Efficacy Study of CDP870 in Subjects With Chronic Plaque Psoriasis Who Are Candidate for Systemic Therapy and/or Phototherapy/Photochemotherapy: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Efficacy Study of CDP870 in Subjects With Chronic Plaque Psoriasis Who Are Candidate for Systemic Therapy and/or Phototherapy/Photochemotherapy (NCT00245765), a randomized phase 2 study. The primary outcome is Achievement of Psoriasis Activity and Severity Index (PASI75) Response at Week 12.

2. Clinical Question

The trial addressed a short-term response question in people with chronic plaque psoriasis for whom systemic therapy and/or light-based therapy was being considered. The comparison included two active dosing regimens and placebo. The primary outcome was a threshold response measured at a specified visit, rather than a continuous change in the PASI score or a time-to-response outcome.

The registry record lists a follow-up period of 12 to 24 weeks after the 12-week treatment period. The primary question concerns the week 12 assessment; it does not by itself answer how long a response lasted or what happened throughout follow-up. Secondary outcomes included time to PASI50 and PASI75, time to relapse, other week 12 PASI response thresholds, body surface area measures, and rebound after stopping therapy.

3. Trial Design

The registry identifies this as a phase 2, randomized, quadruple-masked, parallel-group, placebo-controlled study. The official title describes a multicenter trial. The sponsor was UCB Pharma, and the recorded status is completed. Enrollment is listed as 176. The registry record lists a start of 2005-10 and primary completion of 2006-11.

The three groups were placebo, certolizumab pegol 200 mg, and certolizumab pegol 400 mg. The 200 mg regimen began with a 400 mg initial dose at week 0 and continued with 200 mg every 2 weeks. The 400 mg regimen used 400 mg every 2 weeks. Placebo was administered by subcutaneous injection every 2 weeks. The brief summary describes treatment during 12 weeks, extended by a 12 to 24 week follow-up.

Randomization and masking help reduce the risk that allocation or knowledge of treatment influences outcome assessment, although the registry entry does not detail how these procedures were implemented. The parallel-group design means the groups were followed as separate treatment groups rather than participants crossing between regimens. The primary endpoint population is described as intention-to-treat and includes all randomized subjects. The recorded group sizes for this endpoint were 59 for placebo, 59 for the 200 mg regimen, and 58 for the 400 mg regimen.

The registry record does not report the original sample-size justification, allocation ratio, details of masking procedures, or the full protocol. It also does not report the planned statistical analysis in enough detail to establish all model choices, covariate adjustments, missing-data rules, or multiplicity procedures.

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: The study included a 12-week Treatment Period and a 12 to 24-week Follow-up Period. Participant Flow refers to the Intention-to-treat Set.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Intention-To-Treat (ITT) population consisting of all randomized subjects.

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

Population: Baseline Characteristics refer to the Intention-To-Treat (ITT) population consisting of all randomized subjects.

6. Primary Endpoint

The registry lists the primary outcome as Achievement of Psoriasis Activity and Severity Index (PASI75) Response at Week 12, measured over Week 12.

The primary endpoint was achievement of a Psoriasis Area and Severity Index (PASI) 75 response at week 12, reported as the percentage of subjects. A response was defined as a decrease in PASI score from baseline of at least 75%. The registry describes the PASI score as assessing erythema, infiltration, desquamation, and body surface area involvement across the head, trunk, and upper and lower extremities.

A threshold endpoint turns a change in a clinical score into a responder classification: each participant either meets the specified response threshold or does not. Reporting the percentage meeting that threshold makes the outcome interpretable as the frequency of response in each group. The threshold is part of the endpoint definition; it is not a measure of the full range of score changes among participants.

The week 12 timing fixes the point at which response was assessed. It does not describe response at every point during treatment, persistence after treatment, or longer-term outcomes. The registry record identifies the analysis population as all randomized subjects. It does not state how missing week 12 assessments were handled, so the posted percentages should be read alongside that limitation.

7. Results Posted in the Registry

• Certolizumab Pegol 200 mg (ITT): 74.6% (44/59) versus 6.8% (4/59) on control; risk difference 67.8 percentage points (95% CI 55.0 to 80.6), risk ratio 11.00 (4.22–28.67); unadjusted two-proportion z-test p = <0.001.
• Certolizumab Pegol 400 mg (ITT): 82.8% (48/58) versus 6.8% (4/59) on control; risk difference 76.0 percentage points (95% CI 64.3 to 87.6), risk ratio 12.21 (4.70–31.67); unadjusted two-proportion z-test p = <0.001.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Achievement of a Psoriasis Activity and Severity Index (PASI50) Response at Week 12

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Certolizumab Pegol 200 mg (ITT): 86.4% (51/59) versus 11.9% (7/59) on control; risk difference 74.6 percentage points (95% CI 62.6 to 86.6), risk ratio 7.29 (3.61–14.71); unadjusted two-proportion z-test p = <0.001.
  • Certolizumab Pegol 400 mg (ITT): 93.1% (54/58) versus 11.9% (7/59) on control; risk difference 81.2 percentage points (95% CI 70.7 to 91.8), risk ratio 7.85 (3.90–15.79); unadjusted two-proportion z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for Certolizumab Pegol 200 mg (ITT) than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for Certolizumab Pegol 400 mg (ITT) than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Achievement of a Psoriasis Activity and Severity Index (PASI90) Response at Week 12

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Certolizumab Pegol 200 mg (ITT): 39.0% (23/59) versus 1.7% (1/59) on control; risk difference 37.3 percentage points (95% CI 24.4 to 50.2), risk ratio 23.00 (3.21–164.82); unadjusted two-proportion z-test p = <0.001.
  • Certolizumab Pegol 400 mg (ITT): 46.6% (27/58) versus 1.7% (1/59) on control; risk difference 44.9 percentage points (95% CI 31.6 to 58.1), risk ratio 27.47 (3.86–195.52); unadjusted two-proportion z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for Certolizumab Pegol 200 mg (ITT) than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for Certolizumab Pegol 400 mg (ITT) than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Experience of a Rebound Effect Within 2 Months After Stopping Therapy

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Certolizumab Pegol 200 mg (ITT): 1.7% (1/59) versus 15.3% (9/59) on control; risk difference -13.6 percentage points (95% CI -23.3 to -3.8), risk ratio 0.11 (0.01–0.85); unadjusted two-proportion z-test p = 0.008.
  • Certolizumab Pegol 400 mg (ITT): 1.7% (1/58) versus 15.3% (9/59) on control; risk difference -13.5 percentage points (95% CI -23.3 to -3.8), risk ratio 0.11 (0.01–0.86); unadjusted two-proportion z-test p = 0.009.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically lower for Certolizumab Pegol 200 mg (ITT) than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically lower for Certolizumab Pegol 400 mg (ITT) than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The posted secondary outcomes broadly follow the same direction as the primary endpoint: the week 12 response measures show higher recorded response percentages in both active groups than in placebo, while the recorded rebound outcome after stopping therapy is lower in the active groups than in placebo. Body surface area measures, time to response, and time to relapse are also listed as secondary outcomes, but the registry record does not provide posted results for every listed measure in the registry record for this analysis.

These outcomes add context to the primary finding because they describe other response thresholds, timing, body surface area, or outcomes after stopping treatment. They do not replace the primary week 12 PASI75 comparison. Nor should the secondary outcomes be treated as independent confirmation without considering their analysis plans and the possibility of multiple testing.

The posted secondary comparisons are unadjusted. When many outcomes and comparisons are examined, the chance of observing a nominally unusual result somewhere among them can rise. Without a reported multiplicity strategy, secondary p-values carry less weight than a prespecified primary analysis and are more appropriately viewed as supportive or exploratory. The registry record does not report a hierarchy, adjustment procedure, or complete statistical plan for the secondary analyses.

The pattern across endpoints is therefore useful as descriptive evidence, but it does not establish that every outcome changed reliably or that results persisted beyond the assessments specified. In particular, a difference in response thresholds at week 12 does not answer the separate question of response duration. Time-to-event outcomes require information about event timing and censoring; the statistical details for those analyses are not reported in the registry record.

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

• Time to Psoriasis Activity and Severity Index 50 (PASI50)
• Time to Psoriasis Activity and Severity Index 75 (PASI75)
• Time to Relapse
• Achievement of a Psoriasis Activity and Severity Index (PASI50) Response at Week 12
• Achievement of a Psoriasis Activity and Severity Index (PASI90) Response at Week 12
• Experience of a Rebound Effect Within 2 Months After Stopping Therapy
• Percent of Body Surface Area (BSA) Affected by Psoriasis at Week 12
• Absolute Change From Baseline in the Body Surface Area (BSA) Affected by Psoriasis at Week 12

9. Statistical Interpretation

10. Statistical Methods Explained

For a binary responder outcome, each participant is classified according to whether the endpoint definition was met. The group response percentage is the proportion classified as responders, expressed as a percentage. In general, this approach is easy to interpret, but it compresses the underlying score information: two participants with different changes can both count as responders if they cross the same threshold, while a participant just short of the threshold is classified as a non-responder.

What does a risk difference represent?

A risk difference subtracts the response proportion in the comparison group from the response proportion in the reference group. In these recalculations, placebo is the reference and each active regimen is compared with it. A positive estimate means the posted response proportion is higher in the active group; a negative estimate means it is lower. The recalculated primary risk differences are 0.678 for the 200 mg comparison and 0.760 for the 400 mg comparison. These are simple unadjusted calculations from the posted summary statistics, not adjusted model estimates.

These estimates use proportions rather than odds. Odds compare the frequency of an event with the frequency of no event; an odds ratio compares those odds between groups. Odds ratios can look numerically quite different from risk differences, especially when an outcome is common. They should therefore be interpreted on their own scale rather than translated informally into a difference in percentages.

What do the p-values address?

A p-value is a measure of how incompatible the observed data are with a specified null hypothesis, under the assumptions of the statistical test. A small p-value is evidence against that null within the model and comparison being tested; it is not the probability that the null hypothesis is true. It does not measure the size or clinical importance of an effect. The registry reports p < 0.001 for each primary comparison in its logistic-regression analyses, and the simple unadjusted recalculations also report p < 0.001.

The registry’s sponsor analyses use logistic regression and report odds ratios. The recalculations use the posted group-level responder counts and denominators to estimate unadjusted risk differences. These methods answer related but not identical questions and rely on different effect scales. The record does not report the covariates, link-function details beyond the logistic-regression label, or other model specifications. It also does not explain whether any adjustments beyond the reported regression were used.

Why use an intention-to-treat population?

The primary population is defined in the registry as all randomized subjects. An intention-to-treat approach generally seeks to retain participants in their randomized groups for analysis, preserving the comparison created by randomization. The label alone does not specify how every randomized participant’s endpoint was handled when an assessment was unavailable. The missing-data rules and the number of missing primary assessments are not reported in the registry record.

For context, general statistical reasoning distinguishes the estimated effect from the uncertainty around it. The risk difference is an estimate; an interval around it describes a range of values compatible with the data and the method used, under the interval’s assumptions. Wider intervals indicate less precision than narrower intervals. An interval’s interpretation depends on its confidence level and construction. The recalculated interval confidence level is not specified in the registry record, so it is best described as the posted interval rather than assigned a confidence level not stated there. The sponsor’s reported odds-ratio intervals are explicitly 95% intervals.

Why does multiplicity matter?

When several outcomes, doses, time points, or pairwise comparisons are tested, the chance of obtaining at least one small p-value by chance can increase if each test is assessed without adjustment. A multiplicity plan can define which outcomes are primary, how comparisons are prioritized, and whether statistical thresholds are adjusted. The registry lists multiple secondary outcomes and two active-versus-placebo primary analyses. Its multiplicity strategy is not reported in the registry record. Consequently, the reported p-values should be understood as attached to the individual analyses shown, not as evidence that a family-wide error rate was controlled.

11. Confidence Intervals and Precision

The estimated risk differences are accompanied by intervals that convey uncertainty in the treatment contrasts. For certolizumab pegol 200 mg versus placebo, the recalculated risk difference is 0.678, with an interval from 0.550 to 0.806. For certolizumab pegol 400 mg versus placebo, it is 0.760, with an interval from 0.643 to 0.876. Both intervals lie above zero, matching the direction of the observed group percentages and the small reported p-values.

An interval is not a guarantee that the true effect lies within its endpoints. In general, it is a range generated by a statistical procedure that reflects sampling uncertainty under its assumptions. Its width is informative about precision: greater width means a broader range of values remains compatible with the estimate and data. The intervals are on the risk-difference scale. The registry record does not label the confidence level for these recalculated intervals, so no confidence percentage should be assigned to them.

The sponsor’s logistic-regression analyses report odds ratios with 95% intervals. For the 200 mg comparison, the reported odds ratio is 40.2, with a 95% interval from 13.7 to 150.3. For the 400 mg comparison, it is 73.4, with a 95% interval from 23.5 to 292.6. These intervals are broad, indicating uncertainty about the magnitude on the odds-ratio scale even though both reported comparisons have p < 0.001. The odds-ratio intervals cannot be directly compared numerically with the risk-difference intervals because they describe different effect measures.

The recorded endpoint group sizes were 59, 59, and 58. The precision of an estimate also depends on the number of observed outcomes, the distribution of responses, and the analysis method. The registry record does not report enough information about missing assessments or model details to assess their contribution to uncertainty in full.

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 figures are planning illustrations based on the observed effect, not the trial’s original design assumptions. For the binary outcomes in this analysis, the figures are participants per arm. The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each illustration uses an effect equal to the stated fraction of the observed effect. The original trial’s sample-size justification is not reported in the registry record.

The 80% power column gives the illustrative number of participants per arm for an analysis to have an 80% chance of detecting the chosen effect under the stated assumptions, if that effect is the true one. The 90% power column uses a higher target chance of detection and generally requires more participants. For example, the primary comparison for the 200 mg regimen lists 7 participants per arm for 80% power and 9 participants per arm for 90% power when planning for 100% of the observed effect. Planning for 50% of that observed effect lists 24 participants per arm for 80% power and 31 participants per arm for 90% power.

Smaller effects are harder to distinguish from random variation, so the illustrations require more participants per arm when the target is a smaller fraction of the observed effect. These figures are not observed power. They do not show the probability that this completed trial “had power” after seeing its results; they illustrate hypothetical future planning under the listed assumptions. The assumptions may not match the trial’s original design or the needs of a future study.

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

Worked calculation for this trial

1. Control proportion p₀ = 0.068; treatment proportion p₁ = 0.746; average p̄ = 0.407.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6947 = 1.3616.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.5028 = 0.4232.
4. n = (1.3616 + 0.4232)² / (0.6780)² = 6.9, rounded up to 7 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 <- 0.0677966101694915                          # control proportion
p1 <- 0.745762711864407                          # 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(245765)
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 = 7 (80% power), 9 (90% power)
 75% of observed effect: n per arm = 13 (80% power), 16 (90% power)
 50% of observed effect: n per arm = 24 (80% power), 31 (90% power)
power.prop.test: 6.9 
Simulated power at n = 7 per arm: 0.832 (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.

14. Analyses Reported by the Sponsor

The sponsor’s own primary analyses use logistic regression and report odds ratios for each active regimen versus placebo. For certolizumab pegol 200 mg, the reported odds ratio is 40.2, with a 95% interval from 13.7 to 150.3 and p < 0.001. For certolizumab pegol 400 mg, the reported odds ratio is 73.4, with a 95% interval from 23.5 to 292.6 and p < 0.001. Both comparisons are labelled superiority in the registry.

The recalculations use the posted counts and denominators to estimate unadjusted risk differences. They are not replacements for the sponsor’s regression analyses: they use a different effect scale and do not reproduce any model adjustment. The recalculated direction and the reported sponsor results are consistent in indicating higher response in each active group than placebo. The registry record marks no discrepancy between these analyses.

When a recalculation conflicts with a sponsor analysis, the sponsor’s own analysis takes precedence for representing the analysis reported by the trial. In this record, the important distinction is not a conflicting conclusion, but the difference between adjusted or model-based odds ratios and simple, unadjusted differences in proportions. The registry does not report enough model detail to reproduce the sponsor’s estimates independently.

15. Multiplicity, Missing Data and Analysis Populations

The primary endpoint has two active-versus-placebo comparisons, and the registry lists multiple secondary outcomes, including additional PASI response thresholds and outcomes related to response timing, relapse, body surface area, and rebound. Testing multiple hypotheses can increase the chance of at least one false-positive result when each test is interpreted at a conventional threshold without adjustment. A prespecified testing hierarchy or multiplicity adjustment can address that issue, but such a strategy is not reported in the registry record.

The record reports logistic-regression analyses for the two primary comparisons and gives their odds ratios, 95% intervals, and p-values. It does not report whether those tests were adjusted for the two comparisons or how they fit into an overall testing plan. The recalculated risk differences and their p-values are unadjusted. Thus, the small p-values indicate evidence against the null for the individual comparisons as analyzed, but they do not establish family-wise error control across all outcomes and tests.

The primary population is identified as intention-to-treat and defined as all randomized subjects. This is relevant because retaining randomized participants in their assigned groups can preserve the balance created by randomization. However, the registry record does not report how missing week 12 outcomes were handled, how many were missing, or whether any imputation or other missing-data method was used. It also does not report a sensitivity analysis addressing missing outcomes.

The record does not provide enough information to assess deviations from assigned treatment, adherence, or the handling of intercurrent events in the primary analysis. The adverse-event population is labelled SS, but its relationship to the primary intention-to-treat population is not explained. These gaps do not negate the posted results; they limit how fully the analysis can be evaluated and reproduced.

16. Safety Results

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

Deaths

Other (non-serious) adverse events

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

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: pregnancy (3.5%), disseminated tuberculosis (1.8%), gastroenteritis (1.8%), anxiety (1.8%), psoriasis (1.8%).

The registry reports serious adverse events by safety-set group. Serious adverse events affected 1 of 58 participants in the placebo group, 2 of 60 in the certolizumab pegol 200 mg group, and 5 of 57 in the certolizumab pegol 400 mg group. Deaths were recorded as 0 in each group. These counts describe the events recorded in this trial; they are not adjusted comparisons and do not establish whether differences between groups are meaningful.

Other adverse events affected 34 of 58 participants in the placebo group, 32 of 60 in the 200 mg group, and 27 of 57 in the 400 mg group. The registry also lists serious-event terms with percentages, including Pregnancy at 3.5%, and Disseminated tuberculosis, Gastroenteritis, Anxiety, and Psoriasis at 1.8% each, and Diarrhoea haemorrhagic at 1.7%. The available record does not provide enough context to assign each listed term to a specific treatment group or infer a comparative rate.

Adverse-event counts need interpretation alongside the size and duration of exposure, event definitions, and ascertainment procedures. Those details are not fully reported in the registry record. The figures are descriptive safety information from this study, not a basis for predicting an individual’s risk.

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

The posted primary results show higher week 12 PASI75 response percentages in both certolizumab pegol groups than in the placebo group. The sponsor’s logistic-regression analyses report superiority for both active-versus-placebo comparisons, with p < 0.001 for each. The unadjusted recalculations point in the same direction. Together, these findings describe a clear separation in the recorded week 12 responder proportions within this randomized trial.

That result is specific to the endpoint, population, and follow-up point recorded. PASI75 classifies participants according to whether their PASI score decreased from baseline by at least 75%; it does not show the distribution of changes among responders or non-responders. A week 12 response does not establish how long a response lasts, whether it continues after treatment, or how outcomes compare over longer periods.

The results do not establish a difference between the two active regimens, because the reported primary analyses compare each regimen with placebo rather than directly comparing the doses. Nor do the results alone establish the clinical importance of the observed contrasts, the balance of benefits and harms, or applicability to people unlike those enrolled. Those judgments require context beyond statistical significance and depend on evidence not reported in the registry entry.

The trial’s primary completion and overall status are recorded, but the registry information does not provide the full protocol, detailed missing-data procedures, or a complete multiplicity plan. The listed safety counts are also descriptive and do not by themselves establish comparative safety. No treatment choice or individual medical decision follows from these statistics alone.

18. Why This Trial Matters Statistically

This trial illustrates why the choice of effect measure matters. The sponsor reports logistic-regression odds ratios, while the simple recalculations express the active-versus-placebo contrast as a risk difference. Both approaches can describe the same binary endpoint, but they answer on different scales. Keeping those scales distinct prevents an odds ratio from being mistaken for a percentage-point difference.

It also demonstrates the value of reading estimates together with uncertainty. The response percentages and contrasts convey the observed pattern, while intervals show that the magnitude remains uncertain. Small p-values do not eliminate that uncertainty, establish clinical importance, or resolve questions about the analysis plan.

The record also highlights practical issues in trial interpretation: two active comparisons, multiple secondary outcomes, and incomplete reporting of multiplicity and missing-data methods. These features matter when deciding how much weight to give each result. A well-defined primary endpoint can focus interpretation, but it does not remove the need to understand what was tested and how incomplete observations were handled.

Finally, planning calculations based on observed effects can be misleading if treated as proof that a study was adequately designed. Such calculations are hypothetical illustrations that depend on assumptions and on the estimated effect used as their starting point. They are not observed power and cannot substitute for the original design justification, which is not reported in the registry record.

19. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.
• Participant counts were reconstructed from posted percentages and arm sizes, so small rounding differences are possible.

The registry record does not report the original sample-size justification or enough detail to establish whether the study was designed around the primary endpoint and comparisons now posted. The planning illustrations based on observed effects are not evidence of the trial’s original assumptions. Statistical-analysis details are also incomplete: the sponsor’s analyses are identified as logistic regression, but covariates and other model specifications are not reported.

Missing-data handling is not reported in the registry record. Although the primary population is defined as all randomized subjects, the available information does not establish how participants without a week 12 assessment were treated in the endpoint calculation. The record also does not report a multiplicity plan covering the primary comparisons and secondary outcomes. These omissions limit assessment of robustness and the interpretation of secondary findings.

The primary endpoint is a threshold response at week 12. It does not convey the full range of PASI changes, and the primary comparisons do not directly test the two active regimens against each other. The registry lists a 12 to 24 week follow-up, but the primary result alone does not establish longer-term response or durability.

The serious adverse-event counts are reported for safety-set groups, while the primary endpoint uses an intention-to-treat population. The record does not explain the relationship between those populations or give complete context for the listed serious-event terms. The trial is identified as phase 2, and its findings should be understood as evidence from this study rather than assumed to answer questions beyond its design and recorded outcomes.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Efficacy Study of CDP870 in Subjects With Chronic Plaque Psoriasis Who Are Candidate for Systemic Therapy and/or Phototherapy/Photochemotherapy — NCT00245765.
• Registry record last updated 2019-05-03; status last verified 2019-01.
• Results first posted 2019-05-03.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

23. Record Summary

NCT00245765 is a completed phase 2, randomized, quadruple-masked, parallel, placebo-controlled trial of subcutaneous certolizumab pegol in moderate-to-severe chronic plaque psoriasis. The registry lists enrollment of 176 and describes treatment for 12 weeks, with a 12 to 24 week follow-up.

The primary endpoint was PASI75 response at week 12 in the intention-to-treat population. Posted response percentages were 6.8% for placebo, 74.6% for certolizumab pegol 200 mg, and 82.8% for certolizumab pegol 400 mg. The sponsor reports logistic-regression odds ratios of 40.2 and 73.4 for the active regimens versus placebo, with p < 0.001 for both comparisons.

The registry record does not report the original sample-size justification, a complete multiplicity strategy, or detailed missing-data handling. The results describe the recorded week 12 endpoint and should be interpreted with those reporting limitations in mind.