Efficacy and Safety Study of Buprenorphine HCl Buccal Film in Subjects With Low Back Pain: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Efficacy and Safety Study of Buprenorphine HCl Buccal Film in Subjects With Low Back Pain (NCT01256450), a randomized phase 3 study. The primary outcome is Change in Pain Intensity From Baseline to Week 12.

2. Clinical Question

3. Trial Design

The registry describes a Phase 3, randomized, parallel-group study with quadruple masking. Its official title calls it a 12-Week, placebo-controlled, double-blind, randomized withdrawal study; the brief title identifies buprenorphine HCl buccal film and low back pain. The record lists the study as completed, with an enrollment of 334. The listed start is 2010-11 and primary completion is 2011-07.

The active arm received buprenorphine buccal soluble film and the comparator arm received placebo buccal soluble film. The double-blind treatment groups in the primary outcome are DB Buprenorphine HCl Buccal Film and DB Placebo Film. The registry record does not report the exact randomization ratio, the allocation sequence procedure, the precise masking roles, the dose regimen, or detailed treatment-phase procedures. Although the official title uses the term randomized withdrawal, the record does not provide enough procedural detail to describe how withdrawal or entry into the double-blind phase was implemented.

The primary outcome is change in pain intensity from baseline to Week 12, summarized as a mean with standard deviation. The primary analysis population is described as all randomized subjects who received at least 1 dose of double-blind study medication. The record also lists secondary outcomes covering pain ratings over time, treatment response and failure, subject impressions, satisfaction, and disability. The registry lists 10 outcome measures and 9 posted secondary outcomes. Their availability does not establish that every listed measure was analyzed in the same population or under the same statistical procedures; such details 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.

Before assignment: Of 334 subjects who were enrolled in the open-label (OL) titration phase; a total of 235 completed the open-label titration phase and were randomized in the double-blind (DB) treatment phase.

Open-label Titration

Reasons for not completing this period:

Double-blind Treatment

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Analysis based on Intent-to-Treat (ITT) population; all randomized subjects who received at least 1 dose of double-blind study medication.

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.

Population: Analysis based on Randomized population; all subjects who were randomized into the double-blind period, even if study drug was not taken in the period

6. Primary Endpoint

The registry lists the primary outcome as Change in Pain Intensity From Baseline to Week 12, measured over Baseline, Week 12.

The primary endpoint measures the change in average daily pain intensity between the period before randomization and the period before the Week 12 visit. Pain was rated on an 11-point numeric rating scale, from 0 for no pain to 10 for the worst pain imaginable. For each period, the endpoint uses the average of daily ratings from the last 7 days. The change is defined as the Week 12-period average minus the baseline-period average. A negative change indicates that the recorded average was lower at Week 12 than at baseline; the endpoint comparison asks whether that change differed between groups.

A continuous endpoint retains the degree of change rather than reducing the result to a yes-or-no response. Reporting a mean and standard deviation describes the group’s average change and the spread of individual changes around that average. The registry identifies the primary population as randomized subjects who received at least 1 dose of double-blind study medication. The endpoint is used to assess the trial’s stated efficacy question at a specified follow-up point. It does not, by itself, describe every participant’s experience, establish the importance of a particular change to patients, or answer safety questions. The registry record does not report a threshold defining a clinically important change in this measure.

7. Results Posted in the Registry

• DB Buprenorphine HCl Buccal Film: mean 0.33 versus 0.46 on control; difference -0.13 (95% CI -0.65 to 0.39), standardized effect d = -0.06; z-test p = 0.622.

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.

Percentage of Participants With Treatment Failure in the Double-blind Treatment Phase (up to 12 Weeks)

• 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:
  • DB Buprenorphine HCl Buccal Film: 9.4% (11/117) versus 11.9% (14/118) on control; risk difference -2.5 percentage points (95% CI -10.3 to 5.4), risk ratio 0.79 (0.38–1.67); unadjusted two-proportion z-test p = 0.540.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between DB Buprenorphine HCl Buccal Film and the control. The interval gives the range of effects that remain compatible with the data.

Subject Impression of Change in Pain Intensity From Baseline to Week 12 Using PGIC Scale

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • DB Buprenorphine HCl Buccal Film: mean -0.32 versus -0.92 on control; difference 0.60 (95% CI 0.06 to 1.14), standardized effect d = 0.29; z-test p = 0.029.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for DB Buprenorphine HCl Buccal Film than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change From Baseline to Week 12 in Roland Morris Disability Questionnaire

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • DB Buprenorphine HCl Buccal Film: mean 0.09 versus 1.00 on control; difference -0.91 (95% CI -2.19 to 0.37), standardized effect d = -0.18; z-test p = 0.164.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between DB Buprenorphine HCl Buccal Film and the control. The interval gives the range of effects that remain compatible with the data.

The posted secondary outcomes cover several related but distinct aspects of the study: pain intensity over time, response and treatment failure, subject impression of pain change, treatment satisfaction, disability, and overall satisfaction with study drug. Their measures include continuous scores and participant percentages. This range can add context to the primary pain-intensity comparison, but these outcomes are not interchangeable. They may reflect different constructs, time points, scales, and analysis procedures.

Among the posted secondary results, the calculated comparisons do not all point in the same direction or offer the same degree of precision. One unadjusted comparison has a p-value of 0.029, while other posted comparisons have intervals that include zero. These are exploratory signals rather than a uniform pattern that independently confirms the primary result. The registry record does not report adjusted analyses for these outcomes or a plan for controlling the chance of false-positive findings across multiple comparisons.

Unadjusted secondary results carry less weight when many outcomes are examined because, in general, conducting multiple tests increases the chance that at least one result will appear notable by chance. That general concern does not prove that any particular finding is false; it means the result needs to be interpreted with the full analysis plan and the other evidence. The registry record does not report the number of analyses planned in advance, a hierarchy among secondary endpoints, or a multiplicity procedure. The secondary outcomes can therefore describe patterns worth considering, but they should not be treated as equivalent to a prespecified, multiplicity-controlled primary conclusion. Their results also do not repair uncertainty in the primary estimate.

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

• Change From Baseline in Pain Intensity Over Time Using NRS Scale
• Number of Participants With Response to Treatment as Assessed by an NRS Scale
• Percentage of Participants With Treatment Failure in the Double-blind Treatment Phase (up to 12 Weeks)
• Subject Impression of Change in Pain Intensity From Baseline to Week 12 Using PGIC Scale
• Change From Baseline to Week 12 in Treatment Satisfaction Using TSQM
• Change From Baseline to Week 12 in Roland Morris Disability Questionnaire
• Change From Baseline to Week 12 in Subject's Overall Satisfaction With Study Drug
• Change From Baseline to Week 12 in Investigator's Overall Satisfaction With Study Drug

9. Statistical Interpretation

10. Statistical Methods Explained

What does the mean difference represent?

The primary endpoint is continuous, so its group summaries are means and standard deviations. The mean is the arithmetic average of participants’ endpoint values within a group. The standard deviation describes how dispersed those values are around the group mean; it is not the uncertainty in the estimated mean difference. The recalculated comparison subtracts the placebo mean from the buprenorphine mean. Under that stated ordering, a negative difference corresponds to a lower mean change in the buprenorphine group. Because the endpoint is defined as Week 12 minus baseline, a lower change means a greater decrease in the pain rating, but the size and clinical relevance of a change require context beyond the arithmetic direction.

What does an unadjusted comparison do?

The recalculation uses the posted group means, standard deviations, and group sizes to estimate a simple difference between group averages. It does not reproduce an analysis that adjusts for baseline or other covariates. In general, an unadjusted estimate is a direct comparison of the observed summary values, while an adjusted model estimates a group contrast conditional on the covariates included in that model. If the model and its assumptions are appropriate, adjustment can account for differences in those covariates; the registry record does not report the covariates or model details needed to assess that aspect of the sponsor’s analysis. The recalculation is therefore a descriptive statistical cross-check, not a substitute for the trial’s own analysis.

How should the confidence interval and p-value be read?

A confidence interval describes the range of values for the group contrast that are reasonably compatible with the data and the statistical model under its assumptions. A wide interval indicates less precision than a narrow interval. An interval containing zero means the data do not clearly distinguish a negative difference from zero or a positive difference at the corresponding confidence level. It does not prove that the groups are identical. A p-value evaluates how unusual the data would be under a specified null hypothesis and model. It is not the probability that the null hypothesis is true, and it does not measure the clinical importance of an effect. The unadjusted p-value is attached to the recalculated comparison; the trial’s reported analysis is an ANCOVA result.

Why can adjusted and unadjusted estimates differ?

ANCOVA is a general method for comparing group outcomes while accounting for covariates. In a trial, such a model may use baseline measurements or other prespecified variables, but the particular variables and implementation must not be assumed when they are not reported. Adjustment can change the estimated contrast and its standard error. Here, the registry’s estimate and the unadjusted recalculation are similar in direction and size, but their intervals are not identical. That difference is not evidence of an error by itself: the two calculations answer related questions using different methods. The registry’s analysis is the reported trial analysis and takes precedence over a simple recalculation from summary statistics.

What does variability add?

Participants can have quite different changes even when their group average is similar. The standard deviations describe that within-group variation. General statistical principle: greater variability makes it harder to estimate a group contrast precisely if other aspects of the study are held fixed. The standard error represents uncertainty in an estimate, rather than variation among individual participants. The recalculated comparison uses the posted group summaries to estimate uncertainty, whereas the ANCOVA standard error would depend on its model and data. Individual-level data are not reported in the registry record, so the distribution of responses, possible outliers, and the fit of alternative models cannot be examined from these summaries.

Why can over-dispersion matter for a count or binary outcome?

General statistical principle: a model can be too confident when the observed variability is greater than the model assumes. For binary outcomes, risks can vary among participants or across subgroups, and a simple model may not capture that heterogeneity. For continuous outcomes, unusually uneven spread or influential observations can also affect a mean-based analysis. The posted secondary summaries do not provide enough information to assess these features in detail. This is a general reason to interpret model-based intervals alongside the measurement definition and study design, rather than treating a single test result as a complete description.

What is the role of the analysis population?

The primary outcome description identifies an Intent-to-Treat population consisting of all randomized subjects who received at least 1 dose of double-blind study medication. This definition is specific: it does not describe all enrolled subjects regardless of exposure. General principle: analysis-population choices affect which participants contribute to an estimate and can affect the interpretation of randomization. The registry record does not report how missing Week 12 observations were handled, whether all eligible participants contributed endpoint data, or whether additional analysis populations were used. Those omissions limit assessment of potential bias arising from incomplete outcome data or exclusions.

11. Confidence Intervals and Precision

The recalculated primary mean difference is -0.13, with a 95% confidence interval from -0.646 to 0.386. The interval crosses zero, so the posted summaries are compatible with a lower mean change in the buprenorphine group, little or no difference, or a higher mean change. Its breadth indicates that the point estimate alone should not be treated as a precise estimate of the underlying group contrast. The registry’s reported ANCOVA estimate is -0.14, with a 95% confidence interval from -0.646 to 0.366. That interval also includes zero and leads to the same broad reading of uncertainty.

A confidence interval is not a range containing a fixed proportion of individual participants’ outcomes. It quantifies uncertainty about an estimated group contrast under the method’s assumptions. A narrow interval would indicate greater precision about that contrast; a wide interval leaves more plausible values unresolved. Neither interval establishes equivalence, and neither says that all clinically important differences have been ruled out. The registry record does not report a prespecified equivalence margin or a threshold for a clinically important difference, so those conclusions cannot be drawn from the intervals alone.

The unadjusted recalculation and the reported ANCOVA estimate are close, but they arise from different analyses. The recalculated interval is based on posted summary statistics; the ANCOVA interval reflects the sponsor’s model-based analysis. The model details are not reported in the registry record, so the sources of any difference in precision cannot be fully assessed. The point estimates and intervals should be interpreted together: the estimates are near zero, while the intervals preserve uncertainty about direction and magnitude.

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

For the primary continuous endpoint, planning for 100% of the observed effect gives 3,791 participants per arm for 80% power and 5,075 participants per arm for 90% power. Planning for 75% of the observed effect gives 6,740 participants per arm for 80% power and 9,023 participants per arm for 90% power. Planning for 50% of the observed effect gives 15,164 participants per arm for 80% power and 20,300 participants per arm for 90% power. Smaller effects need more participants to detect under the same planning assumptions.

In general, 80% power means that a study designed under the stated assumptions would have an 80% chance of detecting an effect of the chosen size using the specified test if that effect were the true one. The 90% column expresses the corresponding design probability at 90%. These are planning illustrations, not observed power; they do not describe the probability that the result is true or explain the result obtained in this completed trial. The original design rationale is not reported in the registry record.

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 = -0.130; pooled standard deviation σ = 2.020.
2. n = 2 × (1.96 + 0.842)² × 2.020² / -0.130² = 3,790.9, rounded up to 3,791 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 <- -0.13                      # observed difference in means
sigma <- 2.02019387694082                     # 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(1256450)
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 = 3,791 (80% power), 5,075 (90% power)
 75% of observed effect: n per arm = 6,740 (80% power), 9,023 (90% power)
 50% of observed effect: n per arm = 15,164 (80% power), 20,300 (90% power)
power.t.test: 3791.8 
Simulated power at n = 3,791 per arm: 0.801 (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 reports the trial’s own primary comparison as an ANCOVA mean difference (net) of -0.14, with a 95% confidence interval from -0.646 to 0.366. The recalculation from posted group summaries is an unadjusted mean difference of -0.13, with a 95% confidence interval from -0.646 to 0.386 and an unadjusted p-value of 0.622. The estimates are close, and both intervals include zero. This broad agreement supports the reading that the primary estimate is near zero relative to its uncertainty.

The two results should not be treated as identical analyses. The recalculation uses posted summary statistics and does not reproduce covariate adjustment. The registry’s ANCOVA is the sponsor-reported trial analysis and takes precedence over the recalculation. Details about the ANCOVA covariates, missing-data methods, and other model specifications are not reported in the registry record, so the adjusted analysis cannot be independently reconstructed from the stated information. The recalculation is useful as a simple check of the reported group summaries, but it cannot establish whether the sponsor’s model was appropriate or whether alternative analyses would give the same result. The registry record identifies no discrepancy flag for this comparison.

15. Multiplicity, Missing Data and Analysis Populations

The registry record does not report whether the analysis plan adjusted for multiple testing, defined a hierarchy among secondary outcomes, or treated any secondary endpoint as confirmatory. This matters because the record lists numerous secondary measures, including outcomes related to pain, treatment response, failure, satisfaction, and disability. General statistical principle: when many hypotheses are tested, the probability of at least one apparently unusual result can increase if no adjustment or prespecified testing strategy is used. An unadjusted p-value for a secondary outcome should therefore be read as a nominal result, not as definitive evidence on its own.

Missing-data procedures are also not reported in the registry record. The primary population is described as randomized subjects who received at least 1 dose of double-blind medication, but the record does not say how missing Week 12 scores were handled, whether participants with incomplete follow-up were excluded from a particular analysis, or whether imputation or another method was used. Missing outcome data can affect an estimate if the participants with observed outcomes differ systematically from those without observed outcomes. The posted group summaries alone do not establish whether missingness was balanced or whether the result would be sensitive to alternative assumptions.

The record reports ANCOVA for the primary comparison but does not specify its covariates, model diagnostics, or detailed assumptions. It also does not report interim analyses, stopping rules, or a statistical analysis plan. These omissions do not show that such procedures were absent; they mean their details are not available in the registry record. The outcome description gives an ITT label and eligibility wording, but the record does not report additional analysis populations or sensitivity analyses. As a result, the reported primary estimate can be described, while the robustness of that estimate to missing-data choices, model choices, and multiplicity cannot be fully assessed.

16. Safety Results

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

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: cerebrovascular accident (0.9%), pneumonia (0.3%), blood creatinine increased (0.3%), acute respiratory failure (0.3%).

The safety record presents serious adverse event counts and counts for other adverse events in separate groups. In the OL Buprenorphine HCl Buccal Film group, 1 of 330 was affected by a serious adverse event and 163 of 330 were affected by other adverse events. In the DB Buprenorphine HCl Buccal Film group, the serious adverse event count was 1 of 117 and the other adverse event count was 36 of 117. In the DB Placebo Film group, the serious adverse event count was 0 of 118 and the other adverse event count was 28 of 118. These are registry counts, not adjusted comparisons or estimates of causal risk.

The listed serious adverse event terms and percentages include CEREBROVASCULAR ACCIDENT at 0.9%, and PNEUMONIA, BLOOD CREATININE INCREASED, and ACUTE RESPIRATORY FAILURE at 0.3% each. The registry record does not report deaths in the posted safety summary. A count of zero in the placebo group does not establish that the underlying risk is zero, and group counts alone do not explain timing, severity, relatedness, or exposure duration. The record does not provide enough detail to compare safety causally or to infer an individual’s risk.

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

The primary result is a comparison of mean changes in a pain rating between a buprenorphine-film group and a placebo-film group among the stated analysis population. The unadjusted difference is -0.13, and the registry-reported ANCOVA difference is -0.14. Both confidence intervals include zero. The posted evidence therefore leaves uncertainty about the direction and size of the group contrast. It does not establish that the groups are identical, and it does not establish that a particular difference is clinically important.

The scale gives the outcome a clear direction: 0 represents no pain and 10 represents the worst pain imaginable, while the change is Week 12 minus baseline. Still, a mean is a group-level summary. It cannot show how many individual participants improved, remained stable, or worsened unless those distributions or responder results are examined. The registry lists a response outcome, but the available record does not establish a clinically meaningful threshold for the primary change measure. The results also do not answer whether the observed average change would matter to a particular person.

The randomized, placebo-controlled design is relevant to comparing groups, but the registry summary does not provide every detail needed to evaluate conduct and analysis. In particular, missing-data handling, the ANCOVA specification, multiplicity procedures, and detailed withdrawal procedures are not reported in the registry record. These limitations qualify how far the posted estimates can be generalized or interpreted.

The safety counts describe events recorded in the registry, not a complete account of comparative benefit and harm. Counts alone cannot determine whether events were caused by study medication, how long participants were exposed, or how risks might differ in other populations. The findings should be understood as trial results for the specified study and reported outcomes, rather than as medical advice or a conclusion about an individual’s treatment.

18. Why This Trial Matters Statistically

This trial is statistically informative because it puts a clearly defined continuous endpoint into a randomized, placebo-controlled comparison. The change score has a stated direction, time point, and measurement scale, which makes the central contrast interpretable: the difference concerns average pain-score change from baseline to Week 12. Reporting group means and standard deviations, together with a comparative estimate and confidence interval, supports a more complete reading than relying on a p-value alone.

The comparison also illustrates why adjusted and unadjusted estimates should be distinguished. A simple recalculation from the posted summaries produces an estimate close to the registry’s ANCOVA result, but it cannot reproduce an adjusted model whose covariates and details are not reported. Treating these estimates as the same procedure would obscure what the registry analysis contributes and what cannot be checked independently.

The precision of the primary estimate is as important as its direction. The confidence intervals include zero and span values on either side of it. This makes the result a useful example of the difference between failing to show a clear group difference and proving no difference. The same distinction applies to secondary outcomes: isolated unadjusted findings need more cautious interpretation when the multiplicity plan is not reported.

Finally, the registry combines efficacy outcomes with safety counts and identifies the analysis population, but leaves several interpretive details unreported. Missing-data methods, multiplicity handling, model specifications, and the original sample-size rationale would help readers assess robustness and design choices. Recognizing both the information in the estimates and the limits of the record is central to sound statistical interpretation.

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.

Several limitations specific to the registry record constrain interpretation. The primary outcome description identifies an ITT population as randomized subjects who received at least 1 dose of double-blind medication, but does not report how many participants contributed observed Week 12 values or how missing values were handled. The effect of incomplete outcome data on the estimate therefore cannot be assessed from the posted summaries.

The sponsor’s primary method is identified as ANCOVA, but the covariates, model specification, diagnostic checks, and sensitivity analyses are not reported in the registry record. The unadjusted recalculation is consequently a summary-statistic comparison rather than a reproduction of the sponsor analysis. The registry record also does not report the statistical analysis plan, multiplicity adjustments, or interim-analysis procedures. This is particularly relevant to interpretation of secondary outcomes, where the number and ordering of planned tests are unclear.

The official title describes a randomized withdrawal design, but the registry summary does not give enough detail to explain the withdrawal process, treatment transitions, or selection into the double-blind phase. Dose, adherence, duration of exposure for each participant, and detailed eligibility criteria are also not reported in the outcome information. These gaps limit assessment of how the reported groups were formed and how broadly the results apply.

The safety summary supplies event counts but does not provide detailed event timing, duration, relatedness, or a full comparative analysis. Deaths are not reported in the registry record. The primary endpoint’s clinically important threshold is also not reported, so statistical estimates cannot be translated into a judgment about clinical importance from this record alone. These limitations are uncertainties about the available record, not proof that a procedure or analysis was absent.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Efficacy and Safety Study of Buprenorphine HCl Buccal Film in Subjects With Low Back Pain — NCT01256450.
• Registry record last updated 2017-02-27; status last verified 2017-01.
• Results first posted 2015-12-08.
• 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 Phase 3 randomized study of buprenorphine HCl buccal film versus placebo film in subjects with moderate to severe chronic low back pain. The primary outcome is change in pain intensity from baseline to Week 12, measured using an 11-point numeric rating scale. The primary population is described as randomized subjects who received at least 1 dose of double-blind study medication.

The registry-reported ANCOVA mean difference is -0.14, with a 95% confidence interval from -0.646 to 0.366. The unadjusted recalculation is -0.13, with a confidence interval from -0.646 to 0.386. Both intervals include zero, and the registry-reported analysis takes precedence over the recalculation. Secondary results and safety counts add context but have limitations, including unreported multiplicity and missing-data procedures. The original sample-size rationale and further statistical-analysis details are not reported in the registry record.