Denosumab In Addition To Intense Urate-Lowering Therapy for Bone Erosions: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Denosumab In Addition To Intense Urate-Lowering Therapy for Bone Erosions (NCT02903446), a randomized phase 2 study. The primary outcome is CT Bone Erosion Score.

2. Clinical Question

3. Trial Design

This was a Phase 2, randomized, parallel-group pilot study with no masking. The registry lists an enrollment of 20 and describes the study as controlled and proof-of-concept. The record marks the study as completed. It lists a start date of 2017-02-01 and a primary completion date of 2020-03-01.

The intervention group received denosumab 60 mg by subcutaneous administration every 6 months for a year, together with standard-of-care urate-lowering therapy. The control group received standard urate-lowering therapy. The posted primary outcome compares the CT bone erosion score at baseline and 12 months. The group-level results include 10 participants in each arm for this outcome.

Randomization can help balance measured and unmeasured characteristics between groups on average, but it does not guarantee balance in a small study. The absence of masking means participants and study personnel were not masked to assignment, according to the registry classification. The record does not report details of sequence generation, allocation concealment, adherence, treatment discontinuation, or participant flow. The original sample-size justification, the trial's planned statistical analysis, and any interim analyses are not reported in the registry record.

The registry lists five secondary outcomes, including bone reabsorption, reported functional status, physical and mental health, and pain. Numerical comparison results are posted for three of these outcomes. The posted results should be read as outcomes from a pilot study rather than as a confirmatory assessment of all possible effects.

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

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 CT Bone Erosion Score, measured over Baseline, 12 months.

The primary endpoint is the change in foot CT bone erosion score from baseline to 12 months. The registry describes scoring 14 foot bones separately on a scale from 0 to 10, based on the proportion of eroded bone relative to assessed bone volume. The total score ranges from 0 to 140, and higher scores indicate worsening erosion. The measure is intended to quantify structural damage in the foot rather than symptoms alone.

CT-based scoring is relevant to the study question because the intervention was added to urate-lowering therapy with the aim of addressing bone erosion. A structural measure can therefore assess a feature that is distinct from the frequency of attacks or a participant's reported health status. The registry describes the primary measure as a mean with standard deviation and identifies baseline and 12 months as the assessment timeframe.

The posted means are 6.6 for the intervention group and 7.0 for the control group, with a mean difference of -0.4. The registry's endpoint description refers to change from baseline, but it does not provide separate baseline and 12-month group means in the posted result. The record also does not describe the scoring reliability, reader masking, or handling of unavailable scans. Those details would help readers assess how consistently the structural measure was obtained and how missing imaging data may affect interpretation.

7. Results Posted in the Registry

• Intervention: mean 6.60 versus 7.00 on control; difference -0.40 (95% CI -5.00 to 4.20), standardized effect d = -0.08; z-test p = 0.865.

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.

Decrease in Bone Reabsorption

• 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:
  • Intervention: mean 177.60 versus 324.10 on control; difference -146.50 (95% CI -259.63 to -33.37), standardized effect d = -1.14; z-test p = 0.011.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Intervention than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change in Subject Reported Functional Status (Disability)

• 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:
  • Intervention: mean 0.33 versus 0.11 on control; difference 0.22 (95% CI -0.02 to 0.46), standardized effect d = 0.81; z-test p = 0.070.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Intervention and the control. The interval gives the range of effects that remain compatible with the data.

Subject Reported Change in Physical Health

• 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:
  • Intervention: mean 45.50 versus 52.30 on control; difference -6.80 (95% CI -14.69 to 1.09), standardized effect d = -0.76; z-test p = 0.091.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Intervention and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists five secondary outcomes, spanning bone reabsorption, functional status, reported physical and mental health, and pain. Numerical group comparisons are posted for three secondary measures. Their pattern is mixed: one comparison has a confidence interval that does not include zero, while the intervals for the other two include zero. The estimated directions also do not all align numerically. These results therefore do not form a single, consistent pattern across the reported domains.

Secondary outcomes are related to the primary question but do not measure the same thing. Bone reabsorption is a biological measure, while the reported function and health measures capture other aspects of participants' experience. An association on one measure cannot be assumed to establish a corresponding change in CT-scored erosion or in outcomes that were not numerically reported. The primary outcome remains the main structural endpoint specified in the registry.

Unadjusted secondary comparisons carry less weight because a study examining multiple outcomes creates more opportunities for apparently notable results to arise by chance. The record does not report a multiplicity plan or adjustment. In addition, these comparisons are recalculations from posted summary statistics rather than analyses documented in a reported trial analysis. Their estimates and intervals are best treated as exploratory signals that may inform questions for further study, not as independent confirmation of the primary result.

The record does not provide numerical results for the listed mental-health and pain outcomes, despite including them among the secondary measures. Those outcomes cannot be evaluated from the posted numerical comparisons. The absence of a posted result should not be interpreted as evidence that no change occurred; the analysis and missing-result details are not reported in the registry record.

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

• Decrease in Bone Reabsorption
• Change in Subject Reported Functional Status (Disability)
• Subject Reported Change in Physical Health
• Subject Reported Change in Mental Health
• Assessment of Pain

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is continuous and reported as a mean with a standard deviation. A mean describes the center of a group of numerical observations; a standard deviation describes how dispersed those observations are around the mean. For a two-group comparison, the mean difference expresses the intervention group's mean relative to the control group's mean. The posted primary estimate is -0.4, with the control mean at 7.0 and the intervention mean at 6.6.

What does the confidence interval represent?

A confidence interval gives a range of values reasonably compatible with the observed data under the assumptions of the calculation. It is not a range containing a known proportion of individual participant scores, and it does not assign a probability to the true effect after the data have been observed. For the primary comparison, the interval from -5.004 to 4.204 includes zero and includes both negative and positive differences. That broad span is a sign that the estimate is not precise.

The posted comparisons are recalculated, unadjusted comparisons based on summary statistics. They are not a substitute for a trial-specific model or a sponsor's full analysis. The registry record reports no analyses in its posted analysis listing, and the original statistical analysis plan is not reported in the registry record. The calculated p-values and intervals should accordingly be understood as descriptive inferential summaries of the posted group means and standard deviations, not as evidence that the original protocol specified those exact calculations.

How should the p-value be read?

A p-value measures how unusual data at least as incompatible with a null hypothesis would be under that hypothesis and the statistical model. It does not measure the probability that the null hypothesis is true, the size of an effect, or the likelihood that a finding will replicate. The primary unadjusted p-value is 0.865. Read alongside its interval, it indicates that the posted summary data do not provide strong evidence against a zero mean difference. It does not prove no difference or equivalence.

For a continuous outcome, uncertainty in the group means depends on the amount of spread in the observations and the number of observations contributing to each mean. Greater variability or fewer observations generally makes estimates less precise. In small groups, estimates of spread are themselves uncertain, and a small number of unusual observations can influence the mean and standard deviation. The registry does not provide participant-level results, so the influence of individual values cannot be assessed from the record.

Why distinguish an unadjusted comparison?

An unadjusted comparison means that the recalculation uses the posted group summary statistics without adjustment for other variables. It does not account for possible baseline imbalances, covariates, repeated measurements, or other features that a prespecified trial analysis might address. The record does not report whether the original analysis used an adjusted model or how it treated baseline values. No discrepancy is flagged between the posted summary statistics and the recalculated comparison, but that does not make the recalculation a replacement for a complete analysis.

The outcome description refers to change from baseline to 12 months, while the posted result supplies group means and standard deviations without separate baseline and follow-up summaries. The recalculated contrast therefore reflects the posted outcome summaries; it cannot independently verify the underlying change calculation or show the baseline values. The record does not report an analysis model for repeated observations or a method for dealing with missing measurements.

What can a standardized effect add?

A standardized effect expresses a mean difference relative to a measure of variability, which can help compare magnitudes across measures with different units. It does not replace the original scale, and its interpretation depends on the variability used and the context of the outcome. The posted primary standardized effect is -0.076. Because the raw outcome has a specific clinical meaning and the interval is wide, the standardized value should not be read in isolation or treated as a clinical threshold.

Overall, the methods support a cautious reading: the registry offers group summaries and recalculated unadjusted comparisons, but does not report enough detail to reconstruct a complete trial analysis. The estimates describe the posted data and their statistical uncertainty; they do not resolve the study's unreported design and analysis decisions.

11. Confidence Intervals and Precision

The primary mean difference is -0.4, with a confidence interval from -5.004 to 4.204. This interval includes zero, so the data are compatible with no mean difference as well as with differences in either direction. Its width indicates limited precision: the point estimate is much more specific than the range of values supported by the comparison.

Precision depends on the variability of the outcome and the amount of information available. The primary group standard deviations are 5.4 and 5.1, and the posted outcome groups each include 10 participants. In a small pilot study, estimates of both the mean and variability can be sensitive to the observed participants. The confidence interval reflects uncertainty under the calculation used, but it does not cover every possible source of uncertainty, such as unreported missing-data handling or measurement issues.

The interval should not be interpreted as a probability statement about the true effect, nor as a range of likely individual responses. It quantifies uncertainty in the estimated group contrast under the statistical assumptions. A confidence interval that includes zero does not establish equivalence: demonstrating equivalence would require a defined margin and a suitable analysis, neither of which is reported in the registry record.

The registry does not post a sponsor-reported inferential analysis for the primary outcome. The displayed comparison is a recalculated unadjusted estimate from summary statistics. Its interval is useful for understanding the scale of uncertainty in those summaries, but it does not supply missing details about the trial's planned analysis.

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 illustrations express the required number as participants per arm, not as a total across arms or as total events. They use the observed effect as a starting point and consider planning for 100%, 75%, and 50% of that observed effect. The assumptions listed for these illustrations are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The trial's own original design assumptions and sample-size justification are not reported in the registry record.

The 80% power column describes a planning target under which a study would have an 80% chance of detecting the specified effect if that effect were the true one and the assumptions held. The 90% power column uses a higher target probability of detection under the same stated framework. These are design calculations, not guarantees about what a future study will find. The figures are based on the observed effect in this pilot, which is itself uncertain.

The rows illustrate how the assumed effect size affects the planning requirement: planning to detect a smaller fraction of the observed effect requires more participants per arm. This is because smaller differences are harder to distinguish from random variation when variability and other assumptions are held within the calculation framework. The sample-size curve should be read as a visual expression of that same relationship, rather than as a separate finding about participant outcomes.

These planning figures are not observed power. They do not describe the probability that the completed study detected an effect, and they do not show that an effect is present. They are illustrations derived from the posted observed effect, not a record of the trial's original design calculation. Since the pilot estimate is imprecise, planning based only on that estimate may not represent the effect size a future study should target.

13. How the Sample Size Is Derived

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

Formula

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

Worked calculation for this trial

1. Observed difference Δ = -0.400; pooled standard deviation σ = 5.252.
2. n = 2 × (1.96 + 0.842)² × 5.252² / -0.400² = 2,706.4, rounded up to 2,707 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 <- -0.4                      # observed difference in means
sigma <- 5.25214242000348                     # 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(2903446)
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 = 2,707 (80% power), 3,624 (90% power)
 75% of observed effect: n per arm = 4,812 (80% power), 6,442 (90% power)
 50% of observed effect: n per arm = 10,826 (80% power), 14,493 (90% power)
power.t.test: 2707.4 
Simulated power at n = 2,707 per arm: 0.797 (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 multiple secondary outcomes in addition to the primary CT bone erosion score. When several outcomes are examined, the chance of at least one apparently unusual result can increase if each is assessed separately without accounting for the number of comparisons. Statistical approaches to multiplicity can adjust the interpretation or testing procedure, but the registry record does not report whether a prespecified multiplicity strategy was used. The secondary comparisons should therefore be viewed as unadjusted and exploratory rather than as a set of confirmatory tests.

The record does not report a complete statistical analysis plan, including the planned model for the primary outcome, treatment of baseline measurements, or handling of repeated measures. It also does not report an analysis population definition, such as whether the analysis followed assigned treatment regardless of adherence. Without those details, the posted estimates cannot be tied confidently to a particular prespecified estimand or analysis population.

Missing data are another unresolved issue. The registry does not report the number of participants with unavailable primary or secondary measurements, reasons for missingness, or any imputation or sensitivity-analysis method. The group results indicate the reported sample size for each displayed outcome, but do not explain whether all randomized participants contributed or whether results were available only for participants with observed measurements. This limits assessment of whether missingness could have affected the comparisons.

These gaps do not show that the trial analysis was conducted improperly. They mean that important details needed to evaluate its analytical robustness are not reported in the registry record. The displayed comparisons can be interpreted as unadjusted calculations from the posted summaries, while the planned handling of multiple outcomes, missing data, and analysis populations remains unknown.

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 0% reporting threshold.

Most frequent non-serious adverse event terms

The registry reports serious adverse events for both groups. In the intervention group, 0 of 10 participants at risk were reported with a serious adverse event; in the control group, the corresponding count was 0 of 10. The reported deaths were 0 in each group. These counts describe what was recorded in this study and do not establish that serious events cannot occur.

Other adverse events were reported for 5 of 10 participants at risk in the intervention group and 6 of 10 in the control group. The registry does not provide serious-event terms because no serious events are listed, and it does not give further detail about the other adverse events in the record. With small groups, these counts are descriptive and provide limited precision for comparing safety outcomes.

Safety counts should be interpreted alongside the study's size and follow-up context. The registry lists the intervention as denosumab administered every 6 months for a year with urate-lowering therapy. The posted counts do not establish comparative safety or capture risks beyond the events recorded in this study.

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

The primary result is an imprecise estimate of the difference in CT bone erosion score between denosumab added to urate-lowering therapy and standard urate-lowering therapy. The point estimate is -0.4, but its confidence interval extends from -5.004 to 4.204 and includes zero. The data therefore do not provide a precise estimate of the direction or size of a group difference.

This does not mean the study showed equivalence, nor does it establish that the intervention has no effect. The record does not report an equivalence margin or a confirmatory analysis designed to establish equivalence. A non-significant comparison can reflect uncertainty as well as a small or absent difference; the interval is important for seeing the range of values compatible with the posted data.

The study's pilot and proof-of-concept framing matters. A pilot can generate estimates, test study procedures, and help identify questions for later research, but an estimate from a small group can be unstable. The planning illustrations use the observed effects, and those observed estimates may themselves be uncertain. They should not be mistaken for definitive design requirements or evidence of treatment benefit.

The secondary outcomes add context but do not settle the primary question. Their pattern is mixed, the registry does not report a multiplicity strategy, and numerical results are not available for every listed secondary measure. The safety counts are also descriptive and limited in precision. Together, these posted data describe a small randomized comparison; they do not support medical advice or a broad conclusion about effects in all people with gout.

17. Why This Trial Matters Statistically

This study addresses a statistical distinction between managing gout and measuring structural damage. Its primary endpoint is a CT-based score of foot bone erosion, while the intervention was added to standard urate-lowering therapy. That makes the trial's question specific: whether the reported structural score differs between groups over the stated assessment period, rather than whether every aspect of gout or health changes.

The design is randomized, which is valuable for a controlled comparison, but the small pilot scale is reflected in the uncertainty around the primary estimate. The confidence interval is more informative than the point estimate alone because it shows how wide the range of compatible differences remains. It also prevents a non-significant p-value from being misread as proof of no effect.

The posted results illustrate why secondary outcomes and planning calculations need careful interpretation. Several domains are listed, but their numerical pattern is not uniform and the registry does not report a multiplicity strategy. Planning illustrations based on the pilot's observed effects are useful for showing how assumed effect size influences sample requirements, but they do not establish the true effect or recover the original design rationale.

Finally, the record demonstrates the value of distinguishing posted summaries from a reported prespecified analysis. Recalculated unadjusted comparisons can aid interpretation, but missing details about the analysis plan, missing data, and analysis populations constrain what can be concluded. These statistical considerations are central when reading a pilot trial whose central estimate is uncertain.

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 sample is small: the registry lists an enrollment of 20, and the primary outcome results include 10 participants in each arm. This limits precision and makes the estimates potentially sensitive to individual observations. The wide primary confidence interval reflects uncertainty in the group contrast.

The study was unmasked. The registry does not explain whether outcome readers were masked, so the potential for knowledge of assignment to influence CT scoring cannot be assessed from the record. Details of random sequence generation and allocation concealment are also not reported in the registry record.

The endpoint description states that the score is based on CT images at baseline and 12 months, but separate baseline and follow-up means are not posted. The record does not report scoring reliability, handling of unavailable scans, or whether the posted result includes all randomized participants. Missing-data methods and the analysis population are not reported in the registry record.

The registry does not provide the original sample-size justification, planned statistical analysis, interim-analysis information, or a multiplicity plan. The available comparisons are recalculated from summary statistics and are unadjusted. Numerical secondary results are posted for three measures, while the registry lists five secondary outcomes. These limitations make secondary findings exploratory and leave some outcome information unavailable.

Safety findings are also limited by the study size and the level of detail in the posted record. The serious adverse event counts and deaths are recorded, but the record does not provide further descriptions for the other adverse events. These constraints should accompany interpretation of both the efficacy-related estimates and the safety counts.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Denosumab In Addition To Intense Urate-Lowering Therapy for Bone Erosions — NCT02903446.
• Registry record last updated 2021-11-02; status last verified 2021-10.
• Results first posted 2021-08-31.
• 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

The registry record describes a completed Phase 2 randomized, unmasked, parallel-group pilot study of denosumab added to standard urate-lowering therapy for erosive gout. The intervention was denosumab 60 mg administered subcutaneously every 6 months for a year; the control was standard urate-lowering therapy.

The primary outcome was change in foot CT bone erosion score from baseline to 12 months, with higher scores indicating worsening erosion. The posted unadjusted mean difference was -0.4, and its confidence interval included zero. The secondary comparisons show a mixed pattern, and the record does not report multiplicity handling, missing-data methods, or the original statistical plan.

Safety counts report no serious adverse events or deaths in either group. Given the pilot scale and uncertainty in the primary estimate, the posted results are descriptive and exploratory rather than definitive.