Study Evaluating Interferon And CCI-779 In Advanced Renal Cell Carcinoma: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Study Evaluating Interferon And CCI-779 In Advanced Renal Cell Carcinoma (NCT00065468), a randomized phase 3 study. The primary outcome is Overall Survival (OS).

2. Clinical Question

3. Trial Design

This was a phase 3, randomized, open-label, parallel-group study with three treatment groups: interferon alfa, temsirolimus, and interferon alfa plus temsirolimus. The registry lists enrollment as 626 and the study status as completed. The recorded study dates are 2003-07 for start and 2006-06 for primary completion. The registry record does not give further details about the randomization procedure, allocation concealment, or the planned duration of follow-up for each participant.

The study concerned first-line treatment in poor-prognosis subjects with advanced renal cell carcinoma. The primary objective was efficacy, with overall survival as the primary efficacy endpoint. The primary analysis population was intent-to-treat, described as all randomized participants. The reported arm sizes for the overall-survival outcome were 207 for interferon alfa, 209 for temsirolimus, and 210 for the combination. These outcome-specific counts are not a substitute for a full accounting of follow-up or analysis eligibility.

Open-label means participants and study personnel were not masked to assigned treatment, according to the registry classification. The registry record does not report whether outcome assessment used any additional safeguards against knowledge of treatment assignment. The study lists progression-free survival, objective response, clinical benefit, duration of response, time to treatment failure, quality-adjusted time without symptoms or toxicity, and EQ-5D index score among its secondary outcomes. Results are posted for some, but not all, of these measures. Further details about the original sample-size justification and the original statistical plan are not reported in the registry record.

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:

Analysis population for the primary outcome, as defined in the registry: Intent-to-treat (ITT) Population: all randomized participants

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 (OS), measured over Baseline up to Month 80.

Overall survival is the time from randomization until death. For participants who remain alive, the registry defines the observation as censored at the last contact. The reported measure is median overall survival in months, with a 95% confidence interval, for the intent-to-treat population. The stated timeframe is baseline up to Month 80.

Time-to-event outcomes are useful when participants have different lengths of follow-up or when some participants have not experienced the event by the end of observation. Censoring allows their available follow-up to contribute information without treating them as if they had died. In general, the median is the time by which half of the event-time distribution has been reached; it is a summary of the observed survival experience, not a description of every participant’s outcome.

Overall survival is a direct endpoint based on death rather than a tumor measurement or a treatment-response category. Comparing survival across randomized groups addresses the trial’s stated primary efficacy question. A median alone does not capture the full timing of events, so the registry also reports hazard-ratio analyses. Those comparisons should be read alongside the medians and their confidence intervals, with attention to the analysis method and the limits of the posted information.

7. Results Posted in the Registry

• Interferon Alfa vs Temsirolimus: hazard ratio 0.78 (95% CI 0.63–0.97), reported p = 0.025 (as reported in the registry).
• Interferon Alfa vs Interferon Alfa and Temsirolimus: hazard ratio 0.93 (95% CI 0.75–1.15), reported p = 0.490 (as reported in the registry).

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.

Progression-Free Survival (PFS)

• Endpoint type: Time to event: compared as a hazard ratio.
• Test: Hazard ratio as reported by the sponsor (Log Rank); it was not recalculated.
• Result:
  • Interferon Alfa vs Temsirolimus: hazard ratio 0.74 (95% CI 0.60–0.91), reported p = 0.004 (as reported in the registry).
  • Interferon Alfa vs Interferon Alfa and Temsirolimus: hazard ratio 0.76 (95% CI 0.62–0.94), reported p = 0.011 (as reported in the registry).
• Interpretation:
  • The 95% confidence interval excludes no difference (a ratio of 1), so the hazard of the event is statistically lower for Interferon Alfa vs Temsirolimus than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval excludes no difference (a ratio of 1), so the hazard of the event is statistically lower for Interferon Alfa vs Interferon Alfa and Temsirolimus than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Percentage of Participants With Objective Response

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Temsirolimus: 9.1% (19/209) versus 5.3% (11/207) on control; risk difference 3.8 percentage points (95% CI -1.2 to 8.7), risk ratio 1.71 (0.83–3.51); unadjusted two-proportion z-test p = 0.136.
  • Interferon Alfa and Temsirolimus: 9.5% (20/210) versus 5.3% (11/207) on control; risk difference 4.2 percentage points (95% CI -0.8 to 9.2), risk ratio 1.79 (0.88–3.65); unadjusted two-proportion z-test p = 0.101.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Temsirolimus and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Interferon Alfa and Temsirolimus and the control. The interval gives the range of effects that remain compatible with the data.

Percentage of Participants With Clinical Benefit

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Temsirolimus: 34.0% (71/209) versus 16.4% (34/207) on control; risk difference 17.5 percentage points (95% CI 9.4 to 25.7), risk ratio 2.07 (1.44–2.97); unadjusted two-proportion z-test p = <0.001.
  • Interferon Alfa and Temsirolimus: 30.0% (63/210) versus 16.4% (34/207) on control; risk difference 13.6 percentage points (95% CI 5.6 to 21.6), risk ratio 1.83 (1.26–2.64); unadjusted two-proportion z-test p = 0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for Temsirolimus than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for Interferon Alfa and Temsirolimus than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The posted secondary results show a broadly similar numerical pattern across progression-free survival, objective response, and clinical benefit: the temsirolimus and combination groups have higher posted medians or percentages than interferon alfa alone. This gives context beyond overall survival, but these measures address different aspects of disease status and treatment experience. They are not interchangeable with the primary endpoint, and the pattern across them does not prove a single underlying mechanism or establish the primary result.

For the secondary time-to-event outcome, sponsor-reported comparisons are posted, as are categorical analyses for response and clinical benefit. The registry also lists duration of response, time to treatment failure, quality-adjusted time without symptoms or toxicity, and EQ-5D index score as secondary outcomes. Results for those listed measures are not reported in the registry record. Their absence means the overall secondary-outcome picture is incomplete.

Secondary findings generally carry less inferential weight than a prespecified primary endpoint, particularly when several outcomes and comparisons are examined. Testing multiple hypotheses increases the chance of obtaining at least one apparently unusual result by chance if no adjustment or hierarchy is used. The registry record does not report a multiplicity adjustment or a testing hierarchy, so the secondary p-values should be interpreted as reported rather than as confirmatory evidence with a known family-wise error rate. Unadjusted secondary results can be informative and hypothesis-generating, but they should not override the primary endpoint or be treated as independent confirmation.

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

• Progression-Free Survival (PFS)
• Percentage of Participants With Objective Response
• Percentage of Participants With Clinical Benefit
• Duration of Response (DR)
• Time to Treatment Failure (TTF)
• Quality-adjusted Time Without Symptoms or Toxicity (Q-TWiST)
• European Quality of Life Health Questionnaire (EQ-5D) - Index Score

9. Statistical Interpretation

10. Statistical Methods Explained

The primary endpoint is a time-to-event outcome. Participants enter the risk set at randomization and are followed for time to death, with living participants censored at their last contact under the registry definition. This approach differs from analyzing a simple percentage dead at a fixed date: it can use event timing and observed follow-up even when follow-up ends at different times. A censored participant contributes information up to the last known contact, but censoring does not reveal what happened after that point.

What does a median survival time describe?

A median is a summary of the event-time distribution. It gives a central point in that distribution and is expressed in months. It does not show the shape of the entire survival curve, the timing of every event, or whether the groups’ survival patterns are proportional over time. The registry reports the median and its 95% confidence interval for each arm, which gives a sense of uncertainty around that summary.

How should the hazard ratio be read?

A hazard ratio compares the event rates over follow-up under a model for time-to-event data. The registry reports Cox proportional-hazards estimates and identifies Log Rank as the analysis method. A hazard ratio of 1 represents equal hazards under the comparison’s specified direction; estimates on either side of 1 indicate different relative hazards according to the numerator and denominator convention. The posted labels give the comparison as interferon alfa versus the other treatment, but do not specify the ratio’s numerator convention in more detail. Therefore, interpretation should retain the estimate and comparison as reported rather than infer an unposted coding detail.

The proportional-hazards framework commonly assumes that the relative hazard is adequately represented by a constant ratio over time. The registry record does not report a test or assessment of this assumption. A hazard ratio is also not a ratio of median survival times, and it should not be translated into a direct change in median months. The confidence interval describes uncertainty in the estimated relative hazard, conditional on the analysis and its assumptions.

What do the p-values contribute?

A p-value measures how compatible the observed data are with a specified null hypothesis under the analysis model. It is not the probability that the null hypothesis is true, nor does it measure the size or clinical importance of an effect. The sponsor reports p-values for both primary comparisons. The reported values should be considered with the estimates and confidence intervals, rather than used as a stand-alone ranking of treatment groups. The registry record does not state whether the primary comparisons were adjusted for multiplicity.

What do the secondary analyses add?

The registry reports time-to-event methods for progression-free survival and categorical comparisons for objective response and clinical benefit. A categorical outcome describes whether participants met a defined response or benefit condition, while a time-to-event outcome incorporates the timing of progression or death and censoring. The posted registry results identify the Cochran-Mantel-Haenszel method for response and clinical-benefit comparisons. The record does not provide enough detail to reconstruct all model specifications, stratification factors, or endpoint definitions.

Recalculated values, when presented, are simple unadjusted calculations from posted summary statistics and are supplementary. They do not reproduce a sponsor analysis that may use a different method or additional design information. The sponsor’s reported analyses are the primary reference for the trial’s inferential results. A difference between an unadjusted recalculation and a reported analysis can arise because the methods or underlying data differ; the registry record does not provide all individual-level data needed to independently reproduce the sponsor’s model.

How should planning illustrations be understood?

The planning illustrations use the observed effect as a reference and show hypothetical event or participant requirements under stated assumptions. For time-to-event comparisons, the displayed quantity is total events; for other outcomes, it is participants per arm. These calculations are not the trial’s original design calculation, and the registry record does not report the original design assumptions. They are not evidence about the probability that the completed study detected an effect. General statistical planning depends on assumptions about the target effect, significance level, allocation, and analysis model; changing those assumptions changes the resulting planning requirement.

11. Confidence Intervals and Precision

A 95% confidence interval expresses uncertainty about an estimate under the statistical method used. In repeated use of the same method under its assumptions, intervals constructed this way would contain the true parameter at the stated rate. For an individual trial, the interval is not a probability statement that the true value lies inside that particular interval. It also does not account automatically for biases, model misspecification, missing data, or unreported analysis choices.

For the interferon alfa versus temsirolimus overall-survival comparison, the reported hazard ratio was 0.78 and its 95% confidence interval was 0.63 to 0.97. This interval is relatively close to 1 at its upper end and does not include 1. For interferon alfa versus the combination, the estimate was 0.93, with a 95% confidence interval of 0.75 to 1.15. That interval includes 1 and covers values on either side of it. These are the sponsor-reported intervals; the registry’s comparison labels do not specify the hazard-ratio numerator convention in more detail.

The arm-specific median-survival intervals also communicate uncertainty: 6.1 to 8.8 months for interferon alfa, 8.6 to 12.7 months for temsirolimus, and 6.6 to 10.3 months for the combination. Overlap between arm-specific intervals is not itself a formal test of a treatment contrast. The reported hazard-ratio analyses address the comparisons directly under their stated methods.

Precision is not the same as clinical importance. A narrow interval may still be compatible with effects of different practical importance, while a wider interval may leave substantial uncertainty. The registry record does not report enough information to assess every source of uncertainty, including the proportional-hazards assumption or missing-data procedures. The confidence intervals should therefore be read as model-based precision summaries, not as guarantees about outcomes in other settings.

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 illustrations are hypothetical requirements based on the observed effect, not the trial’s original design calculation. For time-to-event outcomes, the entries are total events needed for the comparison; for other outcomes, they are participants per arm. The assumptions stated for these illustrations 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 to the stated fraction of the observed effect. The registry record does not report the original sample-size justification or the assumptions used when the trial was designed.

The 80% power column describes the planning requirement for a hypothetical study designed to have an 80% chance of detecting the specified effect under the stated assumptions, if that effect and the assumptions were correct. The 90% power column uses a higher target chance of detection, again conditional on those assumptions. These are design targets, not guarantees of detection and not descriptions of the completed trial’s probability of finding an effect.

Rows for smaller fractions of the observed effect require more information: smaller effects are harder to distinguish from random variation, so the illustrations call for more events or participants. For the time-to-event comparisons, the requirement is expressed as events rather than participants because the number of observed events is central to the analysis. For categorical outcomes, the requirement is expressed per arm. The values are planning illustrations and are not observed power; observed power is not a useful substitute for interpreting the estimated effects and their uncertainty.

The illustrations do not incorporate unreported design features or establish that the original study was planned with the same assumptions. They should be used to understand how hypothetical requirements change with the target effect and power level, not to revise the trial’s reported conclusions.

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

d is the total number of events needed (Schoenfeld's formula) with 1:1 allocation and proportional hazards.

Worked calculation for this trial

1. Hazard ratio HR = 0.780, so ln(HR) = -0.2485.
2. d = 4 × (1.96 + 0.842)² / [ln(0.780)]² = 508.6, rounded up to 509 events in total 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
hr <- 0.78                              # observed hazard ratio
events_needed <- function(power, frac = 1) ceiling(round(4 * (z_a + qnorm(power))^2 / log(hr^frac)^2, 6))   # Schoenfeld, 1:1 allocation
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: events = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(events_needed(0.80, f), big.mark = ","), format(events_needed(0.90, f), big.mark = ",")))

# Simulation: given d total events under proportional hazards, events in the treatment arm are Binomial(d, hr / (1 + hr)).
# The score (log-rank type) statistic is (D1 - d / 2) / sqrt(d / 4).
set.seed(65468)
d    <- events_needed(0.80)
reps <- 20000
D1 <- rbinom(reps, d, hr / (1 + hr))
z  <- (D1 - d / 2) / sqrt(d / 4)
cat(sprintf("Simulated power with %s events: %.3f (%d replicates)\n", format(d, big.mark = ","), mean(abs(z) > z_a), reps))

Output from running the code

100% of observed effect: events = 509 (80% power), 681 (90% power)
 75% of observed effect: events = 905 (80% power), 1,211 (90% power)
 50% of observed effect: events = 2,035 (80% power), 2,724 (90% power)
Simulated power with 509 events: 0.807 (20000 replicates)

The simulation uses the fact that, with d events in total and proportional hazards, the number of events in the treatment arm is binomial. It is an approximation that conditions on the total number of events, and it should land close to the target power.

14. Group-Sequential Design Analysis

Many time-to-event trials, especially in oncology, stop or report early when interim data are overwhelming, so a single fixed-sample number understates the real design problem. The calculation below is an illustrative group-sequential design built from this trial's posted control median and hazard ratio. The registry record does not state the planned number of looks or the spending function, so the design is a planning illustration, not a reconstruction of the protocol. Assumed: one-sided α = 0.025, 90% power, three equally spaced looks on information, Lan-DeMets O'Brien-Fleming spending, 24 months of accrual, 60 months in total and a 1% monthly dropout hazard.

Under these assumptions the design needs about 782 participants in total, with the boundaries below.

Fixed design versus group-sequential alternatives

Group-sequential designs cost a small increase in maximum sample size and events compared with the fixed design, in exchange for the chance to stop early for overwhelming efficacy. O'Brien-Fleming spending keeps early boundaries very conservative and the final boundary close to the fixed-design value, whereas Pocock spending spends more alpha early.

Sensitivity to a smaller true effect

Planning for exactly the observed effect is optimistic, because observed effects in published trials tend to be somewhat larger than the true effect. The table repeats the main design (three looks, O'Brien-Fleming spending, 90% power) for smaller true hazard ratios.

For context, this trial enrolled 626 participants.

Cross-check, upper boundaries: gsDesign 3.71, 2.511, 1.993 | rpact 3.71, 2.511, 1.993. Agreement between the two packages confirms the boundary calculation.

R code and output

suppressWarnings(suppressMessages({ library(gsDesign); library(rpact) }))
med_control <- 7.3          # control-arm median, months (converted from the posted unit)
hr          <- 0.78          # hazard ratio used for planning
lambdaC     <- log(2) / med_control
eta         <- 0.01               # dropout hazard per month (assumption)
acc_months  <- 24                 # accrual duration (assumption)
study_months<- 60                 # total study duration (assumption)

design <- function(k, sfu, beta, h = hr) gsSurv(k = k, test.type = 1, alpha = 0.025, beta = beta, sfu = sfu,
  lambdaC = lambdaC, hr = h, hr0 = 1, eta = eta, gamma = 1, R = acc_months, T = study_months, minfup = study_months - acc_months)

# Main design: 3 looks, Lan-DeMets O'Brien-Fleming spending, one-sided alpha 0.025, 90% power
x <- design(3, sfLDOF, 0.10)
cat(sprintf("N_TOTAL|%s\n", format(ceiling(sum(x$gamma * x$R)), big.mark = ",")))
for (i in 1:3) cat(sprintf("GS|%d|%.1f|%.0f|%.3f|%.5f|%.5f\n", i, x$T[i], x$n.I[i], x$upper$bound[i], pnorm(-x$upper$bound[i]), cumsum(x$upper$spend)[i]))
cat("\n"); print(gsBoundSummary(x))

# Comparison of designs
cmp <- list(list("Fixed design, one analysis", 1, sfLDOF), list("Two looks, O'Brien-Fleming", 2, sfLDOF),
            list("Three looks, O'Brien-Fleming", 3, sfLDOF), list("Three looks, Pocock", 3, sfLDPocock))
cat("\n")
for (b in c(0.20, 0.10)) for (d in cmp) {
  y <- design(d[[2]], d[[3]], b)
  cat(sprintf("DES|%s|%d|%.0f|%s|%.1f\n", d[[1]], round(100 * (1 - b)), tail(y$n.I, 1), format(ceiling(sum(y$gamma * y$R)), big.mark = ","), tail(y$T, 1)))
}

# Sensitivity: what if the true effect is smaller than the observed one? (3 looks, O'Brien-Fleming, 90% power)
cat("\n")
for (fr in c(1, 0.75, 0.5)) {
  y <- design(3, sfLDOF, 0.10, exp(log(hr) * fr))
  cat(sprintf("SENS|%.2f|%.3f|%.0f|%s\n", fr, exp(log(hr) * fr), tail(y$n.I, 1), format(ceiling(sum(y$gamma * y$R)), big.mark = ",")))
}

# Independent cross-check of the boundaries with rpact
r <- getDesignGroupSequential(kMax = 3, alpha = 0.025, beta = 0.10, sided = 1, typeOfDesign = "asOF", informationRates = x$timing)
cat(sprintf("\nCross-check, upper boundaries: gsDesign %s | rpact %s\n", paste(round(x$upper$bound, 3), collapse = ", "), paste(round(r$criticalValues, 3), collapse = ", ")))

Method: LachinFoulkes 
    Analysis               Value Efficacy
   IA 1: 33%                   Z   3.7103
      N: 528         p (1-sided)   0.0001
 Events: 230        ~HR at bound   0.6126
   Month: 16    P(Cross) if HR=1   0.0001
             P(Cross) if HR=0.78   0.0338
   IA 2: 67%                   Z   2.5114
      N: 782         p (1-sided)   0.0060
 Events: 459        ~HR at bound   0.7909
   Month: 26    P(Cross) if HR=1   0.0060
             P(Cross) if HR=0.78   0.5603
       Final                   Z   1.9930
      N: 782         p (1-sided)   0.0231
 Events: 688        ~HR at bound   0.8590
   Month: 60    P(Cross) if HR=1   0.0250
             P(Cross) if HR=0.78   0.9000



Cross-check, upper boundaries: gsDesign 3.71, 2.511, 1.993 | rpact 3.71, 2.511, 1.993

15. Analyses Reported by the Sponsor

The registry reports sponsor analyses for overall survival using a Log Rank method and a Cox proportional-hazards parameter. Those analyses give hazard ratios of 0.78 for interferon alfa versus temsirolimus and 0.93 for interferon alfa versus the combination, with their respective 95% confidence intervals and p-values. These reported results are the trial’s formal analyses in the registry record.

Any recalculated values are simple, unadjusted calculations from posted summary statistics. Such calculations can help readers understand the scale and direction of a comparison, but they do not reproduce the sponsor’s time-to-event analysis or necessarily use the same assumptions. Summary-level data cannot capture all details available to an analysis of participant-level event times and censoring.

The registry record marks no discrepancy between the reported and recalculated results. Even so, recalculations should be treated as supplementary rather than as replacements for the sponsor’s analysis. The reported hazard ratios, confidence intervals, and p-values should be read together, with the comparison direction interpreted cautiously because the record does not specify the ratio’s numerator convention in more detail. The registry does not report enough information to independently reproduce the full sponsor analysis.

16. Multiplicity, Missing Data and Analysis Populations

The study evaluates overall survival across three treatment groups, with the primary objective comparing each experimental regimen against interferon alfa alone. The registry record reports a p-value for each primary comparison but does not report whether the testing strategy adjusted for multiple comparisons, whether a hierarchy was used, or how type I error was controlled across the primary analyses. Without those details, the reported p-values should be understood as the values attached to the listed analyses, not as evidence that a particular multiplicity procedure was applied.

Several secondary outcomes are also listed, and results are posted for progression-free survival, objective response, and clinical benefit. Examining multiple outcomes can increase the chance of apparently positive findings from random variation. The registry record does not report a multiplicity plan for the secondary endpoints. Accordingly, those findings are best considered alongside their role as secondary outcomes and the limits of the posted analysis information.

The primary population is identified as intent-to-treat, all randomized participants. For the overall-survival endpoint, the registry says that participants alive at last contact are censored at that contact. Further details about the handling of missing outcome data, loss to follow-up, withdrawals, or deviations from assigned treatment are not reported in the registry record. The record also does not report whether sensitivity analyses assessed the effect of missingness or alternative censoring assumptions.

These omissions do not show that the trial lacked a plan or that data were mishandled; they mean the registry record does not provide those details. Interpretation should distinguish what is explicitly documented—the analysis population, endpoint definition, reported method, estimates, intervals, and p-values—from methods that cannot be verified from the posted record.

17. 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: anemia (9.6%), dyspnea (7.2%), carcinoma (6.2%), pneumonia (5.3%), asthenia (4.8%).

The registry lists participants at risk and participants affected by serious adverse events and by other adverse events for each treatment group. For serious adverse events, the posted counts are 99 of 200 in the interferon alfa group, 82 of 208 in the temsirolimus group, and 122 of 208 in the combination group. For other adverse events, the corresponding counts are 197 of 200, 208 of 208, and 205 of 208. These counts describe the recorded groups and denominators; they do not by themselves establish comparative risk or causation.

The registry lists anemia, dyspnea, carcinoma, pneumonia, asthenia, and dehydration among the most frequent serious adverse-event terms, with percentages of 9.6%, 7.2%, 6.2%, 5.3%, 4.8%, and 4.8%, respectively. The record does not provide the term-specific group breakdown in the information. Death counts under the adverse-event information are not reported in the registry record.

Comparisons of safety require attention to definitions, exposure time, ascertainment, and the severity and duration of events. Those details are not reported, so the counts should be read descriptively rather than as a complete benefit-harm assessment.

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

The overall-survival results describe outcomes among participants randomized in this trial and analyzed in the intent-to-treat population. The posted median and hazard-ratio summaries suggest different observed survival patterns across the three groups. The temsirolimus comparison with interferon alfa has a reported confidence interval that excludes 1 and a p-value of 0.025, while the combination comparison has a confidence interval that includes 1 and a p-value of 0.490. These statistical summaries do not, on their own, determine clinical importance or establish equivalence between the combination and interferon alfa.

The results do not establish that one regimen is appropriate for every person with renal cell carcinoma, or that findings apply beyond the trial’s first-line poor-prognosis advanced-disease population. Nor do the results show that observed differences were caused solely by treatment assignment in all possible settings. Randomization supports comparative interpretation within the study, but limits in reporting and analysis assumptions still matter.

A p-value is not the probability that a treatment has no effect, and a confidence interval does not remove uncertainty about bias, missing data, model assumptions, or generalizability. The reported hazard ratio is also not a direct change in median survival. The comparison direction is listed by treatment names, but the record does not spell out the numerator convention for the hazard ratio.

Overall survival is only one aspect of a treatment’s effects. Secondary outcomes and adverse-event counts add context, but the posted secondary results are incomplete and the safety information does not provide a full comparative assessment. The results therefore support a careful reading of the trial’s reported statistical evidence, not an individualized treatment recommendation or a conclusion about every outcome that could matter.

19. Why This Trial Matters Statistically

This trial illustrates why time-to-event analyses are not reducible to comparing arm medians. The registry reports both median overall survival and hazard-ratio comparisons, with confidence intervals and p-values. The medians give an accessible description of the survival distributions, while the Cox and Log Rank results address event timing across follow-up. They answer related but not identical statistical questions.

It also illustrates the importance of distinguishing an estimate from its uncertainty. The temsirolimus comparison has a confidence interval that excludes 1, whereas the combination comparison’s interval includes 1. The interval widths and locations convey information that a binary significant-or-not label would miss. A non-significant result does not establish equality, and a significant result does not quantify clinical importance by itself.

The three-arm design creates more than one comparison involving the control group, making multiplicity a relevant question. The registry does not report the multiplicity procedure, so readers cannot assume that the p-values reflect a particular family-wise error strategy. The secondary outcomes add breadth, but their multiple comparisons and incomplete reporting limit the weight that can be placed on any single secondary finding.

Finally, the planning illustrations clarify how event or participant requirements depend on the target effect and desired power. They are distinct from the original design justification, which is not reported in the registry record, and they are not observed power. Together, these features show why statistical interpretation requires attention to endpoint, model, precision, multiplicity, and reporting completeness rather than relying on a single number.

20. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

The registry record does not report the original sample-size justification or the assumptions used to design the trial. Its separate planning illustrations are hypothetical and do not recover that original rationale. The record also does not describe interim analyses, stopping rules, or the complete statistical analysis plan.

Although the primary analysis population is identified as intent-to-treat, the registry does not give details about adherence, treatment switching, withdrawals, loss to follow-up, or sensitivity analyses. For overall survival, censoring at last contact is specified for participants who are alive, but the amount and pattern of censoring are not described in the information. Those details can affect how confidently readers assess the time-to-event estimates.

The registry identifies the Log Rank method and Cox proportional-hazards parameter for the primary comparisons, but does not report checks of the proportional-hazards assumption or details of model covariates and stratification. It also does not specify the hazard-ratio numerator convention beyond naming the compared groups. The posted record does not report a multiplicity adjustment for the primary or secondary comparisons.

The trial was open-label. The registry does not describe additional protections against possible knowledge-of-treatment effects in outcome assessment. The study’s safety information is summarized through counts and selected serious-event terms, without enough detail to assess exposure time or the full clinical context of each event. Finally, the registry identifies a specific first-line, poor-prognosis advanced renal cell carcinoma population; applicability to other populations is not established by these results.

21. Related Tutorials

22. Related Statistical Calculators

23. Sources

• ClinicalTrials.gov: Study Evaluating Interferon And CCI-779 In Advanced Renal Cell Carcinoma — NCT00065468.
• Registry record last updated 2012-10-25; status last verified 2012-09.
• Results first posted 2012-10-25.
• 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.

24. Record Summary

The registry describes a completed, randomized, open-label, phase 3, parallel-group study of interferon alfa, temsirolimus, and their combination in first-line poor-prognosis advanced renal cell carcinoma. Enrollment is listed as 626. The primary endpoint was overall survival in the intent-to-treat population, measured from randomization to death, with censoring at last contact for participants who remained alive.

Median overall survival was 7.3 months with interferon alfa, 10.9 months with temsirolimus, and 8.4 months with the combination. Sponsor-reported hazard-ratio analyses gave p-values of 0.025 for interferon alfa versus temsirolimus and 0.490 for interferon alfa versus the combination. The registry also posts secondary results and adverse-event counts, but does not report several details needed to reconstruct the complete analysis plan, missing-data handling, or multiplicity strategy.