk denominators rather than treated as if they were the primary-outcome denominators. The record does not describe follow-up duration or detailed event-collection procedures.

Reported serious-event terms include dehydration (5.6%), infections and infestations (5.4%), hematuria (3.6%), urinary retention (3.6%), generalized muscle weakness (2.8%), and anemia (2.8%). The denominator for these term percentages is not reported in the registry record. The listed terms and counts do not establish comparative safety or causality.

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

The posted result describes a higher observed proportion alive without progression at Day 60 in Arm A than in Arm B: 12 of 36 compared with 6 of 36. The unadjusted risk-difference estimate is 0.167, and the unadjusted p-value is 0.102. The confidence interval for the risk difference includes no difference and values in both directions. Taken together, these statistics describe an uncertain arm comparison, not a definitive treatment effect.

The result does not show that OGX-427 works or does not work. A point estimate reflects the observed data, while the interval communicates that a range of underlying effects remains compatible with those data. The p-value is not the probability that the treatments are the same and does not establish whether a difference is clinically important.

The endpoint is status at Day 60 (±7 days), not the full time-to-progression history. The registry does not provide detailed progression criteria, missing-data methods, an analysis-population definition, or an explanation of how the crossover model affected the primary comparison. It also does not report the reason for termination. These limitations restrict interpretation beyond the posted fixed-time result.

The safety counts are also descriptive and use at-risk denominators that differ between arms and from the primary-outcome denominators. The registry does not explain those differences or provide an adjusted safety comparison. The counts and reported event terms therefore should not be treated as proof of a causal safety effect. Overall, the record supports describing what was observed and the uncertainty around the primary comparison, but not a stronger conclusion about benefit or harm.

16. Why This Trial Matters Statistically

This study illustrates a common statistical challenge in clinical research: a randomized comparison can produce a visibly different set of observed counts while still leaving substantial uncertainty about the underlying effect. The primary outcome counts are 12 of 36 in Arm A and 6 of 36 in Arm B, but the risk-difference confidence interval includes no difference and values in either direction. Interpreting the point estimate without its interval would overstate how precisely the comparison is known.

It also shows why endpoint definition matters. The primary outcome asks about the proportion alive without progression at Day 60 (±7 days), which is a fixed-time status. That question is distinct from asking how long participants remained progression-free over follow-up. Although the registry describes a crossover model, the posted record does not explain how crossover relates to this fixed-time result. Statistical interpretation depends on understanding not only the numerical estimate but also which participants and observations it represents.

Finally, this record highlights the importance of complete analysis reporting. The comparison includes an unadjusted p-value, but details about missing data, analysis populations, multiplicity, and the original sample-size rationale are not reported in the registry record. Safety denominators also differ from the primary-outcome denominators without explanation. Such reporting gaps do not invalidate the posted counts, but they limit reproducibility and constrain the conclusions that readers can draw. The appropriate statistical reading keeps the observed result, its uncertainty, and the unavailable context distinct.

17. 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 leaves several trial-specific questions unanswered. It identifies the study as randomized, unmasked, and crossover, but does not describe randomization procedures, crossover timing, or how crossover was handled in the primary analysis. The primary outcome is defined as participants alive without progression at Day 60 (±7 days), but detailed progression criteria, assessment procedures, and handling of deaths or unavailable assessments are not reported in the registry record.

The record does not define the analysis population or state how missing outcome data were handled. It does not report the statistical test or confidence-interval method, a multiplicity plan, interim analyses, or the original sample-size justification. The posted comparison is unadjusted. The study is listed as terminated, but the reason for termination is not reported in the registry record.

There is also a denominator difference between the primary outcome and safety reporting: each arm has 36 participants recorded for the primary outcome, while the serious and other adverse-event at-risk counts are 56 for Arm A and 36 for Arm B. The registry does not explain why these safety denominators differ. The denominator for the reported serious-event term percentages is also not reported. These features make it important to interpret the safety summaries according to their stated counts and not assume they use the same analysis population as the primary outcome.

These limitations do not change the posted numbers, but they constrain reproducibility and the scope of interpretation. They do not establish that any unreported procedure was absent; they indicate that it is not documented in the registry record.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: OGX-427 in Metastatic Castrate-Resistant Prostate Cancer With Prostate-Specific Antigen Progression While Receiving Abiraterone — NCT01681433.
• Registry record last updated 2022-07-11; status last verified 2022-07.
• Results first posted 2018-10-18.
• 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.

21. Record Summary

The registry describes NCT01681433 as a randomized, unmasked Phase II crossover study of OGX-427 added to continued abiraterone acetate and prednisone in men with metastatic castrate-resistant prostate cancer and PSA progression. Arm A added OGX-427; Arm B continued abiraterone acetate and prednisone. The primary outcome was the proportion alive without progression at Day 60 (±7 days).

The posted counts are 12 of 36 in Arm A and 6 of 36 in Arm B. The unadjusted risk-difference estimate is 0.167, with an unadjusted p-value of 0.102 and a confidence interval spanning negative and positive values. The registry status is terminated, and the reason is not reported in the registry record. Key analysis details, including missing-data handling, analysis population, and crossover procedures, are not reported.