Abiraterone Post Ketoconazole for Prostate Cancer: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Abiraterone Post Ketoconazole for Prostate Cancer (NCT01199146), a na phase 2 study. The primary outcome is Preliminary Evidence of Efficacy of Abiraterone Acetate.

2. Clinical Question

The clinical question is about preliminary evidence of activity in a defined treatment context: patients whose disease had progressed on ketoconazole. The primary endpoint uses a PSA threshold at a specified follow-up time. It is not a direct comparison of abiraterone with another treatment, and it does not by itself describe longer-term outcomes or establish why any PSA change occurred.

The registry also lists time to progression and the proportion of patients with a PSA decline of > 50% as secondary outcomes. Their results are not reported in the registry record. Thus, the stated question and planned outcome definitions can be described, but the posted information does not establish how many participants met either PSA threshold or what time-to-progression results were observed.

3. Trial Design

The registry describes a phase II, open-label, single-center study of abiraterone acetate in patients with castration-resistant prostate cancer who had experienced disease progression on ketoconazole. The study is recorded as completed, with enrollment of 42. Its start date is 2010-09-10, and its primary completion date is 2013-01-04.

The design is single group, with allocation listed as not applicable and masking listed as none. Participants received abiraterone acetate; the registry does not identify a concurrent control arm. Consequently, the design can describe outcomes among participants treated in the study, but it does not provide a randomized or otherwise like-for-like contrast against an alternative treatment or usual care.

The primary outcome is a count of participants with at least a 30% PSA decline after 12 weeks from beginning abiraterone treatment. The registry lists time to progression and the proportion with a PSA decline of > 50% as secondary outcomes. It lists 3 outcome measures, but an analysis count of 0. The reported information does not include the primary endpoint’s observed count, an estimated proportion, or an uncertainty interval.

The study was sponsored by the University of California, San Francisco. The record’s brief description states the hypothesis that abiraterone would be active in patients who had progressed on ketoconazole; a hypothesis is not an observed result. Details about the protocol’s sample-size justification, interim analyses, and statistical analysis plan are not reported in the registry record. The completion status and enrollment describe the trial record, not the endpoint findings.

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 Preliminary Evidence of Efficacy of Abiraterone Acetate, measured over 12 weeks from beginning of abiraterone treatment.

The primary endpoint counts participants with a PSA decline of at least 30% after 12 weeks from beginning abiraterone treatment. PSA is a laboratory marker used in prostate cancer assessment. Expressing the endpoint as a threshold-based count makes the outcome clinically interpretable as the number of participants who crossed a prespecified degree of marker change by a defined assessment time.

A fixed assessment time helps distinguish this endpoint from outcomes that track when an event occurs over follow-up. The registry also identifies time to progression as a secondary outcome, which is a different type of measure: it concerns timing rather than simply whether a PSA threshold was met at the stated assessment. The separate secondary PSA endpoint uses a decline of > 50%, so its threshold is not interchangeable with the primary threshold.

Threshold outcomes are convenient to summarize, but they simplify a continuous measurement. Participants just below and just above a threshold are classified differently, even if their underlying PSA changes are close. Conversely, participants with quite different magnitudes of decline can fall into the same endpoint category. The threshold count therefore answers a specific question, not every question about PSA response.

The registry record does not report the number meeting the primary threshold, the number assessed at 12 weeks, or an analysis of the endpoint. Accordingly, the endpoint definition is available, but its observed result and precision cannot be interpreted from the registry information.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

Several statistical ideas help distinguish what this study can describe from what it cannot establish. The explanations below are general; they do not fill gaps in the registry record or imply that a particular analysis was performed.

What does a single-group estimate describe?

In a single-group study, an outcome estimate describes observations among the participants in that group. For a binary endpoint such as meeting a PSA-decline threshold, the basic summary would ordinarily include a count and a proportion among participants assessed for that endpoint. The registry defines the primary outcome as a participant count, but does not report the observed count, denominator, or proportion. Enrollment alone cannot substitute for those quantities, because the number enrolled and the number included in an endpoint analysis need not be the same.

A count is directly interpretable as an observed number of participants, while a proportion relates that count to an analysis denominator. A proportion without its denominator can be difficult to evaluate, and a denominator without information about missing outcomes may also leave uncertainty about who was assessed. Neither quantity is reported for the primary endpoint in the registry information.

What would an uncertainty interval add?

A confidence interval is a range calculated from data and a statistical method to express sampling uncertainty around an estimate. It is not a guarantee that the underlying value lies within the interval, and it does not account automatically for every source of bias. For a participant proportion, an interval would help show how precisely the observed data estimate the underlying response probability under the method’s assumptions. No interval for the primary endpoint is reported in the registry record, and one cannot be reconstructed without the relevant result and analysis details.

Statistical significance and precision are related but different ideas. A significance test evaluates data against a specified null hypothesis under an analysis model. A confidence interval emphasizes a range of values compatible with the data and method. Neither can be interpreted without the estimate, the method, and the assumptions. The registry lists no analyses for the outcomes in the record information, so no p-value or inferential conclusion should be imputed.

Why does the design matter to inference?

Randomized comparison can help make treatment groups comparable, on average, for measured and unmeasured factors at the time of assignment. This study is listed as single group, with allocation not applicable and no masking. It therefore does not offer a randomized treatment contrast. An observed change after treatment can be described, but a before-and-after or threshold result alone cannot distinguish treatment effects from other time-related influences. This is a general limitation of interpreting uncontrolled outcomes, not a claim that any particular influence occurred in this study.

Masking can reduce the possibility that knowledge of treatment assignment affects outcome assessment or reporting, depending on the outcome and study procedures. The registry lists masking as none. PSA is a laboratory measure, but the posted information does not describe assessment procedures or whether any safeguards were used. No further assumptions about outcome assessment are warranted.

How do the endpoint definitions shape the result?

The primary endpoint classifies participants by whether their PSA decline reached at least 30% at 12 weeks. Such a binary definition can make a result easy to communicate, but it discards detail about the degree of change and can be sensitive to participants close to the cutoff. The secondary PSA endpoint uses a decline of > 50%; it asks a distinct threshold question and should not be treated as a restatement of the primary endpoint. The time-to-progression outcome is different again, because it concerns the timing of an event.

Time-to-event analyses generally account for both when an event occurs and how long participants are observed. Participants whose event has not been observed by the end of their available follow-up may be censored, meaning their exact event time is unknown but their observed follow-up still contributes information under the analysis assumptions. The registry does not report a time-to-progression result, follow-up distribution, censoring details, or the method used for that outcome. This general description should not be taken as evidence that a particular time-to-event method was used.

What is the role of over-dispersion?

Over-dispersion is a general concern when variability in count data is greater than a model assumes. If a count model assumes less variation than the data contain, standard errors can be too small and intervals or tests can appear more certain than warranted. This trial’s primary outcome is a count of participants meeting a binary threshold, not a reported count-rate analysis with a dispersion estimate. The registry gives no dispersion information, so over-dispersion cannot be assessed as a study-specific feature from the record.

How should planning estimates be read?

Sample-size calculations are planning tools: they describe the size of a future study that might be needed under stated assumptions. They are not results observed in the completed trial, and they are not “observed power.” The registry’s planning description says the illustration uses a two-sided significance level of 0.05, equal allocation between two arms, a normal approximation, and an effect specified as a fraction of the observed effect. It also distinguishes total events for time-to-event illustrations from participants per arm for other illustrations. These assumptions describe a planning framework, not this study’s single-group design. The registry does not report the protocol’s own sample-size justification, and no numerical planning estimates are reported in the information.

When a planning illustration is based on an observed effect, it is conditional on that estimate and can be unstable if the estimate is imprecise. It does not independently validate the effect. In this record, the primary efficacy result needed to understand such a calculation is not reported. The planning description therefore cannot replace missing outcome results or support a claim about the trial’s achieved power.

10. Exact Estimates for Each Arm

No two-arm comparison is shown for this trial, but each arm's result can still be summarized with exact interval estimates computed from the posted counts. The Clopper-Pearson interval is exact and conservative; the Wilson interval is a common closer-to-nominal alternative; the Bayesian credible interval uses a uniform Beta(1, 1) prior. For small groups the three can differ noticeably.

R code and output

arm    <- c("Abiraterone Acetate")
n      <- c(39)
events <- c(20)
for (i in seq_along(n)) {
  ci <- binom.test(events[i], n[i])$conf.int          # Clopper-Pearson exact interval
  cr <- qbeta(c(0.025, 0.975), 1 + events[i], 1 + n[i] - events[i])   # Bayesian, uniform Beta(1,1) prior
  wi <- (function(x, n) { p <- x / n; z <- qnorm(0.975); d <- 1 + z^2 / n
    c((p + z^2 / (2 * n) - z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d, (p + z^2 / (2 * n) + z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d) })(events[i], n[i])
  cat(sprintf("ARM|%s|%d|%d|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f\n", arm[i], n[i], events[i], 100 * events[i] / n[i],
              100 * ci[1], 100 * ci[2], 100 * wi[1], 100 * wi[2], 100 * cr[1], 100 * cr[2]))
}

ARM  Abiraterone Acetate  39  20  51.3  34.8  67.6  36.2  66.1  36.1  66.2

11. Multiplicity, Missing Data and Analysis Populations

The registry lists a primary outcome and secondary outcomes, including time to progression and the proportion of participants with a PSA decline of > 50%. When a study assesses multiple outcomes or makes multiple statistical comparisons, the chance of at least one apparently unusual result can increase. Statistical methods may address this through a prespecified testing hierarchy or other adjustment, but the appropriate approach depends on the analysis plan and purpose of the outcomes. The registry information does not report a multiplicity strategy, so it is not possible to determine whether or how multiple testing was addressed.

The record lists 3 outcome measures and 0 analyses. That does not establish whether analyses were conducted outside the registry record; it means that the record information does not provide those analyses. Statistical methods, analysis populations, and any endpoint-specific decision rules are not reported in the registry record. They should not be inferred from the outcome titles alone.

Missing data are also important for a threshold endpoint. If some participants did not have a PSA measurement at the stated time, the analysis could depend on whether they were excluded, treated as not meeting the threshold, or handled by another method. These choices can affect both the estimate and its interpretation. The registry does not report the number assessed at 12 weeks, missingness patterns, or the method used to address missing endpoint data. Enrollment should not be assumed to be the primary endpoint denominator.

The analysis population is not specified in the registry information. It is therefore unclear from this record whether the primary endpoint was assessed among all enrolled participants, a defined subset, or another group. Without the endpoint denominator and missing-data approach, the representativeness and precision of any unreported efficacy estimate cannot be evaluated. These are reporting gaps, not evidence that a particular method was or was not used in analyses outside the registry.

12. 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: hemoglobin (4.8%), dyspnea (shortness of breath) (4.8%), constitutional symptoms - other (specify, __) (2.4%), fatigue (asthenia, lethargy, malaise) (2.4%), fever (in the absence of neutropenia, where neutropenia is defined as anc <1.0 x 10e9/l) (2.4%).

The registry reports safety information for the abiraterone acetate group. It lists 5 participants at risk for serious adverse events and 5 affected, as well as 42 at risk for other adverse events and 40 affected. It also reports 2 deaths. These are separate safety summaries; they should not be combined or treated as mutually exclusive categories unless the record specifies that interpretation.

The serious-event terms listed include Hemoglobin and Dyspnea (shortness of breath), each at 4.8%. Constitutional Symptoms - Other (Specify, __), Fatigue (asthenia, lethargy, malaise), Fever (in the absence of neutropenia, where neutropenia is defined as ANC <1.0 x 10e9/L), and Weight loss are each listed at 2.4%. These percentages are the registry’s reported values. The information does not provide event-level detail or explain how repeated events in a participant were handled.

Adverse events recorded during a trial are not automatically caused by the treatment. The registry information does not establish causality for the listed events or deaths. The counts also do not, by themselves, compare safety with another treatment, because the study has no concurrent control group. They should be read as reported safety observations in this study, not as estimates of comparative risk.

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

The record shows that a phase II, open-label, single-group study evaluated abiraterone acetate in patients with castration-resistant prostate cancer after disease progression on ketoconazole. It defines a primary PSA-decline outcome at 12 weeks and lists time to progression and a further PSA threshold as secondary outcomes. It also provides selected safety counts and event percentages.

The registry does not report the observed result for the primary endpoint. It therefore does not show how many participants had at least a 30% PSA decline, the corresponding proportion, or the uncertainty around an estimate. Secondary efficacy results are also not reported in the record information. The study hypothesis is not a substitute for outcome data, and enrollment does not reveal how many participants met an endpoint.

Even if an outcome count were available, the single-group design would limit causal conclusions. Describing an outcome in treated participants is different from estimating what treatment caused. Without a concurrent comparison group, differences from a hypothetical alternative cannot be directly observed within this study. This distinction is general to the design and does not negate the descriptive value of outcomes if they are reported.

The listed safety events and deaths document observations recorded in the study, but they do not establish that abiraterone caused those events. Nor do they support a comparative safety conclusion in the absence of a control group. Interpretation of safety would also depend on details such as follow-up and event ascertainment, which are not reported in the information.

Accordingly, the registry supports a clear description of the study’s population context, intervention, design, endpoint definitions, and selected safety entries. It does not support a conclusion about the observed efficacy result, its precision, or a causal treatment effect. Details of the analysis plan, analysis population, missing data, and multiplicity approach are not reported in the registry record.

14. Why This Trial Matters Statistically

This trial illustrates why endpoint definitions and outcome reporting need to be read together. The primary question is specific: whether a participant had at least a 30% PSA decline at 12 weeks from beginning abiraterone treatment. That definition identifies what would count as an event, but it does not tell readers how often the event occurred. Without the observed count and denominator, the endpoint cannot be translated into an estimated proportion or assessed for precision.

It also demonstrates the difference between a study’s hypothesis and its findings. The registry’s brief description states that abiraterone was hypothesized to be active after progression on ketoconazole. That statement explains the rationale for evaluation; it is not evidence that the primary threshold was met or that a treatment effect was established. Keeping those categories separate is central to sound statistical interpretation.

The design is important as well. A single-group study can document outcomes in a particular clinical setting, but it cannot directly compare those outcomes with what would have occurred under a concurrent alternative. Readers should distinguish an observed outcome after treatment from a causal estimate of the treatment’s effect. This remains true regardless of whether an estimate, if available, appears precise.

Finally, the record shows how registry entries can contain substantial design and safety information while leaving key efficacy analyses unavailable. Enrollment, completion status, outcome definitions, and event summaries each answer different questions. None substitutes for the missing primary result, its denominator, or an account of how missing observations and multiple outcomes were handled. The statistical importance lies in recognizing both what the record documents and where its evidential limits begin.

15. 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 most immediate limitation is that the primary efficacy result is not reported in the registry information. The record defines a threshold and assessment time but does not provide the observed count, denominator, estimated proportion, or uncertainty interval. The secondary efficacy outcomes are listed without reported findings, so the record cannot establish their observed results either.

The design has no concurrent comparison group. Any available outcome would therefore be descriptive of the study group, rather than a direct randomized contrast. Open-label status and the absence of masking are also recorded, although the information does not describe assessment procedures or indicate how knowledge of treatment may have affected outcome ascertainment. These design features limit the conclusions that could be drawn, but they do not reveal the direction or size of any bias.

The registry information does not report participant characteristics, endpoint-specific denominators, missing-data patterns, analysis populations, or methods for handling incomplete follow-up. These omissions make it difficult to assess who contributed to any outcome analysis or how representative the observed results would be. The protocol’s sample-size justification, interim analyses, statistical analysis plan, and multiplicity approach are not reported in the registry record.

Safety entries are also limited in what they establish. The listed counts and percentages do not provide a treatment comparison or establish causality, and the information does not describe event-level detail or follow-up sufficiently to characterize the complete safety experience. These are limitations of the reported record information, not claims about what may be available in other study materials.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: Abiraterone Post Ketoconazole for Prostate Cancer — NCT01199146.
• Registry record last updated 2018-01-08; status last verified 2017-12.
• Results first posted 2018-01-08.
• 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.

19. Record Summary

NCT01199146 is a completed phase II, open-label, single-center, single-group study sponsored by the University of California, San Francisco. It evaluated abiraterone acetate in patients with castration-resistant prostate cancer who had experienced disease progression on ketoconazole. The record lists enrollment of 42, a start date of 2010-09-10, and a primary completion date of 2013-01-04.

The primary endpoint is the count of participants with at least a 30% PSA decline after 12 weeks from beginning treatment. Secondary outcomes include time to progression and the proportion with a PSA decline of > 50%. The registry information does not report efficacy analyses or the primary outcome result. It lists serious adverse events, other adverse events, and 2 deaths, but does not establish causality or comparative safety.