Evaluation of Efficacy and Safety of VX-548 for Acute Pain After a Bunionectomy: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Evaluation of Efficacy and Safety of VX-548 for Acute Pain After a Bunionectomy (NCT05553366), a randomized phase 3 study. The primary outcome is Time-weighted Sum of the Pain Intensity Difference (SPID) as Recorded on a Numeric Pain Rating Scale (NPRS) From 0 to 48 Hours (SPID48), SUZ Compared to Placebo.

2. Clinical Question

The trial asked whether suzetrigine (SUZ) differed from placebo in pain scores during the first 48 hours after a bunionectomy, and also assessed comparisons with hydrocodone bitartrate/acetaminophen (HB/APAP). Its primary endpoint was the time-weighted Sum of the Pain Intensity Difference (SPID) on a numeric pain rating scale, comparing SUZ with placebo. The registry also lists secondary questions about pain scores, participants’ overall assessment, use of rescue medication, and nausea or vomiting.

The primary endpoint uses the change from baseline at repeated pain assessments, weighted by the time between assessments. That makes it a summary of pain intensity over the specified interval rather than a single rating at one moment. The registry reports a higher least-squares mean SPID48 for SUZ than placebo. The interpretation depends on the endpoint’s defined direction, the reported uncertainty, and the analysis approach; it does not by itself answer every question about pain, later recovery, or individual experience.

3. Trial Design

The registry describes a phase 3, randomized, double-blind, parallel-group, placebo-controlled study sponsored by Vertex Pharmaceuticals Incorporated. The study evaluated efficacy and safety for acute pain after bunionectomy. Enrollment is recorded as 1075. The study is listed as completed, with a start date of 2022-10-03 and a primary completion date of 2023-12-15.

The registry lists three treatment groups relevant to the posted outcomes: placebo, SUZ, and HB/APAP. The placebo group received placebo matched to both active regimens for 2 days. SUZ was given as a 100 mg first dose followed by 50 mg every 12 hours for 2 days. HB/APAP was given at 5 mg/325 mg every 6 hours for 2 days. The double-blind design means the record characterizes the study as masked, but further operational details about how masking was maintained are not reported in the registry record.

The primary efficacy comparison was SUZ versus placebo for SPID48, evaluated from 0 to 48 hours after the first dose. The posted primary outcome population was the Full Analysis Set, defined as randomized participants who received at least one dose of study drug. The registry specifies that the analyzed number for an outcome refers to participants evaluated for that particular outcome. For the primary endpoint, the posted analyzed groups were placebo, with 216 participants, and SUZ, with 426 participants. The HB/APAP group had 431 participants in its posted comparisons.

The registry also reports secondary outcomes, including a SUZ versus HB/APAP SPID48 comparison, a patient global assessment, and nausea or vomiting. The protocol’s original sample-size justification, the detailed sequence of randomization, and any stratification factors are not reported in the registry record. The registry record likewise does not describe the intended handling of all analysis populations beyond the stated Full Analysis Set definition for the primary outcome.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Full Analysis Set (FAS) included all randomized participants who received at least 1 dose of study drug. Here "Overall Number of Participants Analyzed" signifies those participants who were evaluated for this specific outcome measure.

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: Full Analysis Set (FAS) included all randomized participants who received at least 1 dose of study drug.

6. Primary Endpoint

The registry lists the primary outcome as Time-weighted Sum of the Pain Intensity Difference (SPID) as Recorded on a Numeric Pain Rating Scale (NPRS) From 0 to 48 Hours (SPID48), SUZ Compared to Placebo, measured over 0 to 48 hours After First Dose of Study Drug.

The primary endpoint, SPID48, summarizes pain-intensity differences recorded on a numeric pain rating scale from 0, no pain, to 10, worst possible pain. At each postdose assessment, the pain-intensity difference was calculated relative to the baseline pain-intensity score. Those differences were then weighted by the time elapsed since the previous measurement and summed across the 0 to 48 hour interval after the first dose.

The registry describes the possible SPID48 score range as -480, worst score, to 480, best score. In this coding, a higher score indicates a more favorable aggregate pattern of pain-intensity differences. SPID48 is used because it incorporates information across repeated assessments over the specified interval, rather than relying on a single rating. Time weighting also accounts for how long each observed rating represents before the next assessment.

The posted arm values are least-squares means, with standard errors as the dispersion measure. The placebo least-squares mean was 70.6 and the SUZ mean was 99.9. These summaries describe group averages, not the range of individual responses. The outcome is limited to the defined pain scale, the observation interval, and the participants evaluated for this endpoint. The registry does not report additional details about the timing or completeness of each pain assessment or the approach to missing endpoint measurements.

7. Results Posted in the Registry

• Suzetrigine (SUZ): mean 99.90 versus 70.60 on control; difference 29.30 (95% CI 14.13 to 44.47), standardized effect d = 0.32; z-test p = <0.001.

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.

Time-weighted Sum of the Pain Intensity Difference (SPID) as Recorded on a Numeric Pain Rating Scale (NPRS) From 0 to 48 Hours (SPID48), SUZ Compared to HB/APAP

• 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 errors.
• Result:
  • Suzetrigine (SUZ): mean 99.90 versus 120.10 on control; difference -20.20 (95% CI -32.67 to -7.73), standardized effect d = -0.22; z-test p = 0.002.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Suzetrigine (SUZ) than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Percentage of Participants Reporting Good or Excellent on the Patient Global Assessment (PGA) Scale, SUZ Compared to Placebo

• 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:
  • Suzetrigine (SUZ): 61.7% (263/426) versus 53.2% (115/216) on control; risk difference 8.5 percentage points (95% CI 0.4 to 16.6), risk ratio 1.16 (1.00–1.34); unadjusted two-proportion z-test p = 0.039.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for Suzetrigine (SUZ) than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Incidence of Vomiting or Nausea, SUZ Compared to HB/APAP

• 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:
  • Suzetrigine (SUZ): 9.2% (39/426) versus 16.5% (71/431) on control; risk difference -7.3 percentage points (95% CI -11.8 to -2.9), risk ratio 0.56 (0.39–0.80); unadjusted two-proportion z-test p = 0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically lower for Suzetrigine (SUZ) than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcomes broaden the comparison beyond the primary SUZ-versus-placebo SPID48 result. They include a separate SPID48 comparison with HB/APAP, participant global assessment, nausea or vomiting, time to pain reductions, SPID24, and rescue medication measures. The posted results therefore address several different aspects of the short-term postoperative experience rather than repeating a single endpoint.

Across the posted comparisons described in the registry, results are not all on the same scale or against the same comparator. The SUZ-versus-HB/APAP pain-score comparison asks a different question from the primary placebo comparison. The global assessment records participants’ overall rating, while rescue medication and nausea or vomiting are event or use outcomes. These measures can complement the primary endpoint by adding context, but they do not independently establish the primary effect or answer the same question.

The registry lists 10 secondary outcome measures. Multiple outcomes create more opportunities for apparently notable results to arise by chance when each is evaluated separately. The posted secondary p-values are unadjusted re-calculations, and multiplicity adjustment is not reported in the registry record. Therefore, secondary findings should be treated as supportive or exploratory context rather than given the same confirmatory weight as the designated primary endpoint. The record does not report whether a prespecified hierarchy or other multiplicity-control strategy was used.

The secondary pattern should also be interpreted with its analysis populations and timeframes in view. Some outcomes are measured at 48 hours, some over a 48-hour interval, and the nausea or vomiting outcome extends from baseline up to Day 19. Different time windows and outcome definitions limit direct comparisons across endpoints. The registry’s posted descriptions do not report enough detail to assess whether all secondary analyses were planned in advance or how missing observations were handled.

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

• Time-weighted Sum of the Pain Intensity Difference (SPID) as Recorded on a Numeric Pain Rating Scale (NPRS) From 0 to 48 Hours (SPID48), SUZ Compared to HB/APAP
• Time to Greater Than or Equal to (≥)2-Point Reduction in NPRS,SUZ Compared to Placebo
• Time to ≥1-Point Reduction in NPRS, SUZ Compared to Placebo
• Percentage of Participants Reporting Good or Excellent on the Patient Global Assessment (PGA) Scale, SUZ Compared to Placebo
• Incidence of Vomiting or Nausea, SUZ Compared to HB/APAP
• Time-weighted SPID as Recorded on the NPRS From 0 to 24 Hours (SPID24), SUZ Compared to Placebo
• Time to First Use of Rescue Medication, SUZ Compared to Placebo
• Percentage of Participants Using Rescue Medication From 0 to 48 Hours, SUZ Compared to Placebo

9. Statistical Interpretation

10. Statistical Methods Explained

The posted primary outcome is continuous: SPID48 is a numerical summary of pain ratings over time. The arm summaries are least-squares means, and their reported dispersion is the standard error. A standard error describes the uncertainty around an estimated group mean; it is not the spread of individual participants’ scores. It should therefore not be read as a range containing most participants.

What does the re-calculated mean difference represent?

The simple re-calculation compares the posted mean for SUZ with the posted mean for placebo. It gives a mean difference of 29.3 SPID48 units. This is an unadjusted comparison from the posted summary statistics, rather than the sponsor’s ANCOVA estimate. The reported confidence interval, 14.13 to 44.47, conveys a range of values compatible with the re-calculation under its assumptions. The re-calculation does not account for participant-level covariates or other features that may have entered the sponsor’s model.

For binary secondary outcomes, a risk difference compares the proportions with an event or response between groups. The registry also lists risk ratios and odds ratios for some outcomes. These measures express the comparison on different scales and can give different impressions of magnitude, especially when the outcome is not rare. The trial’s posted analyses use methods specific to the outcome: the registry lists a Cochran-Mantel-Haenszel analysis for the patient global assessment and Pearson’s chi-squared test for nausea or vomiting. A method name alone does not supply all details of covariate adjustment or missing-data handling.

Why can the sponsor result differ from a simple re-calculation?

ANCOVA is a model-based method that compares groups while accounting for specified covariates. In general, covariate adjustment can change an estimated contrast and its uncertainty relative to a simple unadjusted calculation. The registry reports ANCOVA for the primary outcome and a superiority conclusion, but the adjusted effect estimate and its confidence interval are not reported in the outcome fields. The re-calculated comparison should be understood as a transparent descriptive check based on group summaries, not as a replacement for the sponsor’s model.

Confidence intervals and p-values answer related but different questions. A confidence interval communicates uncertainty about an estimated effect on its measurement scale. A p-value describes how compatible the data are with a specified null model under the analysis assumptions; it is not the probability that the null hypothesis is true, and it does not measure clinical importance. The primary recalculation’s interval is entirely above zero, while the sponsor’s reported test also indicates a superiority finding. Neither statistic describes the full distribution of individual outcomes.

What do the design and analysis labels tell us?

Randomization is intended, in general, to support comparisons by distributing baseline prognostic factors across groups on average. Double masking is intended to reduce the influence of knowledge of assignment on care, reporting, or assessment. These are general methodological purposes; the registry record does not give further details about randomization procedures or masking implementation. The parallel model indicates that participants were assigned to a treatment group rather than the record describing a crossover design.

The Full Analysis Set is defined in the registry as randomized participants who received at least one dose of study drug. The record further clarifies that the analyzed number is specific to each outcome. This definition does not establish how every protocol deviation was handled, nor does it mean every randomized participant contributed data to every endpoint. The statistical plan, model covariates, missing-data method, and any interim analyses are not reported in the registry record.

Over-dispersion is a general concern when observed variability exceeds what a statistical model assumes, particularly for count or binary data. It can make standard errors too small if ignored. The primary endpoint is continuous, and the registry reports least-squares means and standard errors; details sufficient to assess model assumptions, residual behavior, or alternative variance specifications are not reported in the registry record. Consequently, the model’s diagnostics cannot be evaluated from the posted summary alone.

11. Confidence Intervals and Precision

The primary re-calculated mean difference is 29.3 SPID48 units, with a 95% confidence interval from 14.13 to 44.47. The interval describes uncertainty around the unadjusted group contrast under the calculation’s assumptions. Because the interval does not include zero, it is consistent with a positive mean difference on the endpoint’s stated scale. The endpoints of the interval also indicate that the estimate is not exact: a range of effect sizes remains compatible with the summary data and method.

The interval applies to the re-calculated comparison, not to the sponsor’s ANCOVA estimate. The registry does not report the sponsor’s adjusted effect estimate or an adjusted confidence interval. This distinction matters because adjustment can affect both the estimated contrast and its precision. The sponsor’s reported ANCOVA test supports a superiority conclusion, but its p-value alone does not show the size of the adjusted effect or its confidence interval.

In general, a narrower confidence interval indicates greater precision for the estimate, while a wider interval indicates more uncertainty. Precision is not the same as clinical importance: an estimate can be precise without establishing whether its magnitude matters to patients. Conversely, a confidence interval does not show the range of responses among individuals. The posted standard errors summarize uncertainty around arm means, not the variability of individual pain experiences.

The registry’s primary outcome summary does not report individual-level data, distributions, or a threshold for clinical importance. It also does not provide the sponsor model’s confidence interval. The posted interval should therefore be interpreted as precision for the simple recalculation only, with the analysis population and 0 to 48 hour timeframe in mind.

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 illustrations based on the observed effect, not a report of the trial’s original design calculations. For continuous outcomes such as SPID48, the figures are participants per arm. The registry’s planning assumptions are a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. The effect to detect is specified as a fraction of the observed effect. Time-to-event planning figures, when present, are total numbers of events using the Schoenfeld approach; the displayed SPID48 planning figures are participants per arm.

The 80% power column describes the illustrative number of participants per arm that would give an 80% chance of detecting the assumed effect if the planning assumptions hold and the effect is present. The 90% power column uses the same general interpretation with a higher chance of detection under those assumptions. These figures do not describe the chance that the trial’s finding is true. This is not observed power.

Rows that plan for 100%, 75%, or 50% of the observed effect represent progressively smaller target effects. Smaller effects are harder to distinguish from random variation under a given design, so they require more participants per arm in the planning illustration. The entries are not a recommendation for a future trial and do not establish the sample size that was used or justified in the original protocol. The original sample-size assumptions and justification are 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 = 29.300; pooled standard deviation σ = 92.782.
2. n = 2 × (1.96 + 0.842)² × 92.782² / 29.300² = 157.4, rounded up to 158 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 <- 29.3                      # observed difference in means
sigma <- 92.7822223340765                     # 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(5553366)
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 = 158 (80% power), 211 (90% power)
 75% of observed effect: n per arm = 280 (80% power), 375 (90% power)
 50% of observed effect: n per arm = 630 (80% power), 843 (90% power)
power.t.test: 158.4 
Simulated power at n = 158 per arm: 0.798 (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 that the sponsor analyzed the primary comparison using ANCOVA and recorded a superiority result, with a reported p-value of < 0.001. The posted outcome fields do not include the sponsor’s adjusted effect estimate or confidence interval. The separate recalculation uses the group-level means and standard errors to produce an unadjusted mean difference of 29.3, a confidence interval from 14.13 to 44.47, and p < 0.001.

These are different statistical summaries. ANCOVA is the sponsor’s reported analysis; the recalculation is a simple comparison of the posted summary statistics and does not reproduce the sponsor’s model. The registry record does not identify the model covariates in the reported ANCOVA result. The recalculation can help readers understand the scale and direction of the posted group difference, but it should not be presented as the sponsor’s adjusted estimate.

The two analyses have a consistent broad direction in the record: the posted SUZ mean is higher than the placebo mean, and the sponsor reports superiority. Because the discrepancy flag is false, there is no flagged conflict between the sponsor result and the recalculated result. In general, if a discrepancy were flagged, the sponsor’s own analysis would take precedence over a summary-statistic recalculation.

15. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when a study evaluates several outcomes or makes several statistical comparisons. Even if each test is interpreted using its own conventional threshold, carrying out many tests can increase the chance that at least one result appears statistically notable by chance. Methods such as a testing hierarchy or adjusted significance thresholds can address this issue, but the registry record does not report whether either was used for the secondary outcomes. The primary endpoint is distinguished in the record, while the posted secondary results should be read with greater caution because adjustment is not reported.

The registry describes the primary analysis population as the Full Analysis Set, including all randomized participants who received at least one dose of study drug. It also states that the analyzed number is outcome-specific. This gives a basic definition of the primary population, but it does not report a complete account of participants excluded from each analysis, reasons for missing outcome data, or how missing observations were treated.

Missing-data handling can affect an estimate when participants lack measurements, especially if the reasons for missingness relate to treatment or outcome. General approaches include modeling available observations or imputing unobserved values under specified assumptions. The registry does not report which approach was used for the primary outcome or secondary outcomes, whether sensitivity analyses were conducted, or what assumptions were made about missing data. Those details are necessary to judge how robust results are to incomplete follow-up.

The registry reports an ANCOVA method for the primary comparison, but the model covariates and diagnostics are not reported in the record. Interim analyses, stopping rules, and the protocol’s full statistical analysis plan are also not reported in the registry record. Their absence from the registry entry should not be taken as evidence that a particular procedure was or was not used; it means that these features cannot be assessed from the posted record.

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 5% reporting threshold.

Most frequent non-serious adverse event terms

The serious adverse event figures show zero serious events in each of the three listed groups: placebo, HB/APAP, and SUZ. The registry lists 216 participants at risk in the placebo group, 431 in the HB/APAP group, and 426 in the SUZ group for this safety summary. It also lists zero deaths in each group. These are the posted counts for the reported safety categories and should not be interpreted as proof that no serious event could occur.

The registry also records other adverse events affecting 51 participants in the placebo group, 113 in the HB/APAP group, and 72 in the SUZ group. The record does not provide serious adverse event terms in the listed top-term field. The available figures are counts, not a complete description of event severity, duration, timing, attribution, or recurrence.

Safety summaries depend on the observation and reporting procedures and the participants included in the safety population. Those details are not fully described in the registry record. Comparisons of these counts alone do not establish that one regimen is safer, and the counts do not replace a detailed review of adverse-event definitions and exposure time.

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

The primary result is evidence of a difference in average SPID48 between the SUZ and placebo groups in the posted analysis. The SUZ least-squares mean was higher, and the simple unadjusted recalculation produced a positive mean difference with a confidence interval above zero. The sponsor’s reported ANCOVA analysis also recorded a superiority result. Together, these summaries describe the primary endpoint in the studied population and the specified 0 to 48 hour period.

The result does not mean that every participant had a better pain experience, or that the same difference would occur for every person undergoing bunionectomy. A mean summarizes groups and does not show individual variation. Nor does SPID48 show the pattern at each measurement time; multiple courses of pain ratings can produce similar summary values.

The primary result does not establish effects outside the studied timeframe, for other procedures, or for populations not described in the registry record. It does not answer every question about duration of pain, recovery, patient preferences, or the balance of benefits and harms. The record’s secondary outcomes offer additional information, but they involve different measures, comparators, and time windows, and their multiplicity handling is not reported.

Statistical significance is not a measure of how important an effect is to patients. The registry record does not report a clinically important threshold for SPID48 or a direct translation of the group mean difference into an individual-level outcome. The results should therefore be understood as statistical comparisons of the posted measures, not as a complete evaluation of clinical value or a basis for individual medical decisions.

18. Why This Trial Matters Statistically

This trial illustrates why a clinical result should be read at several levels. The endpoint is not a single pain rating but a time-weighted summary across repeated measurements. Understanding that construction clarifies what the group means represent and why the result is tied to a particular observation window. The scale’s direction also matters: the registry defines higher SPID48 values as better scores.

The record offers both a sponsor-reported ANCOVA test and a simple recalculation from group summary statistics. Keeping those analyses distinct is important. The recalculation provides an accessible estimate and confidence interval, while the sponsor’s analysis is the reported model-based test. A p-value alone cannot replace an effect estimate, and a simple contrast should not be mislabeled as an adjusted analysis.

The secondary outcomes show another important statistical issue: clinical trials often assess more than one measure and comparator. A broad set of outcomes can describe different dimensions of experience, but unadjusted secondary tests do not carry the same confirmatory weight as the designated primary analysis. The registry’s missing detail about multiplicity and missing-data methods also shows why statistical interpretation includes attention to what the record does not report.

Finally, planning illustrations based on an observed effect are not retrospective proof that a trial was adequately powered. They depend on assumptions and effect sizes chosen for the illustration. Separating those planning calculations from the original design rationale, which is not reported in the registry record, helps prevent a common misreading of power and sample size.

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.

The registry record does not report the sponsor’s adjusted effect estimate or confidence interval for the primary ANCOVA analysis, limiting direct assessment of the magnitude and precision of that model-based result. The recalculated estimate is based on posted group summaries and is unadjusted. Covariates included in the sponsor’s model are not reported in the outcome record.

The primary outcome summary does not provide individual-level data, distributions, or results at each separate assessment time. It therefore cannot show variation between participants or the time course underlying the aggregate SPID48 score. The record also does not report a clinically important threshold for interpreting the size of the SPID48 difference.

There are several secondary outcomes, but multiplicity adjustment or a prespecified testing hierarchy is not reported in the registry record. Secondary findings should consequently be read cautiously. Missing-data methods, sensitivity analyses, and detailed accounting of outcome-specific exclusions are also not reported. The Full Analysis Set definition gives some information about the primary population, but it does not answer those questions.

The posted safety summary gives event counts, including zero serious adverse events and zero deaths in the listed groups, but it does not provide detailed event terms in the serious-event field or full information about event timing, duration, and attribution. The registry entry also does not report further demographic details in the record, limiting assessment of how broadly the observed results may apply. These limitations concern the information available in the registry record and do not establish that unreported procedures were not conducted.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Evaluation of Efficacy and Safety of VX-548 for Acute Pain After a Bunionectomy — NCT05553366.
• Registry record last updated 2025-08-01; status last verified 2025-07.
• Results first posted 2025-08-01.
• 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 describes a completed phase 3, randomized, double-blind, parallel-group, placebo-controlled trial of suzetrigine for acute pain after bunionectomy. Enrollment is recorded as 1075. The primary outcome was SPID48, measured from 0 to 48 hours after the first dose in the Full Analysis Set.

The posted SUZ and placebo least-squares means were 99.9 and 70.6. A simple recalculation gives a mean difference of 29.3, with a 95% confidence interval from 14.13 to 44.47 and p < 0.001. The sponsor’s reported ANCOVA analysis recorded a superiority result. The sponsor’s adjusted estimate and confidence interval, multiplicity procedures, and missing-data methods are not reported in the registry record.