Treatment of Chronic Cough in Idiopathic Pulmonary Fibrosis With Thalidomide: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Treatment of Chronic Cough in Idiopathic Pulmonary Fibrosis With Thalidomide (NCT00600028), a randomized phase 3 study. The primary outcome is Efficacy of Thalidomide in Suppressing the Chronic Cough of Idiopathic Pulmonary Fibrosis Using the Cough Quality of Life Questionnaire..

2. Clinical Question

The clinical question concerns symptom burden and its effect on quality of life, rather than a lung-function or survival outcome. The registry’s primary endpoint is the CQLQ score at the stated 6 months timeframe. The trial also lists the Visual Analog Scale of Cough and the St. George Respiratory Questionnaire as secondary outcome measures, but the posted secondary-outcome description does not give numerical results for either measure.

The design allows participants to receive both treatments in different periods, with treatment order randomized. The results are therefore reported by treatment period and sequence as well as in a sponsor analysis. These types of results need to be read with the crossover structure in mind: the group means are not simply results from two separate groups that each received only one treatment. The registry record does not report details of how period or sequence effects were handled in the sponsor’s model.

The question is what the posted measurements show about cough-specific quality of life in this study population, and how precise those estimates are. They do not, on their own, establish how the results would apply to people outside the trial or to outcomes that were not measured or reported.

3. Trial Design

This was a Phase III, randomized, double-blind, placebo-controlled crossover trial sponsored by Johns Hopkins University. It enrolled 25 participants and is listed as completed. The registry lists idiopathic pulmonary fibrosis and cough as the conditions studied.

Participants were assigned to one of two sequences. In one sequence, participants received thalidomide for 12 weeks, followed by a two-week washout period and then placebo for 12 weeks. In the other sequence, participants received placebo first, followed by the washout and then thalidomide. The registry describes the study as double-blind, but does not report further details about how masking was maintained or assessed.

The primary endpoint was the CQLQ, described as a cough-specific quality-of-life measure. The primary timeframe is listed as 6 months. The registry says that the efficacy analysis included participants who received the interventions and completed all study visits. It reports group counts for the treatment periods, but does not give a detailed flow of participants through enrollment, completion, and analysis.

The registry lists two outcome measures and two analyses. The primary outcome is the CQLQ. A secondary outcome description refers to cough measured with a Visual Analog Scale and the St. George Respiratory Questionnaire. Numerical findings for those secondary measures are not reported in the registry record.

A crossover design lets each participant receive both interventions, so comparisons may account for the fact that the same person contributes observations under both treatments. The registry reports a sponsor mixed-model analysis and also makes it possible to recalculate simple, unadjusted contrasts from the posted group means. Those are different analyses and should not be treated as interchangeable. The registry does not report the full statistical plan, the sample-size justification, or further details of the sponsor’s model.

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.

Before assignment: One participant was excluded because of an FVC\>90% predicted

First Intervention (12 Weeks)

Reasons for not completing this period:

Second Intervention (12 Weeks)

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: All participants who received the interventions and completed all study visits were included in the efficacy analysis.

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 Efficacy of Thalidomide in Suppressing the Chronic Cough of Idiopathic Pulmonary Fibrosis Using the Cough Quality of Life Questionnaire., measured over 6 months.

The primary endpoint is the Cough Quality of Life Questionnaire (CQLQ), a continuous score intended to measure the effect of cough on health-related quality of life. Its 28 questions concern cough and its effects and use Likert-like 4-point scales. The registry gives a possible score range from 28 to 112 units on a scale and states that lower scores indicate less effect of cough on health-related quality of life; 28 is described as the best score.

A cough-specific quality-of-life measure is relevant to the stated study question because the trial focuses on chronic cough and its impact, rather than solely on a disease measure that may not reflect how cough affects daily life. The questionnaire turns responses to multiple questions into a score that can be compared across treatment periods. Interpreting a score still depends on its direction: a lower CQLQ score is more favorable on the scale’s stated meaning.

The primary outcome is reported as a mean with standard deviation. A mean gives a central summary of scores, while the standard deviation describes variation among the scores. The registry’s primary timeframe is 6 months, and its efficacy population is described as participants who received interventions and completed all study visits. It does not report a threshold for a clinically important change in CQLQ score or details about the questionnaire’s administration in this trial.

The endpoint is one part of the evidence. It does not measure every possible consequence of idiopathic pulmonary fibrosis or cough, and a change in a questionnaire score is not by itself a complete account of participants’ health.

7. Results Posted in the Registry

• Arm Thalidomide 1st, Placebo 2nd (Intervention Placebo): mean 55.20 versus 47.30 on control; difference 7.90 (95% CI -3.35 to 19.15), standardized effect d = 0.56; z-test p = 0.169.
• Arm Placebo 1st, Thalidomide 2nd (Intervention Placebo): mean 61.60 versus 47.30 on control; difference 14.30 (95% CI 3.60 to 25.00), standardized effect d = 1.11; z-test p = 0.009.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is continuous: each participant’s CQLQ is a numerical score, and the registry summarizes the groups using means and standard deviations. A mean describes the group’s average score. The standard deviation describes how spread out the individual scores are around that mean; it is not a confidence interval for the mean and does not show the range of individual scores.

What does a mean difference describe?

A mean difference compares average scores between two groups or treatment periods. Its direction matters. The CQLQ is scored so that lower values indicate less effect of cough on quality of life. Thus, a positive difference in the recalculated comparisons, where the placebo-period mean is compared with the thalidomide-period mean, reflects a higher average score in the placebo period. The numerical difference alone does not account for the trial design or establish the practical importance of the score change.

The recalculated contrasts are explicitly unadjusted. They use the posted summary statistics and do not represent the sponsor’s mixed-model analysis. In a crossover trial, participants receive both treatments at different times. Measurements from the same person can be related, and period and treatment order may matter. A simple comparison of group summaries does not necessarily account for those dependencies or design features. The registry identifies a mixed-model analysis for the sponsor’s reported result, but the model specification, included terms, and handling of the crossover structure are not reported in the registry record.

How should a confidence interval be read?

A confidence interval expresses statistical uncertainty around an estimate. In general, a narrower interval indicates more precision, while a wider interval indicates less precision. An interval that includes zero is compatible with a range of mean differences that includes no difference under the assumptions of that calculation; an interval entirely on one side of zero is not compatible with zero at the corresponding confidence level under those same assumptions. This general interpretation does not correct for an unsuitable analysis method or establish clinical importance.

The unadjusted recalculations report confidence intervals for both contrasts. The first interval extends from -3.346 to 19.15, and the second from 3.6 to 25.0. The sponsor’s result lists a 95% confidence level, but its confidence limits are not reported in the registry record. A confidence interval for the recalculation should not be mistaken for the interval from the sponsor’s mixed model.

What does a p-value tell the reader?

A p-value describes how compatible the observed data are with a specified null model, under the assumptions of the analysis. It is not the probability that the null hypothesis is true, and it is not a measure of the size or clinical importance of a difference. The recalculated unadjusted p-values are 0.169 and 0.009. The sponsor reports p = 0.001 for its mixed-model analysis. These values come from different analyses and should not be read as if they were estimates from one common model.

Unadjusted means that the recalculation does not apply an adjustment for other variables or model structure. It should not be taken to mean that the recalculation reproduces the trial’s intended primary analysis. The registry reports the sponsor’s model as the analysis for the relevant treatment groups, while the simple recalculation is a separate descriptive comparison based on the posted summaries. Since the registry reports a discrepancy, the sponsor’s own analysis takes precedence.

Why can over-dispersion matter?

For count outcomes, over-dispersion means that the observed variability exceeds what a chosen probability model expects. If a method assumes less variability than is present, its uncertainty estimates can be too small. That general issue is not directly the central modeling question for this continuous CQLQ endpoint, which is reported using means and standard deviations. It can matter for other types of outcomes, but no count-based primary endpoint is reported in this trial.

The planning illustrations use a normal approximation and equal allocation between two arms, as stated for those calculations. This is a planning framework, not a description of the trial’s original design calculation. The registry does not report the original sample-size assumptions or justification. The two treatment sequences and repeated treatment periods also mean that simple two-arm planning examples should not be assumed to reproduce the design of this crossover study.

Finally, the analysis population is an important part of interpretation. The registry states that efficacy analyses included participants who received the interventions and completed all study visits. It does not report a detailed account of missing outcome values, the number excluded from the efficacy analysis, or the procedure used for any missing observations. Without those details, readers cannot assess from the registry record how incomplete follow-up affected the reported analysis.

10. Confidence Intervals and Precision

The recalculated mean difference for the comparison involving the thalidomide-first sequence is 7.9, with a 95% confidence interval from -3.346 to 19.15. This interval includes zero and extends across values on either side of zero. Under the assumptions of this unadjusted calculation, the estimate is therefore imprecise with respect to whether the underlying mean difference is positive or negative.

For the comparison involving the placebo-first sequence, the recalculated mean difference is 14.3, with a 95% confidence interval from 3.6 to 25.0. This interval is entirely positive under the recalculation’s contrast direction. Its limits still span a range of possible mean differences, so the point estimate should not be read as an exact value for the underlying difference.

Confidence intervals are useful because they pair an estimate with its statistical uncertainty. In general, the interval is not a guarantee that the true value lies within its limits, nor does it describe the range of individual participants’ scores. The standard deviations reported for the groups describe individual score variation, while confidence intervals describe uncertainty around a calculated estimate.

The registry’s sponsor analysis reports a mean difference of 4 and p = 0.001, with a 95% confidence level but no confidence limits. Its precision therefore cannot be assessed from the interval width using the registry record. The unadjusted recalculated intervals are not a replacement for that missing sponsor-model interval, because the results come from different analyses. Since the discrepancy is true, the sponsor’s own analysis takes precedence.

Precision is also constrained by the reported group sizes: the treatment-period groups range from 8 participants to 12 participants. These counts are not a substitute for the paired participant-level information needed to characterize a crossover analysis. The registry does not report the covariance between a participant’s scores in the two periods or other details that would permit an independent assessment of the sponsor model’s uncertainty.

11. Planning a Similar Trial: Sample Size

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

The planning figures are participants per arm, not total events. The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between two arms, a normal approximation, and an effect to detect set to a stated fraction of the observed effect. These are planning illustrations based on the observed effect, not the trial’s original design assumptions; the original sample-size justification is not reported in the registry record.

For the comparison involving the thalidomide-first sequence, planning for 100% of the observed effect gives 50 participants per arm for 80% power and 67 participants per arm for 90% power. Planning for 75% of the observed effect gives 89 participants per arm for 80% power and 119 participants per arm for 90% power. Planning for 50% of the observed effect gives 199 participants per arm for 80% power and 267 participants per arm for 90% power.

For the comparison involving the placebo-first sequence, the corresponding figures are 13 and 18 participants per arm for 100% of the observed effect, 23 and 31 for 75% of the observed effect, and 52 and 69 for 50% of the observed effect, for 80% and 90% power respectively.

In plain terms, the 80% and 90% columns describe the planned chance of detecting the specified effect under the listed assumptions if that effect is present. The 90% target requires more participants than the 80% target for each listed comparison and effect fraction. Smaller effects need more participants to detect than larger effects. These figures are not observed power and do not describe the chance that the trial’s result is correct.

12. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = 7.900; pooled standard deviation σ = 14.054.
2. n = 2 × (1.96 + 0.842)² × 14.054² / 7.900² = 49.7, rounded up to 50 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
delta <- 7.90000000000001                      # observed difference in means
sigma <- 14.0543587544932                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^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 (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(600028)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 50 (80% power), 67 (90% power)
 75% of observed effect: n per arm = 89 (80% power), 119 (90% power)
 50% of observed effect: n per arm = 199 (80% power), 267 (90% power)
power.t.test: 50.7 
Simulated power at n = 50 per arm: 0.792 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

13. Analyses Reported by the Sponsor

The registry reports the sponsor’s analysis as a mixed-model analysis of final values for the thalidomide-first and placebo-period groups. It gives a mean difference of 4 and p = 0.001, and lists a 95% confidence level. Confidence limits for this sponsor estimate are not reported in the registry record.

The recalculated comparisons are simple, unadjusted contrasts derived from posted group means and standard deviations. They are not the same as the sponsor’s mixed model. The recalculated mean differences are 7.9 and 14.3, with unadjusted p-values of 0.169 and 0.009. The estimate and p-value for the sponsor analysis therefore differ from the corresponding unadjusted recalculation results.

These differences may reflect differences in the analysis approach, but the registry does not report the model specification or sufficient details to explain the discrepancy. It would be inappropriate to assume which model terms, participant-level correlations, or other features account for it. The recalculated comparisons also should not be presented as a correction to the sponsor’s result.

Because the registry identifies a discrepancy, the sponsor’s own analysis takes precedence as the trial’s reported analysis. The unadjusted recalculations can still help readers understand how the posted group summaries compare, but they do not replace the trial analysis. The sponsor’s reported p-value does not convey the size or clinical importance of the result, and the missing confidence limits restrict assessment of the sponsor estimate’s precision.

14. Multiplicity, Missing Data and Analysis Populations

The registry lists two outcome measures and two analyses. It identifies the CQLQ as the primary outcome and describes a secondary outcome using the Visual Analog Scale of Cough and the St. George Respiratory Questionnaire. Numerical secondary-outcome results are not reported in the registry record. It is therefore not possible to assess the pattern of results across those measures from the posted numerical findings.

When multiple outcomes or analyses are examined, the chance of observing at least one apparently unusual result can increase. Statistical methods may account for multiple comparisons, but whether and how that was done is not reported in the registry record. The registry also does not report an analysis hierarchy or details of any prespecified multiplicity procedure. The reported p-values should consequently be understood as presented, without assuming a multiplicity adjustment.

The efficacy population is described as participants who received interventions and completed all study visits. The registry does not report detailed counts for each stage of follow-up or explain how missing CQLQ observations were handled. It does not report whether missing values were imputed, excluded, or addressed through another method. The amount and pattern of missing outcome data are also not reported in the registry record.

These omissions matter because incomplete follow-up can affect both the population represented by an analysis and the uncertainty of its estimates. A complete-case analysis, as described in broad terms by the registry’s efficacy-population definition, is not automatically biased, but its interpretation depends on why participants did or did not complete visits. The registry does not provide that information.

The record does not report the original sample-size justification, interim analyses, a full statistical analysis plan, or details of the mixed-model specification. It is not possible to determine whether the reported analyses followed a prespecified plan or how the model handled the crossover features. These are limitations in what can be evaluated from the registry record, not evidence that a particular analytic choice was or was not made.

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 non-serious adverse event terms

The registry reports serious adverse event counts for 23 participants at risk in the thalidomide group and 23 at risk in the placebo group. It reports 0 serious adverse events in each group. No serious adverse-event terms are listed. Deaths are not reported in the registry record.

The registry also reports other adverse events for 8 of the 23 participants at risk in the thalidomide group and 1 of the 23 participants at risk in the placebo group. The record does not give further detail in this summary about the event types, severity, timing, or whether participants experienced more than one event. The counts should be read as reported and not converted into percentages or interpreted as a comparison adjusted for the crossover design.

These figures summarize the adverse-event information in the registry and do not establish that no unreported events occurred. The number at risk and the recorded event counts are distinct from the enrollment total and from the efficacy analysis counts. The record does not provide a detailed safety-analysis population or explain how adverse events were collected across the treatment periods.

In general, adverse-event summaries describe events observed and recorded during a study; they do not by themselves determine whether an event was caused by an intervention. The registry’s brief counts do not provide enough detail to characterize the nature or timing of the other adverse events.

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

The primary endpoint is a cough-specific quality-of-life score for which lower values indicate less effect of cough on health-related quality of life. In the reported treatment-period means, the thalidomide-period means are lower than the placebo-period means in each sequence. That pattern is descriptive: the group means do not by themselves account for all features of the crossover design.

The registry also reports a sponsor mixed-model result of mean difference 4 with p = 0.001. Its 95% confidence limits are not reported in the registry record. The unadjusted recalculations produce different estimates and p-values, so the sponsor analysis takes precedence as the trial’s own reported analysis. The registry does not give enough model detail to explain the discrepancy.

These results do not establish how large a change would matter to participants. The registry does not report a clinically important-change threshold for the CQLQ. A statistically small p-value is not a measure of clinical importance, and an observed average does not describe every participant’s experience. Nor does the CQLQ capture every aspect of idiopathic pulmonary fibrosis, cough, or health.

The findings also do not resolve uncertainty about missing data, the handling of period and sequence effects, or the full analysis population. The efficacy analysis is described as including participants who completed all study visits, but the registry does not provide a detailed account of missing observations or the model specification. The listed secondary measures do not have numerical results in the registry record.

Accordingly, the posted results describe CQLQ scores and a sponsor analysis from this completed crossover trial. They should not be extended to outcomes that were not reported or to populations beyond the participants studied without additional evidence. This statistical reading is not medical advice and does not determine an individual treatment decision.

17. Why This Trial Matters Statistically

This trial is statistically notable because it uses a randomized, double-blind crossover design for a symptom-focused outcome. Participants were assigned to receive both thalidomide and placebo in different orders, with a washout period between treatment periods. This structure makes the choice of analysis important: comparisons that use only group summaries may not account for the relationship between measurements from the same participant or the ordering of treatment periods.

The registry presents both a sponsor mixed-model result and enough summary data for unadjusted recalculations. Their estimates and p-values differ. That contrast illustrates a central principle of statistical interpretation: estimates are tied to the analysis that produced them. A simple recalculation is not a substitute for the trial’s reported model, particularly when the model specification and participant-level data are not reported.

The endpoint also emphasizes the distinction between statistical evidence and practical meaning. The CQLQ measures cough’s effect on quality of life, and its direction is clear: lower scores indicate less effect. However, the registry does not give a threshold for a clinically important change. A p-value alone cannot establish whether an average difference is meaningful to participants.

Finally, the planning illustrations make clear how assumed effect size and desired power relate to sample-size planning. They are illustrations based on observed effects, not evidence about the trial’s original planning or a measure of what the completed study achieved. The record’s missing details on the original design assumptions, multiplicity, missing data, and model specification limit how fully readers can evaluate the analysis.

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 registry does not report the full specification of the sponsor’s mixed model, including how the crossover structure, treatment order, or period were handled. The unadjusted recalculations are not paired participant-level analyses and cannot resolve those methodological details. Because the recalculated and sponsor results differ, the recalculated contrasts should not be used as a replacement for the sponsor analysis.

The sponsor result is reported with a 95% confidence level, but its confidence limits are not reported in the registry record. This prevents direct assessment of the precision of the sponsor estimate from the registry entry. The original sample-size justification and the trial’s own design assumptions are also not reported; the available planning illustrations are not a record of the original design.

The registry describes the efficacy population as participants who received interventions and completed all study visits, but does not provide detailed participant flow or explain missing outcome-data handling. It does not report the number or pattern of missing CQLQ scores, or the method used to address them. This limits assessment of how well the analyzed participants represent everyone enrolled.

Only the primary endpoint has numerical results described in the posted data. The registry lists cough measured with a Visual Analog Scale and the St. George Respiratory Questionnaire as secondary measures, but their numerical findings are not reported in the registry record. No clinically important-change threshold for the CQLQ is reported either.

The safety summary is also limited: it gives adverse-event counts but not detailed event types, severity, timing, or causal assessment. Deaths are not reported in the registry record. These limitations define what can be concluded from the registry entry; they do not establish that unreported analyses or information do not exist elsewhere.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Treatment of Chronic Cough in Idiopathic Pulmonary Fibrosis With Thalidomide — NCT00600028.
• Registry record last updated 2017-05-15; status last verified 2017-04.
• Results first posted 2017-05-15.
• 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

This completed Phase III randomized, double-blind, placebo-controlled crossover trial enrolled 25 participants with idiopathic pulmonary fibrosis and chronic cough. Participants received thalidomide and placebo in opposite treatment orders, with each treatment period lasting 12 weeks and a two-week washout period between periods.

The primary endpoint was CQLQ score at 6 months, with lower scores indicating less effect of cough on health-related quality of life. The registry reports treatment-period means and a sponsor mixed-model analysis, alongside recalculated unadjusted contrasts that differ from the sponsor result. The sponsor analysis takes precedence as the trial’s own reported analysis; its confidence limits are not reported in the registry record.

The record lists secondary measures but does not report their numerical results. It also does not report the original sample-size justification, detailed missing-data methods, or the sponsor model specification. Serious adverse events were reported as 0 in each group at risk, while other adverse events were reported as 8 in the thalidomide group and 1 in the placebo group.