Trial in Locally Advanced and Metastatic Adrenocortical Carcinoma Treatment (FIRM-ACT): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Trial in Locally Advanced and Metastatic Adrenocortical Carcinoma Treatment (FIRM-ACT) (NCT00094497), a randomized phase 3 study. The primary outcome is Overall Survival.

2. Clinical Question

The question is clinically framed around survival, but the registry outcome values are death counts by randomized arm rather than reported survival times. Those counts allow a comparison of the recorded proportion who died in each arm, but do not by themselves show when deaths occurred or how long participants lived. The registry record does not report a hazard ratio, median survival, or a time-to-event analysis result.

The trial also lists progression-free survival, change in quality of life measured by QLQ-C30, best overall response rate, and number of disease-free patients as secondary outcomes. Numerical details are posted for quality-of-life change and disease-free participants. The record does not report numerical results for progression-free survival or best overall response rate in the available outcome details.

3. Trial Design

FIRM-ACT is recorded as a phase 3, randomized, parallel-group trial with no masking. The registry lists an enrollment of 304 participants. The study compared two first-line regimens: EDP-M, comprising etoposide, doxorubicin, cisplatin and mitotane, and Sz-M, comprising streptozotocin and mitotane. The population was patients with advanced adrenocortical carcinoma whose disease was not amenable to complete surgical resection.

The primary outcome is titled overall survival, and its description counts participants who died among those randomized to first-line therapy. The timeframe says that outcomes were recorded every 8 weeks until death, up to 5 years. This description specifies repeated follow-up timing and a maximum follow-up horizon, but the posted arm results are counts rather than survival-time summaries. The registry record does not report the detailed follow-up procedures, censoring rules, or a time-to-event analysis result.

The record lists a sponsor, the Collaborative Group for Adrenocortical Carcinoma Treatment, and marks the study as completed. The recorded start is 2004-06 and primary completion is 2010-12. The registry record does not report the original sample-size justification, detailed eligibility criteria, treatment schedules, adherence information, allocation concealment, or a full protocol statistical plan. Randomization and the parallel design are recorded, but further implementation details should not be inferred from those labels.

Because masking is listed as none, the record describes an unmasked trial. That is relevant when considering outcomes that may be affected by assessment or reporting, such as quality of life or response classification. It does not, by itself, establish that assessment was biased. The registry record does not describe any safeguards or blinded outcome assessment.

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 Overall Survival, measured over every 8 weeks until death up to 5 years.

The primary outcome is titled overall survival. The registry defines its reported value as the number of participants who died among those randomized to first-line therapy. Follow-up was recorded every 8 weeks until death, up to 5 years. In the posted results, 108 of 151 participants in the EDP-M arm and 124 of 153 in the Sz-M arm were recorded as having died.

Survival is often used in clinical trials because it is a direct outcome that can be understood as the time participants remain alive. General statistical context: a time-to-event analysis can use both the timing of an event and information from participants who have not yet had the event by the end of observation. That differs from comparing simple event counts, which does not describe the timing of deaths. The registry record gives death counts for this primary outcome but does not report survival curves, median survival, a hazard ratio, or the details of a time-to-event analysis.

Consequently, these counts support a comparison of the recorded deaths in the two randomized groups, but they cannot establish how survival times were distributed or whether a difference in timing was present. The outcome title and the form of the posted data should both be kept in view when interpreting the result.

7. Results Posted in the Registry

• Sz-M: 81.0% (124/153) versus 71.5% (108/151) on control; risk difference 9.5 percentage points (95% CI 0.0 to 19.0), risk ratio 1.13 (1.00–1.29); unadjusted two-proportion z-test p = 0.051.

8. Secondary Efficacy Endpoints

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

Change in Quality of Life as Measured by QLQ-C30

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Sz-M: mean -7.70 versus -6.00 on control; difference -1.70 (95% CI -11.39 to 7.99), standardized effect d = -0.07; z-test p = 0.731.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Sz-M and the control. The interval gives the range of effects that remain compatible with the data.

Number of Disease-free Patients

• 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:
  • Sz-M: 2.0% (3/153) versus 4.0% (6/151) on control; risk difference -2.0 percentage points (95% CI -5.8 to 1.8), risk ratio 0.49 (0.13–1.94); unadjusted two-proportion z-test p = 0.301.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Sz-M and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes broaden the questions beyond the primary death-count comparison. The registry lists progression-free survival, change in QLQ-C30 quality of life, best overall response rate, and number of disease-free participants. Numerical summaries are posted for quality-of-life change and disease-free participants, while the record does not include numerical results for progression-free survival or best overall response rate among the detailed outcome results available.

The quality-of-life summary is based on a subset of participants and its unadjusted comparison is imprecise, with an interval spanning both directions of difference. The disease-free outcome records few participants in each arm, and its interval also includes no difference. These secondary summaries do not establish a clear pattern that independently confirms or overturns the primary death-count comparison. Nor can a count of disease-free participants be treated as equivalent to a time-to-progression analysis.

Secondary outcomes can help characterize different aspects of a trial, but they answer distinct questions and may involve different measurement processes and participant availability. Their relationship to the primary result is therefore contextual rather than confirmatory. In particular, quality of life is a different type of outcome from death, and disease-free participant counts do not supply the missing event timing for the primary survival question.

The registry record does not report a multiplicity adjustment or a prespecified hierarchy for secondary outcomes. General statistical context: when several outcomes are examined, the chance of at least one apparently unusual result can increase unless the analysis plan accounts for the number and structure of comparisons. Unadjusted secondary p-values should therefore carry less weight than a prespecified primary analysis, especially when their analysis populations and missing-data handling are not described. The registry lists no reported secondary analyses, so the displayed summaries should be read as limited descriptive and unadjusted evidence.

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

• Progression-free Survival
• Change in Quality of Life as Measured by QLQ-C30
• Best Overall Response Rate
• Number of Disease-free Patients

9. Statistical Interpretation

10. Statistical Methods Explained

The registry identifies a randomized, parallel-group comparison and posts outcome counts for each arm. The comparisons described in this statistical interpretation are unadjusted comparisons calculated from those posted summaries. The registry record lists 0 reported analyses, so no sponsor-reported analysis result or model specification is available in this record. The original statistical plan, including its test choices and prespecified analysis populations, is not reported in the registry record.

What does a risk difference express?

For a binary outcome such as whether a participant died during the recorded follow-up, a risk difference compares the event proportions in two groups by subtraction. The posted comparison is oriented as Sz-M relative to EDP-M. Its positive estimate indicates a higher recorded event proportion in Sz-M. The risk difference is expressed on the proportion scale; it does not describe the relative increase in risk, and it does not convey when the events occurred.

A risk ratio instead expresses one group’s event proportion relative to the other group’s proportion. An odds ratio compares the odds of the event between groups. These measures describe different scales and can have different numerical values, even when based on the same event counts. The registry includes relative measures for the primary outcome, but their bounds include values near the no-difference value. A relative measure should not be mistaken for an absolute difference or for a survival-time effect.

What does an unadjusted comparison mean?

An unadjusted comparison uses the posted arm summaries without accounting for additional participant characteristics or other covariates. It is a straightforward description of the observed between-arm contrast. Randomization is intended to support fair group comparisons, but an unadjusted estimate remains subject to sampling variability. The registry record does not report covariate adjustment, stratification factors, or an adjusted analysis for the primary outcome.

The p-value reported for the primary comparison is unadjusted. General statistical context: a p-value describes how unusual data at least as incompatible with a specified null hypothesis would be under the assumptions of a test. It is not the probability that the null hypothesis is true, and it is not a measure of the size or importance of the estimated difference. The registry record does not report the precise test procedure, so the p-value should be read as the unadjusted value posted with the comparison rather than attributed to an unreported model.

Why are confidence intervals useful?

A confidence interval gives a range of values compatible with the data under the method used to calculate it. It communicates uncertainty about the estimated contrast, rather than reducing interpretation to a single estimate. A narrow interval would indicate greater precision than a wide interval on the same scale. General statistical context: an interval that includes the no-difference value is compatible with both directions of effect under that interval procedure. The primary risk-difference interval is reported with bounds just above zero and farther into the positive direction, while the unadjusted p-value is 0.051. The record does not identify the interval and test procedures in enough detail to explain their exact relationship.

For the continuous quality-of-life outcome, the comparison is a mean difference. The posted mean changes are -6.0 for EDP-M and -7.7 for Sz-M, with standard deviations of 21.4 and 25.6, respectively. The unadjusted mean difference is -1.7, with a confidence interval from -11.39 to 7.989 and a p-value of 0.731. These are changes in QLQ-C30 units, not a binary event comparison. The record does not state how the scale was scored or whether a particular direction of change represents improvement.

For number of disease-free participants, the result is binary: 6 of 151 in EDP-M and 3 of 153 in Sz-M. The unadjusted risk-difference comparison has a p-value of 0.301. General statistical context: when event counts are small, estimates of proportions and relative measures can be especially imprecise. The confidence interval for the risk difference includes the no-difference value, so the data do not pin down the direction or size of a difference with precision.

What can be inferred from the outcome summaries?

The primary record describes death counts over a follow-up period, while the title refers to overall survival. A death-count comparison treats the outcome as whether a death was recorded, and does not retain the event timing. General statistical context: survival analyses commonly account for the time to an event and for participants whose event time is not observed during follow-up. Such methods require information about event timing and censoring. The registry record does not post a survival curve, median survival, hazard ratio, or a detailed survival-analysis method, so none should be inferred from the count comparison alone.

The registry record lists secondary outcomes and numerical data for some of them, but reports no secondary analyses. This distinction matters: an outcome value and an analysis result are not interchangeable. The record does not report whether the posted secondary values were analyzed according to an intention-to-treat principle, how missing values were handled, or whether multiple comparisons were addressed.

Finally, the simple planning illustrations associated with the comparisons are based on observed effects and explicit planning assumptions, not on a reconstruction of the trial’s original design. They describe hypothetical future sample sizes under those assumptions. They do not estimate the probability that this completed trial detected an effect, and they do not establish what the trial’s original investigators planned.

11. Confidence Intervals and Precision

The primary risk-difference estimate is 0.095 for Sz-M relative to EDP-M. Its reported interval has a lower limit just above zero and an upper limit of 0.190. The interval communicates that the estimated difference is uncertain in size: values near no difference and appreciably larger positive differences remain relevant to the interval. The unadjusted p-value is 0.051, which is close to the conventional 0.05 reference point. Neither the interval nor the p-value alone establishes a definitive conclusion about survival.

The primary outcome is presented as counts of participants who died, rather than as survival times. This limits what can be said about precision in relation to the stated survival question. The event-count comparison provides uncertainty around a difference in recorded proportions; it does not provide an interval for a difference in median survival or a hazard ratio. Those survival-time estimates are not reported in the registry record.

For quality-of-life change, the unadjusted mean difference is -1.7, and its interval extends from -11.39 to 7.989. This interval includes zero and spans changes in either direction. It is therefore not a precise estimate of a directional difference between groups. The outcome summaries also have different numbers of participants in the two arms: 60 for EDP-M and 39 for Sz-M. The reasons for those analysis counts are not reported in the registry record.

The disease-free participant comparison is based on 6 participants in EDP-M and 3 in Sz-M. Its risk-difference interval includes zero. With few recorded events, an interval can encompass a broad range of plausible differences, so the observed counts should not be read as a precise estimate of a secondary effect. The registry record does not post confidence intervals for every listed secondary outcome.

General statistical context: precision concerns how tightly data constrain an estimate, whereas statistical significance is a decision convention applied to a test or interval. The posted estimates and intervals are more informative when read together than when reduced to a significant or nonsignificant label. The registry record does not report the procedures needed to assess whether the intervals account for all features of the trial design.

12. Planning a Similar Trial: Sample Size

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

The planning values are participants per arm for the binary and continuous outcomes presented in the sample-size material. They are not total trial enrollment targets. The stated planning 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 set at the stated fraction of the observed effect. The registry record does not report the trial’s own original sample-size assumptions or justification.

The 80% power column gives the number of participants per arm that the planning calculation indicates would be needed, under those assumptions, for an 80% chance of detecting the specified effect if that effect were the true one. The 90% power column gives the corresponding per-arm planning count for a 90% chance. These are design probabilities under assumed effects and methods, not guarantees about the results of a future study.

The planning rows describe using the full observed effect, 75% of the observed effect, and 50% of the observed effect. When the target effect is smaller, more participants are required to distinguish it from chance variation under the same assumptions. This illustrates why planning around a smaller effect can require substantially larger groups.

These figures are planning illustrations based on observed effects, not observed power for FIRM-ACT. Observed power is not a useful substitute for reading the estimates and their uncertainty after a trial has been completed. The illustrations also depend on the normal approximation and equal allocation assumption; they should not be treated as the original protocol’s design calculation or as a guarantee that a future trial would achieve the stated power.

For time-to-event planning, the stated convention is to show the total number of events, whereas the other planning values are participants per arm. The listed planning calculations in the available outcomes concern binary and continuous summaries, so the per-arm interpretation applies to those values. The registry record does not report the original planned enrollment rationale.

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 = 0.715; treatment proportion p₁ = 0.810; average p̄ = 0.763.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6015 = 1.1790.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.5977 = 0.5031.
4. n = (1.1790 + 0.5031)² / (0.0952)² = 312.0, rounded up to 313 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 <- 0.71523178807947                          # control proportion
p1 <- 0.810457516339869                          # 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(94497)
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 = 313 (80% power), 418 (90% power)
 75% of observed effect: n per arm = 575 (80% power), 769 (90% power)
 50% of observed effect: n per arm = 1,335 (80% power), 1,786 (90% power)
power.prop.test: 312 
Simulated power at n = 313 per arm: 0.804 (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 identifies overall survival as the primary outcome and lists several secondary outcomes. It does not report a multiplicity strategy, such as an adjustment across outcomes or a prespecified order for testing them. General statistical context: testing multiple outcomes can increase the chance of finding an apparently unusual result by chance. Without a reported plan, the secondary comparisons should not be interpreted as if they were separately protected confirmatory tests.

The record lists 0 reported analyses. It therefore does not provide a sponsor-reported analysis plan or results describing how the outcomes were modeled, whether there were interim analyses, or which analysis populations were used. Those details are not reported in the registry record and should not be inferred from the presence of outcome summaries.

The primary outcome description refers to participants randomized to first-line therapy, but the record does not give a detailed analysis-population definition or explain how participants with incomplete follow-up were handled. It does not report loss to follow-up, censoring rules, missingness patterns, imputation methods, or sensitivity analyses. For the quality-of-life outcome, the arm summaries include 60 participants in EDP-M and 39 in Sz-M, rather than the full randomized arm counts. The reasons for those available sample sizes and the effects of missing data are not reported in the registry record.

For the disease-free outcome, the posted denominators match the randomized arm counts, but the record does not describe the operational definition of disease-free status or how a participant’s status was determined at each assessment. Similarly, it does not state whether outcome assessors were masked or whether assessments were independently reviewed. These omissions limit assessment of the robustness of the secondary results.

Missing-data methods can affect estimates when outcomes are unavailable, particularly if availability is related to health status or treatment experience. General statistical context: complete-case summaries describe participants with available measurements and do not automatically represent every randomized participant. The registry record does not give enough information to determine whether the posted quality-of-life results are affected by such selection. These are reporting limitations, not evidence that any particular handling method was or was not used.

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

Serious events with the highest arm-level rate: bone marrow toxicity (11.5%), other (10.1%), gastrointestinal disorder (8.1%), cardiovascular or thromboembolic events (6.8%), infection (6.8%).

The serious adverse-event summaries list 86 affected participants among 148 at risk in the EDP-M group and 62 among 149 at risk in the Sz-M group. These denominators differ from the randomized arm counts, and the registry record does not explain the difference. The serious adverse-event category terms most frequently listed include bone marrow toxicity at 11.5%, Other at 10.1%, gastrointestinal disorder at 8.1%, cardiovascular or thromboembolic events at 6.8%, infection at 6.8%, and respiratory disorder at 6.1%.

These figures describe reported serious adverse events in the registry; they do not establish that the regimens caused each event or allow a complete comparison of overall safety. The record does not state whether category percentages refer to participants, events, or another denominator, and it does not provide enough detail to determine whether people could appear in more than one category. The death fields for adverse events are not populated. Other adverse-event denominators and affected counts are recorded as zero, which should not be interpreted as proof that no other events occurred.

The serious adverse-event counts are not interchangeable with the primary outcome death counts. The record does not provide definitions, severity breakdowns, exposure-adjusted rates, or a detailed account of how adverse events were collected. Caution is needed when comparing the arm summaries because the at-risk denominators differ and the reporting details are limited.

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

The posted primary results show more recorded deaths in the Sz-M arm than in the EDP-M arm, with an unadjusted risk-difference estimate in the positive direction for Sz-M relative to EDP-M. The unadjusted p-value is 0.051, and the interval indicates uncertainty in the magnitude of the difference. These results describe the observed event counts and their unadjusted comparison; they do not provide a direct estimate of how much longer participants lived in either arm.

The registry’s outcome title is overall survival, but its posted primary values are counts of participants who died. Without event times and a reported time-to-event analysis, readers cannot infer median survival, survival probabilities at particular times, or a hazard ratio. A comparison of death counts also does not reveal whether one group’s deaths occurred earlier or later in follow-up. Those quantities are not reported in the registry record.

The unadjusted comparison is close to a conventional significance threshold. That does not make the result proof of a difference, and a p-value just above a threshold does not prove that there is no difference. The point estimate, interval, event counts, outcome definition, and analysis limitations should be considered together. The registry does not report the exact analysis methods or an adjusted sponsor analysis for the primary outcome.

Secondary outcomes provide limited additional context. The available quality-of-life and disease-free summaries do not give precise evidence of a directional difference, and other listed secondary outcomes lack numerical results in the detailed record. The registry does not describe a multiplicity plan or missing-data methods, which further limits confirmatory interpretation of secondary findings.

These findings are not a treatment recommendation and do not establish that either regimen works or fails. They are a statistical reading of the results recorded for this trial. Clinical decisions require a broader assessment of evidence and individual circumstances; the registry record alone cannot supply that context.

17. Why This Trial Matters Statistically

FIRM-ACT matters statistically because it is recorded as a randomized phase 3 comparison of two first-line regimens in a population with advanced adrenocortical carcinoma that could not be completely removed surgically. Randomization provides an important framework for comparing assigned treatment groups. The record also makes clear that the trial was unmasked, which is relevant when assessing outcomes that may depend on participant reports or clinical judgments.

The trial highlights a distinction between the clinical label of an endpoint and the form of the results posted for it. Overall survival is the primary outcome, but the numerical results are counts of participants who died. A count comparison and a time-to-event analysis answer related but different questions. Keeping that distinction visible prevents readers from interpreting an event-count risk difference as a difference in survival duration.

The primary comparison also illustrates why estimates and uncertainty should be read together. The observed direction favors a lower death proportion in EDP-M, while the unadjusted p-value is near a conventional reference threshold and the interval leaves uncertainty about the size of the difference. A binary significant-or-not label would conceal that nuance.

The secondary summaries show another important issue: outcomes can have different available sample sizes, event frequencies, and measurement scales. Quality-of-life change is available for fewer participants than were randomized, while the disease-free event counts are small. Without missing-data and multiplicity details, those summaries should not be treated as strong independent confirmation.

Finally, the sample-size illustrations demonstrate how planning requirements depend on the effect size assumed. They are calculations based on observed effects and stated planning assumptions, not a record of the original design rationale. Together, these features make the trial useful for teaching careful distinctions among endpoint definitions, event counts, effect estimates, uncertainty, and planning calculations.

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 primary outcome is described as overall survival, but the posted primary results are death counts rather than reported survival times. This prevents assessment of event timing, median survival, survival probabilities over time, or a hazard ratio from the registry results. The follow-up timeframe is described as every 8 weeks until death, up to 5 years, but the record does not explain censoring, incomplete follow-up, or event ascertainment.

The registry record does not report the full statistical analysis plan, the original sample-size justification, or any sponsor-reported analyses. It does not describe interim analyses, covariate adjustment, analysis-population definitions, or missing-data methods. The quality-of-life summaries include fewer participants than the randomized groups, and the reasons for that availability are not given. Those gaps limit assessment of the robustness and generalizability of the secondary comparison.

The study is recorded as unmasked. The record does not state whether outcome assessment was blinded, whether response assessments were independently reviewed, or what protections were used to reduce assessment or reporting bias. This is particularly relevant to outcomes that may involve judgment or self-report, though the record alone does not establish that bias occurred.

The serious adverse-event summaries use at-risk denominators that differ from the randomized arm sizes, without an explanation of the difference. The adverse-event record does not clarify the denominator behind the listed category percentages, possible overlap among categories, or how adverse events were collected and classified. The unpopulated adverse-event death fields and zero entries for other adverse events should not be interpreted as complete evidence of absence.

Finally, the registry lists secondary endpoints without numerical results for all of them, and it does not report a multiplicity approach. These are limitations of the information recorded, not proof that analyses or procedures were absent from the trial itself.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Trial in Locally Advanced and Metastatic Adrenocortical Carcinoma Treatment (FIRM-ACT) — NCT00094497.
• Registry record last updated 2016-09-21; status last verified 2016-09.
• Results first posted 2016-09-21.
• 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

FIRM-ACT is the First International Randomized Trial in Locally Advanced and Metastatic Adrenocortical Carcinoma Treatment, registered as NCT00094497. The registry lists the Collaborative Group for Adrenocortical Carcinoma Treatment as sponsor and marks the phase 3 randomized parallel-group study as completed. The recorded start is 2004-06, primary completion is 2010-12, and enrollment is 304.

The trial compared first-line EDP-M with Sz-M in patients with advanced adrenocortical carcinoma whose disease was not amenable to complete surgical resection. The primary outcome is titled overall survival and is reported as participants who died among those randomized to first-line therapy. Secondary outcomes include progression-free survival, quality-of-life change, best overall response rate, and number of disease-free participants.

The registry record lists 8 outcome measures and 0 reported analyses. It does not report the original sample-size justification, detailed analysis plan, or a time-to-event result for the primary outcome. The posted numerical comparisons should therefore be read as registry-recorded counts and unadjusted comparisons, with the reporting limitations.