DaxibotulinumtoxinA for Injection for the Treatment of Plantar Fasciitis: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for DaxibotulinumtoxinA for Injection for the Treatment of Plantar Fasciitis (NCT03825315), a randomized phase 2 study. The primary outcome is Change From Baseline at Week 8 in the Numeric Pain Rating Scale (NPRS) Score.

2. Clinical Question

The primary outcome is a continuous pain score, not a direct count of people who improved. The posted group results are least-squares mean changes, with standard errors. More negative mean changes indicate larger decreases in the recorded score; the posted means were negative in all three groups. The estimates therefore need to be read comparatively: the relevant question is whether the change in either DAXI group differed from the change in placebo, and how precisely that difference was estimated.

The registry also posts two secondary outcomes: change in Foot Function Index score and the proportion of participants with at least a 20% decrease from baseline in NPRS. These outcomes provide additional perspectives on function and on a threshold-based pain response. They do not replace the primary comparison, and the registry record does not report adjusted analyses for these secondary endpoints.

3. Trial Design

The registry describes a phase II, prospective, randomized, double-blind, multicenter, placebo-controlled trial with a parallel-group design. Masking is recorded as quadruple. The trial is listed as completed, with enrollment of 155 participants. Its start date is 2018-12-31 and its primary completion date is 2020-06-04.

Participants were assigned to one of three groups: DAXI 80 U, DAXI 120 U, or placebo. The brief description says the study evaluated a single administration. The posted primary outcome results include 49 participants in the DAXI 80 U group, 54 in the DAXI 120 U group, and 52 in the placebo group. Those arm counts add to the recorded enrollment, but the registry record does not explain participant flow, exclusions, or whether every enrolled participant contributed to every outcome.

Random allocation and masking are design features intended to reduce systematic differences between groups and influence of expectations on assessment. The parallel-group structure means participants were assigned to a group rather than crossing between interventions. The registry identifies the trial as multicenter, but the number and locations of centers are not reported in the registry record. It also does not report the randomization procedure, allocation concealment details, or the operational meaning of quadruple masking.

The original sample-size calculation, assumptions used to plan enrollment, and any interim analyses are not reported in the registry record. The sample-size illustrations based on observed results are a separate, retrospective planning exercise and should not be mistaken for the trial’s original design 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

Analysis population for the primary outcome, as defined in the registry: Intent to treat population

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 Change From Baseline at Week 8 in the Numeric Pain Rating Scale (NPRS) Score, measured over Week 8.

The primary endpoint is change from baseline at Week 8 in the Numeric Pain Rating Scale score. The score runs from 0, meaning no pain, to 10, meaning the worst pain imaginable. Participants recorded pain within 15 minutes after stepping out of bed in the morning. The value used for the outcome was averaged over 5 days: the 4 days before the study visit and the visit day.

Change from baseline expresses how a participant’s score at follow-up differs from their starting score. In the posted group summaries, negative changes represent decreases in the score. The reported group values are least-squares means, accompanied by standard errors. A group mean describes an average change, so it does not show how many individual participants improved, remained unchanged, or worsened.

A pain rating is a patient-reported measure that can capture a symptom directly and repeatedly. Recording pain shortly after getting out of bed focuses the measurement on a specified time of day, while averaging across several days can represent more than a single reading. These are general measurement considerations; the registry does not report evidence about the scale’s measurement properties in this trial or explain why Week 8 was selected as the primary time point.

The clinically important size of a difference, if any, is not reported in the registry record. Statistical estimates alone therefore do not establish whether a difference is important to participants.

7. Results Posted in the Registry

• DAXI 80 U: mean -3.29 versus -2.75 on control; difference -0.54 (95% CI -1.42 to 0.34), standardized effect d = -0.24; z-test p = 0.227.
• DAXI 120 U: mean -3.25 versus -2.75 on control; difference -0.50 (95% CI -1.33 to 0.33), standardized effect d = -0.23; z-test p = 0.239.

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.

Change From Baseline at Week 8 in Foot Function Index (FFI)

• 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:
  • DAXI 80 U: mean -29.02 versus -23.63 on control; difference -5.39 (95% CI -11.47 to 0.69), standardized effect d = -0.35; z-test p = 0.082.
  • DAXI 120 U: mean -27.37 versus -23.63 on control; difference -3.74 (95% CI -9.75 to 2.27), standardized effect d = -0.24; z-test p = 0.222.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between DAXI 80 U and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between DAXI 120 U and the control. The interval gives the range of effects that remain compatible with the data.

Proportion of Subjects With a Decrease From Baseline of >= 20% in NPRS

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • DAXI 80 U: 71.4% (35/49) versus 65.4% (34/52) on control; risk difference 6.0 percentage points (95% CI -12.0 to 24.1), risk ratio 1.09 (0.84–1.42); unadjusted two-proportion z-test p = 0.514.
  • DAXI 120 U: 75.9% (41/54) versus 65.4% (34/52) on control; risk difference 10.5 percentage points (95% CI -6.7 to 27.8), risk ratio 1.16 (0.91–1.49); unadjusted two-proportion z-test p = 0.233.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between DAXI 80 U and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between DAXI 120 U and the control. The interval gives the range of effects that remain compatible with the data.

The two secondary outcomes add different types of information. Foot Function Index is a continuous change score, while the NPRS threshold outcome counts participants meeting a defined decrease threshold. In both, the posted active-group summaries are numerically more favorable in direction than the placebo summaries under the outcome coding. This broad pattern is consistent with the direction of the primary point estimates, but the secondary results do not make the primary comparison more precise or resolve its uncertainty.

For the Foot Function Index comparison, the confidence intervals include zero for both dose groups, and the unadjusted p-values are 0.082 and 0.222. For the threshold response, the posted unadjusted p-values are 0.514 and 0.233, and the risk-difference intervals include zero. These endpoint-level results are displayed in the statistical results; their overall lesson is that the registry’s secondary comparisons do not provide clear, precise confirmation of a difference from placebo.

Secondary outcomes can be informative because they assess function and a responder threshold rather than only average pain-score change. They also involve additional comparisons. If several outcomes are examined without accounting for multiplicity, the chance of finding at least one apparently unusual result can increase. Conversely, a non-significant secondary comparison does not establish absence of an effect, particularly when its estimate is imprecise.

The registry record lists no reported analyses for these secondary outcomes. It does not explain whether they were prespecified, how missing values were handled, or whether any adjustment for multiple testing was planned. Without those details, secondary findings carry less confirmatory weight than a fully specified primary analysis. Their role is best understood as contextual: they show whether different outcome definitions tell a broadly compatible story, while leaving uncertainty about the size and reliability of any between-group difference.

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

• Change From Baseline at Week 8 in Foot Function Index (FFI)
• Proportion of Subjects With a Decrease From Baseline of >= 20% in NPRS

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is continuous: it is a numeric score summarized with a mean. The registry reports least-squares means and standard errors for each arm. A least-squares mean is a model-based group mean; unlike a simple arithmetic average, it can reflect adjustments specified in a statistical model. The model and any adjustment variables are not reported in the registry record, so the exact basis for these least-squares means cannot be assessed from the record alone.

What does a mean difference represent?

A mean difference compares the average change in one group with the average change in another. For the primary comparisons, placebo is the reference group. The reported estimates of -0.54 for DAXI 80 U and -0.5 for DAXI 120 U represent the active-group mean change minus the placebo-group mean change. A negative estimate means the active group had a more negative average change in this coding. It is an average contrast, not an individual participant’s change and not the chance that a participant improved.

The arm-level values were -3.29 for DAXI 80 U, -3.25 for DAXI 120 U, and -2.75 for placebo. All three are changes from baseline, not Week 8 scores. The reported standard errors were 0.329, 0.298, and 0.302, respectively. A standard error describes the estimated sampling uncertainty around a mean; it is not the spread of individual participant scores. The record does not post the arm-level standard deviations or the distribution of individual changes.

How should a confidence interval be read?

A confidence interval gives a range of values compatible with the data and the method used to construct the interval. It communicates uncertainty around an estimate rather than a guarantee that the true value lies within the particular interval. For both primary comparisons, the interval includes zero. Zero represents no difference between the group mean changes. Because the intervals extend across zero, the data are compatible with a range that includes no difference as well as differences in either direction. This does not establish that the groups are equal.

The unadjusted p-values for the primary comparisons are 0.227 and 0.239. A p-value is a measure of how unusual data at least as inconsistent with a specified null hypothesis would be if that hypothesis and the analysis assumptions held. It is not the probability that the null hypothesis is true, nor a measure of clinical importance. The registry record does not report the prespecified significance threshold or whether these comparisons were part of a broader testing procedure. The sample-size illustrations separately state a two-sided significance level of 0.05; that is an assumption for those illustrations, not evidence of the trial’s original analysis plan.

What do the secondary outcome summaries add?

The Foot Function Index outcome is also continuous and is presented as a change from baseline at Week 8. Its group results are least-squares means with standard errors. The NPRS threshold outcome is binary: it counts participants whose score decreased from baseline by at least 20%. For a binary outcome, the posted counts and the number at risk describe observed responses, while a risk difference contrasts the observed group proportions. The registry also posts risk-ratio and odds-ratio estimates in its calculated comparisons, but the record does not list reported analyses for these secondary endpoints.

For continuous outcomes, variability in participant measurements affects how precisely an average or mean difference is estimated. For binary outcomes, precision depends in part on the number of participants and the number of responses in each group. Sparse counts can make estimates less stable. These are general statistical principles; they do not establish which particular source of uncertainty dominates in this trial.

Why does over-dispersion matter in general?

Over-dispersion means that observed variation is greater than a statistical model expects. When a model underestimates variation, standard errors can be too small and intervals too narrow, making evidence appear more precise than it is. The posted primary endpoint is a continuous score, and the registry record does not report an over-dispersion assessment or a model diagnostic. This general issue should not be read as evidence that over-dispersion occurred in this trial.

The comparison estimates are unadjusted calculations based on the posted arm summaries, and the pooled standard deviations are described as approximate. These calculations offer a transparent comparison but are not a substitute for a complete trial analysis. No discrepancy between the posted summaries and these calculations is flagged. Nevertheless, the sponsor’s full analysis methods and analysis output are not reported in the registry record, so there is no basis to evaluate model choices, missing-data handling, or any adjusted estimates.

11. Confidence Intervals and Precision

Precision concerns how narrowly the data locate an estimated group difference. For the primary comparison of DAXI 80 U with placebo, the mean difference was -0.54, with a confidence interval from -1.415 to 0.335. For DAXI 120 U compared with placebo, the mean difference was -0.5, with a confidence interval from -1.332 to 0.332. Both intervals include zero. The estimates therefore allow for no average difference and for differences in either direction within the respective intervals.

The intervals are wide relative to the point estimates, so the point estimates should not be treated as exact descriptions of the underlying differences. A confidence interval is not a range containing every plausible individual response: it concerns uncertainty in the estimated group contrast. Individual participant outcomes can vary more than the uncertainty around the mean difference suggests, and participant-level distributions are not reported in the registry record.

The posted arm sizes for the primary endpoint were 49, 54, and 52. Standard errors for the arm means were 0.329, 0.298, and 0.302. These summaries help describe the basis for uncertainty, but they do not reveal the full score distributions or the analysis model. The registry does not report missing-data counts by outcome, the method used to handle missing measurements, or the construction details for the reported intervals.

Interpretation should account for both the estimate and its interval. A point estimate alone can make a difference appear more definitive than the data support; a p-value alone does not describe the range of compatible effects. The primary intervals include zero, and the record does not specify a clinically important difference against which to judge the span of possible values. Thus the precision information limits how confidently the observed point estimates can be generalized.

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 illustrations are planning calculations based on the observed effects, not the trial’s original enrollment plan. For these comparisons, the displayed quantities are participants per arm, not total events. They state assumptions of a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each row considers detecting the stated fraction of the observed effect. The original design assumptions and sample-size justification are not reported in the registry record.

The 80% power column gives the number of participants per arm estimated to provide an 80% chance of detecting the chosen effect under the illustration’s assumptions, if that effect is present. The 90% power column uses a higher target chance of detection and consequently requires more participants per arm for the same stated effect. These are planning quantities, not guarantees that a study of that size will produce a statistically significant result.

For the primary comparison of DAXI 80 U with placebo, planning for 100% of the observed effect gives 270 participants per arm for 80% power and 362 participants per arm for 90% power. Planning for 75% of the observed effect gives 480 and 643 participants per arm, respectively. Planning for 50% gives 1,080 and 1,446 participants per arm. For the DAXI 120 U comparison, the corresponding illustrations are 300 and 401 participants per arm for 100% of the observed effect; 533 and 713 for 75%; and 1,198 and 1,604 for 50%.

A smaller target effect is harder to distinguish from random variation, so the illustrations require more participants per arm when the fraction of the observed effect is reduced. These figures are not observed power; they are prospective planning illustrations calculated from the observed effects under stated assumptions. The sample-size curve should be read in the same way: it represents how planning requirements change as the target effect changes, not how likely the completed trial was to succeed.

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 = -0.540; pooled standard deviation σ = 2.239.
2. n = 2 × (1.96 + 0.842)² × 2.239² / -0.540² = 270.0, rounded up to 270 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 <- -0.54                      # observed difference in means
sigma <- 2.23935380289615                     # 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(3825315)
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 = 270 (80% power), 362 (90% power)
 75% of observed effect: n per arm = 480 (80% power), 643 (90% power)
 50% of observed effect: n per arm = 1,080 (80% power), 1,446 (90% power)
power.t.test: 270.9 
Simulated power at n = 270 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. Multiplicity, Missing Data and Analysis Populations

The registry lists one primary outcome and two secondary outcomes. Comparing multiple doses and outcomes raises the general issue of multiplicity: with more statistical tests, the chance of at least one apparently notable result under a no-effect scenario can increase. A multiplicity plan may control that risk by defining a testing hierarchy or adjusting thresholds. The registry record does not report whether such a plan was used, whether the secondary outcomes were confirmatory, or how the two dose comparisons were handled together.

The posted p-values are identified as unadjusted. They should therefore be read as individual comparisons rather than as evidence that a family of tests has been controlled for multiple testing. The record does not report a prespecified significance threshold for the trial’s own analysis, or whether the p-values shown correspond to the sponsor’s primary analysis. The 0.05 significance level in the planning illustration is not a report of the trial’s testing plan.

Missing-data methods matter because outcomes may be unavailable for some participants, and different assumptions or methods can affect estimated group differences. The primary outcome is described for the intent-to-treat population, but the registry record does not state how many participants had missing Week 8 NPRS measurements, how missing outcomes were handled, or whether the analysis followed a particular imputation or model-based procedure. A population label alone does not answer those questions.

The record also does not report protocol deviations, exclusions from the analysis, sensitivity analyses, or reasons for missing observations. The posted endpoint arm counts are not a substitute for a participant flow description. Thus the extent to which the results depend on analysis-population definitions or missing-data assumptions cannot be assessed from the registry record.

These omissions do not show that a particular problem occurred. They limit independent evaluation of the analysis and the strength of confirmatory claims. The reported comparisons can be described as posted, unadjusted results, while conclusions about multiplicity control, robustness to missingness, or adherence to a prespecified statistical plan are not available.

15. 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 serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: infectious mononucleosis (2.0%), uterine haemorrhage (2.0%), abortion spontaneous (1.9%), nephrolithiasis (1.9%).

The registry posts serious adverse event counts of 2 among 49 participants in the DAXI 80 U group, 2 among 54 in the DAXI 120 U group, and 0 among 52 in the placebo group. It posts 0 deaths in each group. These are counts with the listed group sizes, not adjusted comparisons of safety risk.

The registry separately reports other adverse events affecting 7 participants in the DAXI 80 U group, 12 in the DAXI 120 U group, and 10 in the placebo group. Serious events and other adverse events are distinct categories in the record; the counts should not be combined. The serious-event terms listed include Infectious mononucleosis, Uterine haemorrhage, Abortion spontaneous, and Nephrolithiasis. The registry lists percentages beside those terms, but does not give enough detail in the posted record to determine from those entries alone how events were counted or whether a term represents a participant or an event.

These descriptive counts do not establish that an event was caused by an intervention, and a zero count does not establish absence of risk. The registry record does not report event narratives, severity beyond the serious classification, timing, relatedness assessments, or statistical comparisons. The safety figures are therefore best read as a compact account of recorded events in the trial groups, not as a complete comparative safety assessment.

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

The posted primary results describe decreases in average NPRS scores in all three groups by Week 8. The estimated mean changes were -3.29 for DAXI 80 U, -3.25 for DAXI 120 U, and -2.75 for placebo. The unadjusted between-group estimates were -0.54 and -0.5, with confidence intervals that include zero. These data do not precisely establish the size or direction of a difference between either active group and placebo.

That statement is not equivalent to saying the groups are the same. The intervals include a range of possible differences, and the trial’s posted sample sizes are limited relative to the retrospective planning illustrations. Nor do the results establish that either dose produces an important change for participants: a threshold for clinical importance is not reported in the registry record. Statistical significance, clinical importance, and certainty are related but distinct concepts.

The arm averages also do not describe every participant’s experience. Some participants may have had larger decreases, smaller decreases, no change, or increases in score, but the registry does not post participant-level data or distributions. The threshold-response secondary outcome gives an additional group-level count, but it does not resolve the limitations of the primary mean comparison or replace a fully reported analysis.

The design features—randomization, masking, placebo control, and parallel groups—are relevant strengths of the trial structure. However, the available registry record does not provide enough detail to evaluate important analysis questions, including the original statistical plan, handling of missing data, and multiplicity. Findings should therefore be described as registry-posted results rather than as a complete account of all trial evidence.

No treatment recommendation follows from these statistics. The results characterize the observed group summaries and their uncertainty in this trial. They do not, by themselves, establish benefit, lack of benefit, long-term outcomes, or the balance of effects in settings beyond the trial.

17. Why This Trial Matters Statistically

This trial illustrates why a comparison with placebo is more informative than looking at within-group change alone. Each group had a negative average change in NPRS. The primary statistical question is not whether scores decreased within a group, but whether the average change differed between each DAXI group and placebo. The posted between-group estimates and their intervals directly address that contrast, while showing substantial uncertainty around its size.

It also demonstrates the value of reading estimates, intervals, and p-values together. A point estimate communicates direction and scale, an interval communicates precision, and a p-value addresses compatibility with a specified null under the analysis assumptions. None of these alone answers whether a difference matters clinically. The registry record does not state a clinically important difference, making that distinction especially relevant.

The secondary outcomes offer a useful statistical contrast between a continuous score and a threshold-based response. These measures can tell different aspects of an outcome story, but examining more outcomes also raises multiplicity concerns. The absence of reported secondary analyses or a multiplicity plan means that a consistent-looking direction should not be mistaken for independent confirmation.

Finally, retrospective sample-size illustrations show how observed effects translate into planning requirements under explicit assumptions. They are useful for understanding uncertainty and the challenge of detecting smaller effects, but they do not reveal what the trial was designed to detect. The original design assumptions are not reported in the registry record. Keeping those two questions separate prevents post hoc planning calculations from being mistaken for the rationale behind the completed study.

18. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

The registry record gives arm-level means and standard errors but does not report the full statistical model used to obtain the least-squares means. It does not identify covariates, covariance assumptions, or the exact method used to construct the confidence intervals. This limits independent assessment of whether the posted comparisons reproduce the planned analysis.

Participant-level score distributions, baseline values by group, and participant flow are not reported in the registry record. Although outcome-specific arm counts are posted, the record does not explain missing measurements, exclusions, protocol deviations, or how the intent-to-treat population was operationalized. These details are important for evaluating whether the reported groups and analysis populations remained comparable.

The record does not report the original power calculation, target effect, assumptions about variability, or the planned enrollment rationale. It also does not report a prespecified hierarchy for dose comparisons and secondary endpoints, or any multiplicity adjustment. As a result, the confirmatory status of the secondary outcomes and the interpretation of unadjusted p-values cannot be established from the registry record.

The follow-up outcome discussed is at Week 8. Longer-term outcome results are not included in the registry entries, and the registry record does not provide information about durability beyond that time point. The number and locations of study centers, eligibility criteria, and additional participant characteristics are also not reported in the registry record. These gaps limit judgments about how representative the enrolled population was and how broadly the results may apply.

Finally, the serious-event counts are descriptive and sparse. No detailed event narratives, relatedness assessments, or comparative safety analysis are reported. These limitations concern the information available in the registry record; they do not establish that any unreported method or assessment was absent from the full trial conduct.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: DaxibotulinumtoxinA for Injection for the Treatment of Plantar Fasciitis — NCT03825315.
• Registry record last updated 2023-09-21; status last verified 2023-08.
• Results first posted 2023-09-21.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

22. Record Summary

NCT03825315 is a completed phase II randomized, quadruple-masked, parallel-group, multicenter, placebo-controlled trial of DAXI 80 U, DAXI 120 U, and placebo for plantar fasciitis. Enrollment was 155. The primary outcome was change from baseline at Week 8 in NPRS, measured in the morning and averaged over 5 days.

The posted mean changes were -3.29, -3.25, and -2.75 in the DAXI 80 U, DAXI 120 U, and placebo groups, respectively. Unadjusted comparisons with placebo had confidence intervals that included zero. Secondary outcomes addressed Foot Function Index change and an NPRS decrease threshold. The record also posts adverse-event counts, including serious events and deaths.

The registry record does not report the original sample-size justification, detailed analysis plan, multiplicity approach, or missing-data methods. Those omissions constrain how fully the posted results can be evaluated.