Docetaxel and Bortezomib in Treating Patients With Progressive or Recurrent Non-Small Cell Lung Cancer: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Docetaxel and Bortezomib in Treating Patients With Progressive or Recurrent Non-Small Cell Lung Cancer (NCT00362882), a randomized phase 2 study. The primary outcome is Overall Response Rate.

2. Clinical Question

3. Trial Design

This was a randomized, open-label, parallel-group phase II trial sponsored by the National Cancer Institute. The registry lists enrollment of 81 and a completed status. The record gives a start date of 2006-07 and a primary completion date of 2010-07. It describes a comparison of sequential versus concurrent administration of docetaxel and bortezomib in previously treated non-small cell lung cancer.

In Arm 1, docetaxel was given intravenously over 60 minutes on day 1, with bortezomib intravenously over 3-5 seconds on days 1 and 8. In Arm 2, docetaxel was administered as in Arm 1, while bortezomib was given on days 2 and 8. Thus, the defining contrast is the timing of bortezomib relative to docetaxel and the treatment schedule, rather than a contrast between different drug combinations.

The registry lists 40 participants for Arm 1 and 41 for Arm 2 in the primary outcome results. These are the arm-level denominators attached to those posted results; the record does not establish whether every enrolled participant was included in every outcome analysis. Details of allocation generation, concealment, eligibility criteria beyond the brief description, treatment exposure, and analysis populations are not reported in the registry record. Masking is listed as none, so the trial was not blinded according to the registry.

The primary completion date and trial status describe the registry record, but do not by themselves explain how the analysis was conducted or how follow-up was handled. Protocol-specific design assumptions, including the original sample-size justification, 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

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 Response Rate, measured over Up to 4 years.

The primary endpoint, overall response rate, is the percentage of participants whose target lesions met the registry's stated RECIST v1.0 criteria for complete or partial response. Complete response means disappearance of all target lesions. Partial response means at least a 30% decrease in the sum of the longest diameters of target lesions. The registry says response was assessed by CT, MRI or X-ray, with a timeframe of up to 4 years.

Response rate is a binary outcome at the participant level: a participant is classified as having an overall response if the response definition is met, or not having an overall response if it is not. This makes the measure a direct summary of the proportion classified as responders under the stated criteria. As a general statistical point, binary outcomes can make an endpoint easy to interpret, but the resulting percentage does not describe the duration of response or the full pattern of change in tumor measurements.

The registry reports 10.0% for Arm 1 and 10.0% for Arm 2. The record does not provide details about how participants with unevaluable imaging, missing assessments, or incomplete follow-up were handled in calculating these percentages. Nor does the registry record report a more detailed definition of the response-evaluable population. Those omissions limit interpretation of the percentage as a summary of all participants randomized.

7. Results Posted in the Registry

• Arm 2: 9.8% (4/41) versus 10.0% (4/40) on control; risk difference -0.2 percentage points (95% CI -13.2 to 12.8), risk ratio 0.98 (0.26–3.64); unadjusted two-proportion z-test p = 0.971.

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.

Disease Control Rate

• 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:
  • Arm 2: 48.8% (20/41) versus 50.0% (20/40) on control; risk difference -1.2 percentage points (95% CI -23.0 to 20.6), risk ratio 0.98 (0.63–1.52); unadjusted two-proportion z-test p = 0.913.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Arm 2 and the control. The interval gives the range of effects that remain compatible with the data.

Progression-free Survival @ 6 Months

• 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:
  • Arm 2: 17.1% (7/41) versus 30.0% (12/40) on control; risk difference -12.9 percentage points (95% CI -31.2 to 5.4), risk ratio 0.57 (0.25–1.30); unadjusted two-proportion z-test p = 0.170.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Arm 2 and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes add context by considering disease control, a fixed-time progression-free survival measure, and overall survival. Their broad pattern does not remove the uncertainty in the primary response comparison. In particular, outcomes describing disease control or remaining progression-free capture aspects of disease status that are related to, but not identical to, the RECIST-defined overall response endpoint. Overall survival is a distinct outcome, and the registry lists it as secondary without posting a numerical result in the registry record for this analysis.

The registry reports a log-rank analysis for progression-free survival, while its fixed-time measure is expressed as a percentage. These address related but different questions: a fixed-time percentage describes status at a specified time, while a log-rank test compares event-time experience over follow-up. They should not be treated as interchangeable confirmations or contradictions of the primary result.

Secondary results generally carry less confirmatory weight when several outcomes are assessed and no multiplicity strategy is reported. Testing multiple outcomes increases the chance that at least one result may appear notable by chance, depending on the testing plan and relationships among outcomes. The registry record does not report a multiplicity adjustment or a prespecified hierarchy of secondary hypotheses. Thus, secondary findings are better viewed as supportive or exploratory evidence than as independent proof of a schedule effect.

The record lists four outcome measures and three secondary outcomes, but does not provide complete reported analyses for all listed outcomes. Missing numerical results should not be interpreted as evidence of no effect. Taken together, the secondary endpoints can inform the overall clinical and statistical context, but they do not establish a stronger conclusion than the imprecise primary comparison supports.

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

• Overall Survival
• Disease Control Rate
• Progression-free Survival @ 6 Months

9. Statistical Interpretation

10. Statistical Methods Explained

The primary endpoint is binary: each participant is classified according to whether a complete or partial response was recorded under the registry's RECIST v1.0 definition. A proportion summarizes the number classified as having an event relative to the arm's reported outcome denominator. The registry gives percentages for each arm and the arm-level denominators used in the posted result. The registry record does not report how missing or unevaluable assessments were classified.

The comparison is presented as a risk difference, with Arm 2 compared against Arm 1. In general, a risk difference subtracts the event proportion in one group from the event proportion in the reference group, with the direction depending on the stated group order. A value at zero corresponds to equal proportions; values on either side describe differences in opposite directions. The posted estimate is -0.002. Its 95% confidence interval runs from -0.132 to 0.128, so the data are compatible with an effect in either direction under this calculation.

A confidence interval communicates uncertainty in an estimated effect. It is not a range containing a fixed proportion of individual participant outcomes, nor does it assign a probability to the true value after the data are observed. Its interpretation depends on the analysis method and assumptions. The registry provides a confidence interval for the unadjusted risk difference, but it does not report the detailed interval-construction method in the record.

The unadjusted p-value for the primary comparison is 0.971. In general, a p-value evaluates how compatible the data are with a null hypothesis under a specified statistical model. It does not measure the size or clinical importance of an effect, and it is not the probability that a result occurred by chance. The record does not report a multiplicity adjustment for the primary or secondary outcome analyses. Accordingly, the posted p-value is best read as an unadjusted comparison, not as a result adjusted for a family of outcome tests.

The registry also posts a risk ratio and an odds ratio for the primary comparison, each with confidence limits. These are alternative ways to express a contrast between binary outcomes. A risk ratio compares the proportions directly, while an odds ratio compares the odds of the event. Ratios use a different scale from a risk difference, so their numerical values should not be read as percentage-point differences. Neither scale removes the uncertainty evident in the associated intervals.

The secondary progression-free survival outcome has a reported log-rank analysis with p = 0.17. In general, the log-rank test compares time-to-event experience between groups over follow-up, taking account of the ordering of event times and censoring under its assumptions. The registry also posts a six-month percentage outcome, but it does not provide a hazard ratio or a confidence interval for a time-to-event model. The log-rank result should not be treated as the same estimand as the difference between percentages at a fixed time.

For binary outcomes, uncertainty depends in part on the numbers of participants and events in each arm. General statistical reasoning explains why limited event information can leave wide intervals even when the point estimate is near zero. In time-to-event analyses, the number and timing of events are important to the information available; censoring also affects what can be learned from follow-up. The registry record does not report censoring details, event-time summaries, or a detailed statistical analysis plan.

Randomization is intended, as a general design principle, to support fair comparison by reducing systematic differences between groups at allocation. It does not guarantee balance in every trial, and it does not address missing outcome data or deviations after allocation. Because masking is listed as none, participant and investigator awareness of assigned schedule was not prevented by blinding. The record does not describe measures to limit assessment bias or how response assessments were reviewed.

The record does not report model adjustments, missing-data methods, a per-protocol definition, an intention-to-treat analysis population, interim analyses, or the original statistical plan. Those details matter because analysis choices affect the interpretation of estimates and their uncertainty. The posted summaries support a direct descriptive comparison, but they do not reveal all analytic decisions that may have been made during the trial.

11. Confidence Intervals and Precision

The primary risk-difference estimate for Arm 2 versus Arm 1 is -0.002. Its 95% confidence interval extends from -0.132 to 0.128. Since the interval crosses zero, the posted data are compatible with a lower response proportion in Arm 2, little or no difference, or a higher response proportion in Arm 2. The point estimate alone does not capture that uncertainty.

The interval is wide enough to include effects in both directions. This means the trial's posted primary comparison does not pin down the size or direction of a schedule difference with high precision. The unadjusted p-value of 0.971 is consistent with the interval's failure to isolate a difference from zero, but the two statistics communicate different aspects of the result: the interval gives a range of effect estimates, while the p-value measures compatibility with a null hypothesis under the test assumptions.

Precision is not the same as whether a result is statistically significant. Nor does a confidence interval establish equivalence: that requires a prespecified margin and an appropriate analysis, neither of which is reported in the registry record. The interval should instead be read as a warning against treating equal rounded arm percentages as proof that the underlying response rates are identical.

More generally, confidence intervals are affected by the amount of outcome information and the analysis method. For binary outcomes, the observed numbers of responses and the denominators contribute to uncertainty. The registry record supplies arm-level summaries but does not report all details needed to assess the handling of missing assessments or the precise interval method. The posted confidence interval is therefore useful evidence of uncertainty, but it cannot resolve those unreported analysis details.

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 based on the observed effect and are not the trial's original design justification. For the binary response and disease-control outcomes, the figures are participants per arm. For time-to-event planning, the figures are total events, as specified in the registry record. The progression-free survival planning values should therefore be read as event requirements, not as participants per arm.

The illustrations assume a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. They consider detecting the stated fraction of the observed effect. The columns for 80% and 90% power describe different planning targets: under the stated assumptions, the 90% target is designed to give a higher chance of detecting the specified effect than the 80% target, and generally requires more information. Smaller effects require more participants or events to distinguish them from no difference with the same power target.

These figures are hypothetical planning estimates calculated from observed effects, not evidence about the trial's actual design choices. They are not observed power. Observed power is not a useful substitute for interpreting the confidence interval and the uncertainty in the effect estimate. The trial's own sample-size assumptions and justification are not reported in the registry record. The planning values should be treated as illustrations of how required information changes with the effect targeted, rather than as a retrospective judgment about whether the trial was adequately designed.

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 = 0.100; treatment proportion p₁ = 0.098; average p̄ = 0.099.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.4220 = 0.8270.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.4220 = 0.3551.
4. n = (0.8270 + 0.3551)² / (-0.0024)² = 234,911.9, rounded up to 234,912 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 <- 0.1                          # control proportion
p1 <- 0.0975609756097561                          # 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(362882)
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 = 234,912 (80% power), 314,480 (90% power)
 75% of observed effect: n per arm = 418,770 (80% power), 560,613 (90% power)
 50% of observed effect: n per arm = 944,812 (80% power), 1,264,835 (90% power)
power.prop.test: 234911.9 
Simulated power at n = 234,912 per arm: 0.798 (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 lists one primary endpoint and three secondary outcomes. It does not report a multiplicity adjustment, a testing hierarchy, or a plan specifying which outcomes would be treated as confirmatory. When several outcomes are examined, unadjusted p-values do not account for the increased opportunity for chance findings across tests. General statistical practice may address this through a prespecified strategy, but the registry record does not say whether such a strategy was used outside the posted information.

The reported progression-free survival log-rank p-value is unadjusted in the information available for this analysis. Its interpretation should therefore remain cautious, especially alongside other outcome assessments. The absence of a posted multiplicity procedure does not show that no such procedure was used; it means the procedure is not reported in the registry record.

Missing-data handling is not reported in the registry record. In particular, the record does not explain how participants with missing or unevaluable imaging contributed to the response outcome, how incomplete follow-up was handled for time-to-event outcomes, or whether any imputation method was used. The analysis populations are also not reported in enough detail to determine whether the posted denominators represent an intention-to-treat, response-evaluable, or another population.

The registry does not report an interim analysis plan, stopping rules, or the original statistical analysis plan. It also does not describe adjustments for baseline characteristics or deviations from assigned treatment. Without these details, the posted estimates can be interpreted as summaries of the recorded outcomes, but the full set of analysis decisions cannot be independently assessed from the registry record alone.

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 0% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: neutrophil count decreased (17.1%), dyspnea (15.0%), pneumonia (10.0%), disease progression (9.8%), hemoglobin decreased (7.5%).

The registry records serious adverse events affecting 15 of 40 participants in Arm 1 and 21 of 41 in Arm 2. It also records other adverse events affecting 40 of 40 participants in Arm 1 and 41 of 41 in Arm 2. These are counts of participants recorded as affected in each category, not measures of treatment effect adjusted for exposure or follow-up.

The listed serious adverse-event terms include neutrophil count decreased, dyspnea, pneumonia, disease progression, hemoglobin decreased, and leukopenia, with percentages reported in the registry. These entries describe events recorded in the study; the information does not establish that a particular event was caused by treatment. The registry record does not provide enough detail to assess event timing, duration, recurrence, or the definition used for each category.

Deaths are not reported in the adverse-event summary. This should not be read as evidence that no deaths occurred. The serious-event figures are descriptive and should be interpreted alongside the trial's population, follow-up, and reporting procedures, which are not fully described in the registry record.

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

The registry results describe a randomized comparison of two schedules of docetaxel and bortezomib in previously treated non-small cell lung cancer. The posted primary outcome is the percentage of participants classified as having an overall response under the stated RECIST criteria. Both arms have a reported response rate of 10.0%, and the unadjusted risk-difference estimate is close to zero. Its confidence interval includes effects in either direction and is not sufficiently narrow to establish that the schedules produce the same response rate.

The results do not establish superiority of either schedule. They also do not demonstrate equivalence or noninferiority, because the registry does not report a prespecified margin for either claim. A nonsignificant p-value is not proof of no difference. Likewise, equality of rounded percentages does not mean the underlying response probabilities are identical.

The outcome is a response classification, not a complete account of treatment experience. It does not by itself describe response duration, symptoms, quality of life, or the balance of benefits and harms. The registry lists secondary outcomes and adverse-event summaries, but analysis and reporting details are incomplete. Missing-data procedures, analysis populations, and the original analysis plan are not reported in the registry record.

These findings should be understood as the posted results of this particular phase II trial, not as a prediction for every patient or setting. The record does not supply enough information to establish how closely the analyzed participants match other populations or how the findings would generalize beyond the trial. Statistical interpretation is therefore appropriately limited to the observed arm summaries, their uncertainty, and the limitations of the registry reporting.

17. Why This Trial Matters Statistically

This trial illustrates why an effect estimate should be read together with its uncertainty. The arm-level primary percentages are the same as reported, and the risk-difference point estimate is near zero. Yet its confidence interval spans effects favoring either schedule. A point estimate that appears small does not settle whether an important difference could remain compatible with the data.

It also demonstrates the distinction between failure to detect a difference and evidence of equivalence. The unadjusted p-value does not provide a probability that the schedules are the same, and the registry does not report an equivalence or noninferiority framework. Making that distinction is central to interpreting randomized comparisons, particularly when the estimate is imprecise.

The different outcome types add a further statistical lesson. A response percentage, a fixed-time progression-free survival percentage, and a log-rank comparison of event times are not interchangeable measures. They answer related but distinct questions and can contribute different information. Their interpretation also depends on analysis populations and follow-up details that are not fully reported in the registry record.

Finally, planning estimates based on observed effects are illustrations rather than evidence of the study's original design rationale or observed power. The record does not report its own sample-size assumptions. Separating retrospective planning calculations from trial design decisions helps avoid overstating what the posted results can establish.

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.
• Participant counts were reconstructed from posted percentages and arm sizes, so small rounding differences are possible.

The registry record gives limited detail about eligibility, participant characteristics, treatment exposure, adherence, and follow-up. It does not report the analysis populations or explain whether all randomized participants contributed to each endpoint. These omissions make it difficult to determine precisely to whom the posted estimates apply and how incomplete outcome information was handled.

For the primary response endpoint, the registry states the RECIST v1.0 criteria and assessment modalities, but does not report how missing or unevaluable imaging was treated, who assessed response, or whether assessment was centrally reviewed. Masking is listed as none. The record does not describe safeguards intended to reduce the influence of knowledge of assigned schedule on assessment.

The confidence interval for the unadjusted risk difference is broad and includes effects in both directions. The result therefore has limited precision. The registry does not report a clinically meaningful difference threshold, an equivalence margin, or a noninferiority margin, limiting interpretation of what effect sizes would be considered important.

For secondary endpoints, the record does not report a multiplicity procedure, and the numerical results available are incomplete. Time-to-event analysis details, including censoring and event definitions, are not fully described. Adverse-event summaries lack details about timing, duration, attribution, and exposure. These are limitations of what the registry record reports; they do not establish that the trial did not collect or analyze those data.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Docetaxel and Bortezomib in Treating Patients With Progressive or Recurrent Non-Small Cell Lung Cancer — NCT00362882.
• Registry record last updated 2017-12-05; status last verified 2017-10.
• Results first posted 2014-10-02.
• 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

NCT00362882 is a completed randomized phase II, open-label, parallel-group trial sponsored by the National Cancer Institute. It compared schedules of docetaxel and bortezomib in previously treated patients with progressive or recurrent non-small cell lung cancer. The registry lists enrollment of 81, a start date of 2006-07, and a primary completion date of 2010-07.

The primary endpoint was overall response rate under RECIST v1.0. The registry reports 10.0% for each arm. The unadjusted risk difference for Arm 2 versus Arm 1 is -0.002, with a 95% confidence interval from -0.132 to 0.128 and an unadjusted p-value of 0.971. The interval indicates substantial uncertainty about the direction and size of any difference.

The registry also lists disease control rate, overall survival, and progression-free survival as secondary outcomes. Analysis populations, missing-data methods, multiplicity handling, and the original sample-size justification are not reported in the registry record.