MPC-004 for the Treatment of an Acute Gout Flare: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for MPC-004 for the Treatment of an Acute Gout Flare (NCT00506883), a randomized phase 3 study. The primary outcome is Responders.

2. Clinical Question

The trial addressed whether the proportion meeting that response definition differed between each colchicine-dose group and placebo. It also compared the two colchicine doses as part of a dose-comparison design, although the posted primary comparisons are against placebo. The outcome was binary: each participant either met the responder definition or did not.

The pain score used an 11 point scale from 0 to 10, with 10 described as the worst pain imaginable. The response required both a specified reduction in target joint pain and no rescue-drug use. Thus, the endpoint captures a combined pain-and-rescue-drug criterion rather than pain-score change alone.

The record describes a multicenter, randomized, double-blind, placebo-controlled, parallel-group study in patients with an acute gout flare. It lists 185 enrolled participants and an ITT population of 184 for the primary outcome. The posted outcome counts and comparisons allow a statistical reading of observed responder counts and their uncertainty, but do not answer questions beyond the defined outcome, follow-up time, and groups reported in the registry record.

3. Trial Design

The registry describes a phase 3, multicenter, randomized, double-blind, placebo-controlled, parallel-group dose-comparison study. Its official title specifies a 1 week study. The record lists 185 participants enrolled, a start date of 2007-04, primary completion in 2007-10, and a completed status. The sponsor is Takeda.

Participants were assigned to high-dose colchicine, low-dose colchicine, or placebo. The high-dose arm is recorded as a total dose of 4.8 mg. Its arm description says that after confirmation of a flare, patients were to begin standard dosing with two capsules initially, followed by additional one-capsule doses every hour for an additional 6 doses. The low-dose arm is recorded as a total dose of 1.8 mg. Its description says that treatment was to begin within 12 hours of a confirmed flare, with two capsules initially and one additional capsule an hour later; the remaining schedule is incomplete in the registry record. The placebo arm is listed, but its arm description is empty.

Randomization, double masking, and a parallel-group structure describe how the comparison was organized, but the registry record does not report the allocation ratio, randomization procedure, or details of how masking was maintained. The planned enrollment and the number included in the primary analysis are not the same figures: enrollment is 185, while the outcome description specifies an ITT population of N=184. The record does not explain the difference.

The primary outcome was assessed 24 hours after baseline. The posted results include responder counts for all three arms and two comparisons against placebo. No additional primary outcome or secondary outcome results are posted in the record. The trial’s original sample-size justification, detailed analysis plan, and information about interim analyses are not reported in the registry record.

4. Participant Flow and Accounting

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

Before assignment: 813 patients with confirmed diagnosis of gout based on American College of Rheumatology criteria were screened. 575 patients qualified and were randomized within 28 days of screening. 238 patients failed screening. The vast majority, 235 (98.7%) failed to meet inclusion/exclusion criteria.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: The Intent-to-Treat (ITT) population(N=184) was used. The ITT group is defined as all patients who were randomized,and had a qualifying gout flare based on contact with the Gout Flare Call Center, who were instructed to begin taking and took at least one dose of the study drug study drug. One patient had a flare, but

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 Responders, measured over 24 hours after baseline.

The primary endpoint was the number of participants classified as responders 24 hours after baseline. A responder had to achieve at least a 50% reduction from baseline in target joint pain score and not use rescue drug. Pain was scored on an 11 point scale from 0 to 10, with 10 representing the worst pain imaginable. This definition turns each participant’s pain and rescue-drug information into a yes-or-no outcome for the primary analysis.

A responder endpoint can be easier to interpret than an average score change because it states how many participants crossed a prespecified threshold and met the associated rescue-drug condition. It also preserves a clinically recognizable distinction between meeting and not meeting the study’s chosen response criterion. These are general features of binary responder endpoints; they do not establish whether this particular threshold was chosen for any specific reason. The rationale for selecting the threshold and time point is not reported in the registry record.

The result is specific to the combined definition and the 24-hour assessment. It is not a measure of every aspect of pain, the duration of response, or outcomes at later times. A participant who had a large pain reduction but used rescue drug would not meet the posted definition, just as a participant with a smaller pain reduction would not meet it. The reported counts therefore need to be interpreted as counts satisfying the complete endpoint rule, not as counts with any improvement in pain.

7. Results Posted in the Registry

• High Dose Colchicine(MPC-004): 32.7% (17/52) versus 15.5% (9/58) on control; risk difference 17.2 percentage points (95% CI 1.4 to 33.0), risk ratio 2.11 (1.03–4.31); unadjusted two-proportion z-test p = 0.034.
• Low Dose Colchicine(MPC-004): 37.8% (28/74) versus 15.5% (9/58) on control; risk difference 22.3 percentage points (95% CI 7.9 to 36.8), risk ratio 2.44 (1.25–4.75); unadjusted two-proportion z-test p = 0.005.

8. Statistical Interpretation

9. Statistical Methods Explained

The posted outcome is binary: each participant is counted as a responder or not a responder. For a binary outcome, the arm-level result can be expressed as a count of events and the number of participants assessed. The count alone is not enough to compare groups when their sizes differ, so comparisons use a measure that relates the event frequency in one group to the event frequency in another.

What does a risk difference describe?

A risk difference subtracts one group’s event probability from the other group’s event probability. Here, the posted comparisons place each colchicine group against placebo. The estimates are 0.172 for high dose and 0.223 for low dose. A value above zero indicates a higher observed responder probability in the colchicine group under the comparison’s direction. The risk difference is an absolute contrast, rather than a relative multiplier. It is useful when the question concerns the size of the gap between groups on the probability scale.

The reported risk differences are not the raw participant counts. They summarize the comparison after accounting for the different group denominators. The registry also reports relative risks and odds ratios, which express contrasts on different scales. A relative risk compares event probabilities; an odds ratio compares event odds. These measures can appear numerically different because they answer related but distinct questions. The registry does not give a direct comparison between the two active arms.

What does a confidence interval add?

A point estimate gives one value for the group contrast, while a confidence interval describes the range of values reasonably compatible with the observed data under the interval method. For high-dose colchicine versus placebo, the risk-difference estimate is 0.172 and its interval is 0.014 to 0.330. For low-dose colchicine versus placebo, the estimate is 0.223 and its interval is 0.079 to 0.368. The interval’s width conveys precision: narrower intervals indicate less statistical uncertainty than wider intervals, all else equal. A confidence interval is not a prediction range for individual outcomes and does not ensure that a future study will reproduce a value inside it.

How should the p-values be read?

The registry reports unadjusted p-values of 0.034 for high-dose colchicine versus placebo and 0.005 for low-dose colchicine versus placebo. In general, a p-value evaluates how unusual data at least as discrepant as those observed would be under a specified null hypothesis and model. It is not the probability that the null hypothesis is true, nor does it measure the size or practical importance of a contrast. Since the record labels these values unadjusted and does not describe a multiplicity procedure, they should not be treated as multiplicity-adjusted results.

The record does not identify the test used for the posted comparisons or describe assumptions and adjustments in sufficient detail. It also reports no separate statistical analyses in the analysis listing. Therefore, the posted estimates and p-values can be described, but the precise testing method cannot be reconstructed from the registry record.

Why does the endpoint’s binary form matter?

The response rule combines a reduction in target joint pain with no rescue-drug use. This creates a participant-level classification that can be compared across randomized arms. Binary outcomes are often summarized with event counts and proportions, and the between-group estimates depend on both the number meeting the rule and the number assessed. A thresholded outcome is also sensitive to the chosen cutoff: people just on different sides of the threshold receive different classifications even if their underlying scores are similar. That is a general property of threshold-based endpoints, not a claim about individual participants in this study.

Since the posted primary analysis uses an ITT population, its stated population includes randomized participants with a qualifying flare who were instructed to start study drug and took at least one dose. The record does not clarify how missing endpoint data were handled or whether every member of that defined population had a measured 24-hour outcome. Those details matter because exclusion or imputation of missing outcomes can affect a binary comparison. No missing-data method or sensitivity analysis is reported in the registry record.

10. Confidence Intervals and Precision

The risk-difference estimates are 0.172 for high-dose colchicine versus placebo and 0.223 for low-dose colchicine versus placebo. Their confidence intervals are 0.014 to 0.330 and 0.079 to 0.368, respectively. Each interval gives a range around its estimate rather than a single certain value. Both posted intervals are above zero, but their widths show that the exact size of each contrast remains uncertain.

The high-dose confidence interval extends from 0.014 to 0.330; the low-dose interval extends from 0.079 to 0.368. These ranges are substantial relative to their point estimates. That spread is consistent with limited precision in estimates based on group counts of 52.0, 74.0, and 58.0. The data support a range of plausible contrasts under the interval method, not certainty that the point estimate is the true contrast.

Confidence intervals are often described through repeated-sampling properties: under the method’s assumptions, intervals constructed in the same way would cover the underlying parameter at the stated confidence level at the corresponding long-run frequency. The registry record does not state the confidence level or interval construction method in the comparison description, so those details cannot be specified from this record. An interval should not be interpreted as the range containing most participants’ outcomes or as a guarantee about a replication.

The posted relative-risk and odds-ratio intervals are also broad. For high dose, the relative-risk interval is 1.03 to 4.311 and the odds-ratio interval is 1.057 to 6.616. For low dose, the corresponding intervals are 1.251 to 4.755 and 1.414 to 7.769. These alternative scales reinforce that the comparisons have uncertainty, while their numeric ranges should not be compared directly with risk-difference intervals because the measures use different scales.

11. 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 figures are planning illustrations for a two-arm comparison, expressed as participants per arm. They are not total event counts. For each comparison, the illustration uses the observed effect as its reference and shows planning for 100%, 75%, or 50% of that observed effect. The high-dose comparison lists 97 participants per arm for 80% power and 129 participants per arm for 90% power when planning for 100% of the observed effect; the corresponding figures for 75% are 161 and 215, and for 50% are 337 and 451. The low-dose comparison lists 61 and 81 participants per arm for 100%, 101 and 135 for 75%, and 209 and 279 for 50%.

The 80% power column means the planned design would have an 80% chance of detecting the stated effect under the planning assumptions, if the assumed effect and other assumptions were correct. The 90% column describes a higher target chance of detection under those same assumptions. These are design calculations, not properties of the observed trial result. Smaller effects require more participants in the planning illustrations because weaker contrasts are harder to distinguish from random variation.

The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation; the effect to detect is the stated fraction of the observed effect. The original trial’s own sample-size assumptions and justification are not reported in the registry record. These figures are planning illustrations based on the observed effects, not observed power.

12. 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, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.155; treatment proportion p₁ = 0.327; average p̄ = 0.241.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6049 = 1.1856.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.5926 = 0.4987.
4. n = (1.1856 + 0.4987)² / (0.1718)² = 96.2, rounded up to 97 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
p0 <- 0.155172413793103                          # control proportion
p1 <- 0.326923076923077                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^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 (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(506883)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 97 (80% power), 129 (90% power)
 75% of observed effect: n per arm = 161 (80% power), 215 (90% power)
 50% of observed effect: n per arm = 337 (80% power), 451 (90% power)
power.prop.test: 96.2 
Simulated power at n = 97 per arm: 0.808 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-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.

13. Multiplicity, Missing Data and Analysis Populations

The primary outcome description identifies the ITT population as N=184. It defines that population as randomized patients who had a qualifying gout flare based on contact with the Gout Flare Call Center, were instructed to begin taking study drug, and took at least one dose. The record does not explain why this analysis population differs from the total enrollment of 185, or state how the participant outside the defined ITT population was handled.

The registry posts two primary comparisons against placebo, one for each colchicine dose, and gives unadjusted p-values for both. It does not report a multiplicity adjustment, a testing hierarchy, or a prespecified procedure for controlling error across comparisons. Without that information, the unadjusted values should be interpreted as the listed comparison results, not as evidence that any adjustment was applied. The record does not post a direct test comparing high-dose with low-dose colchicine.

No secondary outcome results are posted. The registry lists one outcome measure, and the analysis listing contains no analyses. That does not establish that no additional analyses were performed; it means they are not reported in the registry record. The statistical analysis plan, including any planned subgroup analyses, is not reported.

The registry record also does not report the amount or pattern of missing outcome data, the method used to handle missing 24-hour assessments, or sensitivity analyses evaluating alternative missing-data assumptions. Such information can matter for binary outcomes because the classification depends on having enough information to determine whether the responder rule was met. The ITT definition is available, but the analysis handling beyond that definition is not specified.

Interim analyses and stopping rules are not reported in the registry record. Neither are the original sample-size rationale, the detailed test used for each comparison, or any covariate adjustment. These omissions limit how completely the posted estimates can be audited or connected to a prespecified analysis strategy.

14. Safety Results

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

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 1.4% reporting threshold.

Most frequent non-serious adverse event terms

The registry reports zero serious adverse events in each group: 0 among 52 participants at risk in the high-dose colchicine group, 0 among 74 in the low-dose group, and 0 among 59 in the placebo group. The placebo safety denominator is 59, while the posted placebo responder denominator is 58. The registry record does not explain this difference. The death counts are not reported in the registry record.

Zero reported serious adverse events means no serious events were recorded in the listed group counts. It does not establish that the underlying risk is zero. With finite numbers of participants, an event that was not observed may still be possible. The registry does not list serious adverse-event terms, and does not provide further detail about event definitions, timing, severity beyond the serious classification, or causality assessment.

The record also lists other adverse events affecting 40 participants in the high-dose group, 27 in the low-dose group, and 16 in the placebo group. Those counts are separate from the serious-event counts and should not be conflated with them. The registry’s adverse-event figures alone do not describe the specific events or establish a causal relationship to study treatment.

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

The posted results describe how many participants met a particular responder definition 24 hours after baseline and how the estimated responder probability in each colchicine group compared with placebo. The high-dose estimate is a risk difference of 0.172, and the low-dose estimate is 0.223. Both are positive, and their posted confidence intervals are above zero. These findings describe the reported endpoint and comparisons; they do not by themselves establish how the result applies to every patient or setting.

The result does not show whether high-dose colchicine and low-dose colchicine differ from one another. The registry posts two separate comparisons against placebo, not a direct active-dose comparison. Comparing the two point estimates informally is not a substitute for a statistical test of their difference, which is not reported. Nor does the 24-hour responder measure establish the duration of any response or describe later outcomes.

The endpoint is a composite decision rule in the practical sense that it requires both a pain-score reduction and no rescue-drug use. It does not measure pain alone, and it does not capture every possible patient experience. A response classification cannot provide the full distribution of pain scores or changes for those who did not meet the threshold. The record does not post a secondary outcome that would broaden that assessment.

The uncertainty intervals are important alongside the point estimates. They indicate that the exact magnitude of each risk difference is not known precisely. The p-values are unadjusted, and the registry does not report a multiplicity plan, missing-data procedure, detailed statistical analysis plan, or interim analysis information. Those omissions constrain interpretation of the comparisons and prevent a complete review of the analysis strategy.

The safety record lists no serious adverse events in the groups, but the group sizes and lack of further event detail mean this should not be read as proof of no serious-event risk. Other adverse-event counts are also posted. These registry entries describe reported events; they do not alone establish treatment causality. No medical conclusion should be drawn beyond the statistical description of the outcomes and safety counts in the record.

16. Why This Trial Matters Statistically

This trial illustrates how a randomized, placebo-controlled design can produce interpretable between-group contrasts for a binary clinical endpoint. The primary outcome was not simply a pain score: it required a threshold reduction in target joint pain and no rescue-drug use. That definition makes the endpoint’s construction central to understanding the reported counts and comparisons.

It also illustrates why effect measures should be read alongside one another. The risk difference gives an absolute contrast, while the relative risk and odds ratio express relative contrasts on different scales. The confidence intervals show that the point estimates are not exact, and the unadjusted p-values do not convey the size or precision of the effect. Together, these statistics answer different questions and should not be treated as interchangeable.

The two active arms make the limits of indirect comparison particularly relevant. Each is reported against placebo, but the record does not report a direct high-dose versus low-dose test. A larger estimate in one active arm is not, by itself, evidence of a statistically established difference between dose groups. This distinction is important whenever a trial has multiple arms and only some contrasts are posted.

The record also shows the importance of analysis transparency. It specifies an ITT population but does not describe missing-data handling, multiplicity control, interim analyses, or the original sample-size justification. Those details help readers evaluate how estimates were produced and how much weight to place on multiple comparisons. Their absence does not erase the posted results, but it limits the scope of statistical interpretation.

Finally, the safety entries illustrate that zero observed serious adverse events is not equivalent to zero underlying risk. Counts need their denominators and context, and the placebo safety denominator differs from its responder denominator. Clear reporting of populations, endpoint definitions, analysis choices, and event denominators is essential for a reliable reading of clinical-trial statistics.

17. 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 primary outcome is measured at 24 hours after baseline, so the posted comparison is limited to that assessment. Although the official title describes a 1 week study, no longer-term primary outcome is reported. The registry lists one outcome measure and no secondary outcome results, limiting the range of outcomes available for statistical interpretation.

The responder rule depends on both a specified reduction in target joint pain and no rescue-drug use. It therefore cannot be interpreted as pain change alone. The registry record does not report the rationale for the 50% threshold or the 24-hour time point, and it does not provide the full distribution of pain scores.

The posted primary analysis uses an ITT population of 184, while total enrollment is 185. The record does not explain the difference or specify the treatment of missing outcome data. The placebo responder denominator is 58, whereas the placebo safety denominator is 59; no explanation is reported. These population and denominator details should be kept distinct rather than assumed to reflect the same analysis set.

Two comparisons against placebo are posted, with unadjusted p-values. A multiplicity strategy, direct comparison between the colchicine doses, and detailed analysis plan are not reported. The record also does not describe the statistical test, interim analyses, or original sample-size justification. The low-dose regimen description is incomplete, and the placebo arm description is empty.

The safety entries report no serious adverse events in the listed groups, but deaths are not reported and further event-level detail is not provided. The counts do not establish causality or eliminate the possibility of events not observed in the trial. These limitations apply to what can be concluded from the registry record and do not establish that unreported procedures or analyses were absent.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: MPC-004 for the Treatment of an Acute Gout Flare — NCT00506883.
• Registry record last updated 2012-11-01; status last verified 2012-10.
• Results first posted 2009-09-22.
• 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.

21. Record Summary

NCT00506883 is a completed phase 3, randomized, double-blind, parallel-group, placebo-controlled study of high-dose colchicine, low-dose colchicine, and placebo for acute gout flares. The record lists 185 participants enrolled and identifies Takeda as sponsor. The study began in 2007-04 and reached primary completion in 2007-10.

The primary outcome was responders 24 hours after baseline, defined by at least a 50% reduction in target joint pain score without rescue drug. The ITT population was N=184. The posted responder counts were 17.0 of 52.0 for high-dose colchicine, 28.0 of 74.0 for low-dose colchicine, and 9.0 of 58.0 for placebo. The posted risk differences against placebo were 0.172 and 0.223, respectively, with unadjusted p-values of 0.034 and 0.005.

No secondary outcome results are posted. The registry reports zero serious adverse events in each arm; death counts are not reported. Details of multiplicity handling, missing-data methods, the original sample-size justification, and interim analyses are not reported in the registry record.