Pregabalin in Preventing Acute Pain Syndrome in Patients Receiving Paclitaxel: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Pregabalin in Preventing Acute Pain Syndrome in Patients Receiving Paclitaxel (NCT01637077), a randomized phase 2 study. The primary outcome is Worst of the Pain Scores for the Week Following the First Cycle of Paclitaxel Administration, Paclitaxel-associated Acute Pain Syndrome (P-APS) Pain Score.

2. Clinical Question

3. Trial Design

The registry describes a randomized, double-masked, parallel-group phase 2 pilot trial comparing pregabalin with placebo. It lists 46 participants enrolled and identifies the sponsor as Academic and Community Cancer Research United. The registry lists a start date of 2012-01, primary completion of 2013-11, and overall status of completed.

Participants in Arm I received pregabalin by mouth twice daily beginning on the first night of chemotherapy for 12 weeks, followed by once-daily dosing for 1 week. Participants in Arm II received placebo using the same schedule. The trial included questionnaire administration as well as the study drugs. The record's summary describes the study as examining pregabalin for preventing acute pain syndrome among patients receiving paclitaxel.

The primary outcome concerns the worst pain score for the week following the first paclitaxel cycle. The posted outcome groups include 19 participants in the pregabalin arm and 22 in the placebo arm. The registry does not report why these posted group sizes differ from the overall enrollment figure, or provide participant flow sufficient to explain the difference. The primary analysis population and the handling of participants without outcome data are not reported in the registry record.

The study lists 11 outcome measures and 14 analyses. The primary outcome is continuous, summarized by a mean and standard deviation. Secondary outcomes include pain ratings, use of non-prescription pain medication and opioids, new aches or pains attributed to paclitaxel, and adverse events. The record does not report the original sample-size justification, detailed randomization procedures, or a prespecified statistical analysis plan.

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:

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 Worst of the Pain Scores for the Week Following the First Cycle of Paclitaxel Administration, Paclitaxel-associated Acute Pain Syndrome (P-APS) Pain Score, measured over From treatment initiation to 6 days following treatment initiation; up to 7 days.

The primary endpoint is the worst of the pain scores reported for the week after the first paclitaxel administration. Participants recorded pain using a daily post-paclitaxel questionnaire. The stated assessment covers the first 6 days following treatment initiation, with a timeframe described as up to 7 days. Scores range from 0, indicating no aches or pains, to 10, indicating aches or pains as bad as can be; higher scores represent more pain.

Using the worst score focuses on the most intense reported pain during the assessment period, rather than the average across daily ratings. This can be relevant when a symptom varies from day to day, although it does not by itself describe how long pain lasted, when it occurred, or how much pain participants experienced on other days. Those aspects require other summaries or outcomes.

The primary outcome is a continuous measure, reported as a mean and standard deviation for each arm. The observed means were 2.6 for pregabalin and 3.2 for placebo. A mean gives a group-level average, while the standard deviation describes the spread of individual scores around that average. Neither statistic alone describes every participant's experience. The registry record does not report a threshold for what would count as an important difference on this scale.

7. Results Posted in the Registry

• Arm I (Pregabalin): mean 2.60 versus 3.20 on control; difference -0.60 (95% CI -2.28 to 1.08), standardized effect d = -0.22; z-test p = 0.485.

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.

The Percentage of Patients Who Use Non-prescription Pain Medications

• 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 I (Pregabalin): 52.6% (10/19) versus 50.0% (11/22) on control; risk difference 2.6 percentage points (95% CI -28.0 to 33.3), risk ratio 1.05 (0.58–1.91); unadjusted two-proportion z-test p = 0.867.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Arm I (Pregabalin) and the control. The interval gives the range of effects that remain compatible with the data.

The Percentage of Patients Taking Opioid Medications

• 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 I (Pregabalin): 15.8% (3/19) versus 18.2% (4/22) on control; risk difference -2.4 percentage points (95% CI -25.4 to 20.6), risk ratio 0.87 (0.22–3.40); unadjusted two-proportion z-test p = 0.839.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Arm I (Pregabalin) and the control. The interval gives the range of effects that remain compatible with the data.

The Percentage of Patients Who Report the Development of New Aches/Pains That They Attribute to Paclitaxel

• 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 I (Pregabalin): 21.1% (4/19) versus 59.1% (13/22) on control; risk difference -38.0 percentage points (95% CI -65.6 to -10.5), risk ratio 0.36 (0.14–0.91); unadjusted two-proportion z-test p = 0.014.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically lower for Arm I (Pregabalin) than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcomes cover several related but distinct aspects of acute pain and treatment experience: medication use, new aches or pains attributed to paclitaxel, pain ratings, and adverse events. Across those measures, the pattern is not uniformly one of lower reported symptoms or lower medication use in the pregabalin arm. The secondary results therefore add context rather than forming a single consistent confirmation of the primary pain-score comparison.

The outcome concerning new aches or pains attributed to paclitaxel is notable in relation to the primary endpoint because it addresses whether participants reported the development of symptoms, whereas the primary endpoint measures the worst pain score over a defined period. A difference on one measure does not necessarily imply a comparable difference on another. Differences in outcome definition, reporting, and timeframe can produce different patterns without a logical contradiction.

Medication-use outcomes likewise reflect behavior as well as symptoms. Use of non-prescription pain medication and use of opioids are not direct substitutes for a daily pain score; they can be influenced by access, preference, clinician decisions, and other factors that are not described in the registry record. The record lists additional pain-rating outcomes, but complete arm-level results for every secondary measure are not included in the posted results summarized in the record.

Unadjusted secondary results carry less weight than a prespecified primary analysis when several outcomes and analyses are available. Testing many outcomes increases the likelihood of at least one result appearing statistically notable by chance. The registry does not report a multiplicity adjustment or a hierarchy identifying which secondary outcomes were confirmatory. Consequently, secondary comparisons are useful for generating hypotheses and understanding the range of measured outcomes, but should not be treated as independent definitive proof of a treatment effect.

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

• Area Under the Curve Per Assessment (aAUCpa) of Worst, Average and Least Pain (Items 1-3 Appendix IV) for the First Cycle of Treatment.
• Percentage of Participants With Grade 3 or Higher Adverse Events Considered At Least Possibly Related to Treatment
• The Percentage of Patients Who Use Non-prescription Pain Medications
• The Percentage of Patients Taking Opioid Medications
• The Percentage of Patients Who Report the Development of New Aches/Pains That They Attribute to Paclitaxel
• The Worst Pain Reported at the End of the Week for the Overall Week (Item 2 Appendix V)
• The Percentage of Patients Who Report, at Week's End, Using Non-prescription Pain Medications
• The Percentage of Patients Who Report, at Week's End, Using Opioids

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is a continuous pain score, and the posted arm summaries are means with standard deviations. A mean is the arithmetic average across the participants in an arm. The standard deviation describes how dispersed individual scores are around that mean. When a scale is bounded, as this score is from 0 to 10, the mean and standard deviation still provide a concise summary, but they do not show the full distribution, including whether scores cluster at particular values or whether there are unusual observations.

What does a mean difference express?

The unadjusted recalculation compares the pregabalin mean of 2.6 with the placebo mean of 3.2. Its estimated mean difference is -0.6 points, expressed as pregabalin relative to placebo. A negative estimate means the observed average score was lower in the pregabalin group. This is a descriptive contrast in the posted summaries, not proof that the intervention caused a difference. Randomization supports fair comparison in principle, but precision, conduct, outcome availability, and analysis choices still affect interpretation.

The recalculated confidence interval for the mean difference extends from -2.284 to 1.084. A confidence interval is a range of values compatible with the data under the assumptions of the calculation. In repeated use of the same procedure, intervals constructed this way would cover the underlying quantity at their stated confidence level at the corresponding rate. It is not a probability statement that the fixed true effect lies within this particular interval. Because this interval includes zero, the data do not distinguish clearly between a negative mean difference, no difference, and a positive mean difference.

Why are there two primary p-values?

The registry reports a Kruskal-Wallis test with p = 0.56. The recalculation reports an unadjusted mean-difference p-value of 0.485. These results come from different methods. The recalculated comparison uses the arm means and standard deviations to estimate a mean contrast. The Kruskal-Wallis test is a rank-based comparison that evaluates differences in the distributions of ranked observations; it is not a direct test of the difference between means. Therefore, the p-values need not match, and neither should be presented as if it were the other method's result.

A p-value describes how unusual data at least as incompatible with a specified null hypothesis would be under the assumptions of a statistical test. It is not the probability that the null hypothesis is true, nor does it measure the size or clinical importance of a difference. A larger p-value does not establish that the groups are equivalent. The size and precision of the estimated effect, the study design, and the relevance of the outcome all matter alongside a p-value.

How should secondary comparisons be read?

The registry reports chi-squared tests for the listed secondary binary outcomes, including pain-medication use and new aches or pains attributed to paclitaxel. A chi-squared test compares the observed category counts with the counts expected under a null hypothesis of no group association. The recalculated risk difference describes the absolute difference between group proportions, while a p-value from a chi-squared test addresses compatibility with the null under the test's assumptions. These are related but distinct summaries.

For binary outcomes, a percentage can be easier to interpret than a test result, but the percentage alone does not communicate uncertainty. The arm sizes are modest, so individual observations can have a substantial influence on the observed proportions. A confidence interval gives a range of plausible values for the contrast under its method and assumptions. Wide intervals indicate limited precision. For some recalculated binary comparisons, the posted interval endpoints contain more than three decimal places; those values are not repeated in the narrative. The registry's own p-values remain the reported analyses, while recalculations are unadjusted descriptive comparisons.

Multiplicity is relevant because the registry lists 11 outcome measures and 14 analyses. When many outcomes are tested, the chance of at least one nominally small p-value can increase even if no underlying effects exist. An adjustment or a clear hierarchy of confirmatory outcomes can address that issue, but the multiplicity plan is not reported in the registry record. Thus, individual secondary p-values should not be interpreted in isolation as if each were the sole planned test.

What does over-dispersion mean in general?

General statistical context: over-dispersion occurs when observed variability exceeds what a model assumes. In count or binary-data models, this can make standard errors too small and confidence intervals too narrow if not addressed. The registry record does not identify over-dispersion as an issue in this trial, nor does it describe a model-based adjustment for it. The concept is useful for understanding why checking model assumptions matters, but it should not be taken as a finding about this study.

The posted primary comparison uses a continuous outcome, but its analysis assumptions are not fully described. The recalculated mean difference is an unadjusted comparison based on the posted summary statistics. It does not account for covariates, changes over time, or unreported aspects of the design. The registry record does not report an adjusted primary estimate, a detailed plan for handling missing observations, or a full analysis population definition.

11. Confidence Intervals and Precision

The primary mean difference is -0.6 points, with a 95% confidence interval from -2.284 to 1.084. The interval is wide enough to include values on both sides of zero. It therefore conveys substantial uncertainty about the direction and size of the underlying mean contrast. The observed difference should not be read as a precise estimate of what would occur in a larger population.

Confidence intervals describe uncertainty in an estimated quantity, conditional on the data and the assumptions of the method used. The primary recalculated interval is based on the posted arm summaries and is unadjusted. It does not incorporate any adjustment for other variables or account for missing-data processes that are not described in the registry record. The interval's interpretation depends on the suitability of the underlying method and the completeness of the summarized data.

The arm standard deviations, 2.5 for pregabalin and 3.0 for placebo, indicate that individual scores varied around the group means. In a study with modest outcome group sizes, that variability limits how narrowly the group difference can be estimated. The registry's primary analysis is a Kruskal-Wallis test, which does not provide a confidence interval in the posted results. Accordingly, the interval attached to the mean difference belongs to the unadjusted recalculation, not to the registry's reported rank-based test.

The registry does not report a threshold for a clinically important difference on the pain scale. Statistical uncertainty can be described, but the importance of any particular value within the interval cannot be established from the record alone. The secondary outcomes also have uncertainty, and their interpretation is further complicated by multiple outcomes and unavailable details about the analysis plan.

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 sample-size planning figures are illustrations based on the observed effect, not the trial's original design calculation. For the continuous primary outcome, the figures refer to participants per arm. The planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation; the target effect is the stated fraction of the observed effect. The trial's own original sample-size assumptions and justification are not reported in the registry record.

The 80% power column describes the number of participants per arm that the planning calculation estimates would be needed for an 80% chance of detecting the specified effect under the stated assumptions, if that effect were the true effect and the analysis followed those assumptions. The 90% power column gives the corresponding per-arm planning figure for a 90% chance. These are design-planning quantities, not guarantees about what a future study will find.

The illustrations include planning for 100%, 75%, and 50% of the observed effect. Smaller target effects require more participants because a less pronounced group difference is harder to distinguish from random variation. For example, planning for 75% of the observed effect requires more participants per arm than planning for the full observed effect. The same pattern holds for planning for 50% of the observed effect.

These calculations do not describe the power of the completed trial and are not observed power. They also do not establish that the observed effect is a reliable estimate for planning a future study. Because the observed effect comes from a pilot trial, using it as the basis for planning can be uncertain. The figures are best read as conditional illustrations of how sample size changes with the assumed effect, rather than as a recommended enrollment target.

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, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -0.600; pooled standard deviation σ = 2.780.
2. n = 2 × (1.96 + 0.842)² × 2.780² / -0.600² = 337.1, rounded up to 338 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 <- -0.6                      # observed difference in means
sigma <- 2.7804260879889                     # 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(1637077)
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 = 338 (80% power), 452 (90% power)
 75% of observed effect: n per arm = 600 (80% power), 803 (90% power)
 50% of observed effect: n per arm = 1,349 (80% power), 1,806 (90% power)
power.t.test: 338.1 
Simulated power at n = 338 per arm: 0.803 (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.

14. Analyses Reported by the Sponsor

The registry's reported primary analysis is a Kruskal-Wallis test, with p = 0.56. The unadjusted recalculation based on the posted means and standard deviations estimates a mean difference of -0.6 points, with a 95% confidence interval from -2.284 to 1.084 and p = 0.485. These values are not competing versions of an identical calculation: the registry reports a rank-based test, while the recalculation estimates and tests a difference in means.

The registry result should be understood as the sponsor's posted analysis for the primary endpoint. The recalculated mean contrast adds a complementary summary of the posted group means and its uncertainty, but it does not replace the reported analysis or establish what the original analysis plan specified. The registry record does not report enough detail to reconstruct the full analysis procedures beyond the named test and p-value.

For the secondary outcomes, the registry reports chi-squared p-values. Recalculated comparisons use the posted group summaries and are unadjusted. Differences between these values can arise from method, rounding, or the exact data used in each analysis; the record does not provide enough detail to attribute any particular difference to one cause. The primary discrepancy flag is false, so there is no identified conflict requiring the sponsor's own result to be displaced by a recalculation.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists 11 outcome measures and 14 analyses, including the primary pain-score comparison and multiple secondary outcomes. Each statistical test addresses a particular question, but the interpretation of a group of tests differs from interpretation of a single prespecified test. When many tests are performed, the chance of finding at least one result with a small p-value by random variation is greater than for a single test. This is why a multiplicity strategy, such as adjusting the threshold or defining a hierarchy of hypotheses, can matter.

The multiplicity plan is not reported in the registry record. It is therefore unclear whether the secondary analyses were intended as exploratory, whether any adjustment was planned, or whether the ordering of outcomes was specified in advance. The registry's posted p-values should be read as the results of individual comparisons, not as evidence that the overall family of outcomes has controlled error rates.

Missing-data handling is also not reported in the registry record. The overall enrollment is 46, while the primary outcome summaries include 19 participants in the pregabalin group and 22 in the placebo group. The record does not explain the difference between enrollment and the posted primary outcome group sizes, report reasons for unavailable outcomes, or describe an imputation method or sensitivity analysis. Without that information, it is not possible to assess whether missingness could have affected the estimates.

The analysis population is not reported in sufficient detail to determine whether participants were analyzed according to randomized assignment, whether any were excluded after randomization, or how protocol deviations were handled. The randomization and masking are listed, but procedural details are not reported in the registry record. These omissions do not demonstrate that the analyses were biased; they limit the ability to evaluate the protections against bias and the robustness of the findings.

The posted summaries also do not identify whether all planned outcome timepoints and analyses are represented. The registry lists outcomes over different periods, but a comprehensive statistical analysis plan and complete outcome reporting are not reported. These limitations support a cautious interpretation of nominal secondary findings and prevent a full assessment of selective reporting or analysis flexibility.

16. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 0% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: hyponatremia (4.8%), cognitive disturbance (4.8%), constipation (4.5%).

The posted serious adverse event figures show 1 affected participant among 21 at risk in the pregabalin arm and 1 among 22 at risk in the placebo arm. The registry reports 0 deaths in each arm. These counts describe the posted safety summaries; they do not establish that the groups have the same underlying risk, particularly given the limited number of participants.

Other adverse events are reported for 15 of 21 participants at risk in the pregabalin arm and 21 of 22 in the placebo arm. Serious and other adverse events are distinct categories in the registry record, and the figures should not be combined. The record lists hyponatremia, cognitive disturbance, and constipation among the top serious adverse event terms, each with a reported percentage. It does not provide enough detail in these summaries to attribute those terms to a particular arm or establish a causal relationship with treatment.

Safety counts require context about definitions, observation time, event severity, and assessment procedures. Those details are not reported in the registry record. The figures therefore describe reported events among participants at risk, not a complete comparative safety analysis or an estimate of an underlying event rate with precision.

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

The primary outcome results show that the observed mean worst pain score was 2.6 in the pregabalin arm and 3.2 in the placebo arm during the week after the first paclitaxel cycle. The unadjusted recalculated mean difference was -0.6 points, but its 95% confidence interval, from -2.284 to 1.084, includes values indicating lower scores in either arm as well as no difference. The result is therefore uncertain and does not provide a precise estimate of the group contrast.

The registry's primary analysis reports a Kruskal-Wallis p-value of 0.56. A p-value of this kind does not tell whether the null hypothesis is true, nor does it establish equivalence between treatments. The mean-difference calculation and the registry's rank-based test use different methods, so both should be described according to what they measure rather than treated as interchangeable.

One secondary outcome reports a difference in the percentage of participants who described new aches or pains as attributable to paclitaxel, with a nominally small reported p-value. That outcome is not the same as the primary worst-pain score, and the trial lists multiple outcomes and analyses. The multiplicity plan is not reported, and the secondary result should be interpreted cautiously rather than taken as a definitive conclusion.

The trial is described as a pilot and has modest posted arm sizes for the primary endpoint. The registry record also does not explain the difference between enrollment of 46 and the primary outcome group sizes, or report the handling of missing data. Those gaps limit the assessment of precision and potential bias. Overall, the posted results describe a comparison and its uncertainty; they do not establish a treatment recommendation or prove that one group had a reliably different clinical outcome.

18. Why This Trial Matters Statistically

This trial illustrates why a point estimate and its uncertainty should be read together. The observed mean difference is -0.6 points, but the 95% confidence interval from -2.284 to 1.084 spans values on both sides of zero. Looking only at the direction of the observed means would miss how uncertain the contrast is.

It also illustrates that different statistical tests can address related, but not identical, questions. The registry's Kruskal-Wallis test is rank-based, whereas the recalculation summarizes a difference in means. The corresponding p-values, 0.56 and 0.485, are not required to match. Stating each method clearly helps prevent a p-value from being mistaken for an effect estimate or a measure of clinical importance.

The secondary outcomes show why outcome definitions matter. A pain score, reported development of new aches or pains, and use of pain medication each capture different facets of experience. A result on one measure does not automatically answer the question addressed by another. The presence of multiple endpoints also makes multiplicity and selective reporting relevant to interpretation.

Finally, the difference between overall enrollment and the outcome-specific group sizes highlights the value of transparent participant flow and missing-data reporting. Without that context, readers cannot fully judge which participants contributed to each estimate. These are general lessons in interpreting a pilot trial: distinguish descriptive observations from confirmatory evidence, attend to uncertainty, and evaluate how completely the analysis is documented.

19. 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.

This trial's pilot designation and posted primary outcome group sizes constrain the precision of the comparison. The confidence interval for the recalculated mean difference is broad and includes both directions of effect. The registry does not report a threshold for an important difference on the 0-to-10 pain scale, so the clinical importance of possible values within that interval cannot be determined from the record.

Participant accounting is incomplete in the posted record. Enrollment is 46, while the primary outcome summaries include 19 participants in the pregabalin group and 22 in the placebo group. Reasons for the difference, participant flow, and the primary analysis population are not reported. Missing-data methods and sensitivity analyses are also not reported in the registry record.

The registry identifies randomization and double masking but does not report details of sequence generation, allocation concealment, masking assessment, or protocol adherence. The original sample-size justification and a full statistical analysis plan are not reported. The record also does not report how multiplicity was handled across 11 outcome measures and 14 analyses. These omissions make it difficult to evaluate the prespecification of secondary analyses and the robustness of their nominal p-values.

Some registry outcomes are listed without complete arm-level results in the posted data. The timeframes differ across outcomes, and measures such as pain scores, symptom attribution, and medication use are not directly interchangeable. Safety summaries provide counts, but details about event definitions, follow-up, and attribution are not reported. These limitations do not determine the direction of any bias, but they restrict what can be concluded from the available results.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Pregabalin in Preventing Acute Pain Syndrome in Patients Receiving Paclitaxel — NCT01637077.
• Registry record last updated 2018-04-06; status last verified 2018-04.
• Results first posted 2018-04-06.
• 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.

23. Record Summary

The registry record describes a completed, randomized, double-masked, parallel-group phase 2 pilot trial of pregabalin versus placebo for paclitaxel-associated acute pain syndrome. It lists enrollment of 46 and a primary outcome measuring the worst pain score during the week following the first paclitaxel cycle.

The posted primary means were 2.6 for pregabalin and 3.2 for placebo. The unadjusted recalculated mean difference was -0.6, with a 95% confidence interval from -2.284 to 1.084; the registry reports a Kruskal-Wallis p-value of 0.56. Secondary outcomes include pain medication use, new aches or pains attributed to paclitaxel, and adverse events. Details about missing data, the analysis population, multiplicity, and the original sample-size justification are not reported in the registry record.