Vascular Inflammation in Psoriasis Trial (The VIP Trial): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Vascular Inflammation in Psoriasis Trial (The VIP Trial) (NCT01553058), a randomized phase 4 study. The primary outcome is Change in Vascular Inflammation.

2. Clinical Question

The clinical question is framed around a measured imaging marker, not a clinical cardiovascular event. The study description says it also examined blood markers related to cholesterol, cholesterol efflux, metabolic factors, and inflammation. These are related risk-factor measures, but the primary endpoint reported in the registry record is the FDG-PET/CT measure of vascular inflammation.

The record identifies the study as randomized and triple masked, but it does not report which parties were masked or how masking was maintained. It calls the model factorial; the allocation of interventions within that model and the specific factorial contrasts are not reported in the registry record. The posted summaries present results for adalimumab and NB-UVB phototherapy against placebo injection. They do not establish what other comparisons, if any, were prespecified.

3. Trial Design

The Vascular Inflammation in Psoriasis Trial, also called the VIP Trial, is registered as a phase 4, randomized, triple-masked study with a factorial model. The registry record lists an enrollment of 97 and names the University of Pennsylvania as sponsor. The study started in 2012-07, reached primary completion on 2016-08-08, and is marked completed. These record details describe the study, but do not by themselves explain the rationale for its design.

The intervention groups were adalimumab (Humira), placebo injection, and NB-UVB phototherapy. The placebo is described as an injection in place of active Humira injection. The NB-UVB arm is described as phototherapy 3 times per week with no other intervention. The record does not provide additional details about treatment duration, adherence, co-interventions, allocation concealment, or the sequence of randomization.

The primary endpoint was change in vascular inflammation between baseline and week 12. Other listed outcomes included psoriasis activity, patient-reported quality of life, dietary assessment, physical activity, and adverse events. Numerical secondary results are posted for EQ-5D, DLQI, and MEDFICTS; the record does not report numerical results for every outcome in its secondary-outcome list.

Although the design is labeled factorial, the registry record does not explain the factors, their levels, or the planned factorial analysis. It also does not report the original sample-size justification, analysis populations, missing-data procedures, interim analyses, or a complete statistical analysis plan. Those omissions limit how fully the design and analysis choices can be reconstructed from 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.

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 Change in Vascular Inflammation, measured over Baseline - Week 12.

The primary endpoint is change in total vascular inflammation across five aortic segments from baseline to week 12, measured with FDG-PET/CT. The image-based measure is a tissue-to-background ratio (TBR): arterial FDG uptake is measured as the standardized uptake value (SUV) maximum divided by the venous SUV mean. The registry reports the endpoint as a mean change with standard deviation.

In general, FDG-PET/CT measures uptake of a labeled glucose analogue in tissue. In this study, the imaging measure was used to quantify arterial uptake as a marker of vascular inflammation. A ratio of arterial to venous uptake provides the stated TBR measure. This is an imaging biomarker rather than a direct count of cardiovascular events, and the posted result should be read as a change in that biomarker over the defined interval.

The arm means are all negative: -0.067 for adalimumab, -0.052 for placebo injection, and -0.079 for NB-UVB phototherapy. A negative change indicates a lower measured TBR at follow-up than at baseline, according to the endpoint's change definition. These within-arm changes do not, by themselves, answer whether one group changed differently from another. For that question, the relevant quantities are between-group contrasts and their uncertainty.

The registry does not report a threshold for a clinically meaningful TBR change or evidence linking a change of a particular size to a clinical outcome. The endpoint therefore supports interpretation of the measured imaging result, but not an inference about the size of any clinical benefit or harm.

7. Results Posted in the Registry

• Adalimumab (Humira): mean -0.07 versus -0.05 on control; difference -0.02 (95% CI -0.10 to 0.07), standardized effect d = -0.09; z-test p = 0.722.
• NB-UVB Phototherapy: mean -0.08 versus -0.05 on control; difference -0.03 (95% CI -0.07 to 0.01), standardized effect d = -0.34; z-test p = 0.186.

8. Secondary Efficacy Endpoints

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

Change in Patient-reported Outcomes-EuroQol EQ-5D

• 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:
  • Adalimumab (Humira): mean 0.07 versus 0.00 on control; difference 0.07 (95% CI -0.01 to 0.15), standardized effect d = 0.45; z-test p = 0.073.
  • NB-UVB Phototherapy: mean 0.16 versus 0.00 on control; difference 0.16 (95% CI 0.07 to 0.25), standardized effect d = 0.89; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Adalimumab (Humira) and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for NB-UVB Phototherapy than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change in Patient-reported Outcomes-Dermatology Life Quality Index (DLQI)

• 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:
  • Adalimumab (Humira): mean -7.91 versus -3.73 on control; difference -4.18 (95% CI -8.29 to -0.07), standardized effect d = -0.50; z-test p = 0.046.
  • NB-UVB Phototherapy: mean -9.27 versus -3.73 on control; difference -5.54 (95% CI -8.78 to -2.30), standardized effect d = -0.85; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Adalimumab (Humira) 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 mean is statistically lower for NB-UVB Phototherapy than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change in Patient-reported Outcomes-MEDFICTS Dietary Assessment)

• 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:
  • Adalimumab (Humira): mean -10.17 versus -13.66 on control; difference 3.49 (95% CI -8.21 to 15.19), standardized effect d = 0.15; z-test p = 0.559.
  • NB-UVB Phototherapy: mean -16.29 versus -13.66 on control; difference -2.63 (95% CI -14.97 to 9.71), standardized effect d = -0.11; z-test p = 0.676.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Adalimumab (Humira) and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between NB-UVB Phototherapy and the control. The interval gives the range of effects that remain compatible with the data.

The posted secondary results cover patient-reported health status, dermatology-related quality of life, and dietary assessment. The pattern is not uniform across these outcomes or across the treatment comparisons. This adds descriptive context to the primary imaging result, but does not change what the primary endpoint measures or resolve its uncertainty.

Secondary outcomes can help describe broader dimensions of a trial, including outcomes experienced or reported by participants. However, results on these measures do not automatically corroborate a change in vascular inflammation: they measure different constructs, use different scales, and can respond differently. A result on one secondary measure should therefore be interpreted as evidence about that measure, not as a direct confirmation of the primary endpoint.

The registry lists additional secondary outcomes, including psoriasis activity, physical activity, and adverse events, but numerical results for all listed outcomes are not reported in the registry record. It also reports 18 outcome measures and 24 analyses, while the available secondary numerical summaries cover only selected measures. The record does not explain how those outcomes and analyses were prioritized or how the secondary comparisons were planned.

In general, testing many outcomes or comparisons increases the chance that some results may appear notable through random variation. Adjustment for multiplicity, a prespecified hierarchy, or another strategy can help guide interpretation, but the strategy used in this trial is not reported in the registry record. The recalculated secondary p-values are unadjusted. They should therefore carry less weight than a clearly prespecified primary analysis, especially when the broader analysis plan and multiplicity approach are unavailable.

The overall secondary pattern is best treated as exploratory context. It can motivate questions about consistency across outcome domains, but it cannot by itself establish an overall treatment effect or determine which result should take precedence.

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

• Change in Psoriasis Activity (PASI-75 and PGA)
• Change in Patient-reported Outcomes-EuroQol EQ-5D
• Change in Patient-reported Outcomes-Dermatology Life Quality Index (DLQI)
• Change in Patient-reported Outcomes-MEDFICTS Dietary Assessment)
• Change in Patient-reported Outcomes-International Physical Activity Questionnaire (IPAQ)
• Number of Patients With Adverse Events.

9. Statistical Interpretation

10. Statistical Methods Explained

The primary endpoint is continuous: it is a numerical measure of change in TBR. The posted group summaries report a mean and standard deviation for each arm. A mean describes the average observed change; a standard deviation describes the spread of individual observations around that average. Neither summary alone tells how precisely the mean or a between-group contrast has been estimated.

What does the between-group estimate represent?

A mean difference compares the average change in one group with the average change in the placebo group. The recalculated estimate for adalimumab versus placebo is -0.015, and the estimate for NB-UVB versus placebo is -0.027. A negative estimate means the average change in the named treatment group was more negative than the placebo-group change, on the posted endpoint scale. This direction is not itself evidence of a meaningful treatment effect; uncertainty and the endpoint's clinical interpretation matter as well.

The recalculated comparisons are described as unadjusted. They use the posted group means and standard deviations to construct a simple comparison and are not the same as the sponsor's reported linear-regression analyses. In general, regression can account for specified covariates or use other model details, but which covariates and specifications were used in the sponsor analyses is not reported in the registry record. It would therefore be inappropriate to infer an adjustment strategy from the method label alone.

How should a p-value be understood?

In general, a p-value describes how compatible the observed data are with a specified null model, under the assumptions of the statistical test. A larger p-value is not proof that groups are identical, and a smaller p-value does not measure the size or importance of a difference. Interpretation should consider the estimate, confidence interval, design, and analysis plan, rather than treating a p-value as a stand-alone verdict. The recalculated primary comparisons have p-values of 0.722 and 0.186. The registry's sponsor-reported regression p-values are 0.795 and 0.647 for the corresponding comparisons.

Why does variability matter?

In general, greater variation among observations makes a group mean less precise when other features of the study are unchanged. The primary endpoint's posted standard deviations are 0.213 for adalimumab, 0.112 for placebo injection, and 0.02 for NB-UVB phototherapy. The spread differs across arms, so uncertainty in the mean differences depends on both the estimated contrast and the variability in the groups. The recalculation uses the reported standard deviations; it does not establish that the observations follow a particular distribution or that the equal-variance assumptions of a simple comparison are appropriate.

The registry labels the study factorial, but does not report the factorial structure or model. The primary analysis population, handling of missing observations, and any covariate adjustment are also not reported in the registry record. These omissions make it difficult to assess whether the simple recalculation matches the prespecified analysis or how the sponsor's regression was specified.

What can the posted analysis establish?

The posted group means and standard deviations support descriptive summaries and simple unadjusted comparisons. The sponsor analyses supply p-values from linear regression, but not the regression estimates or confidence intervals. Without a full analysis plan and details on missing data, model assumptions, and population definitions, neither source completely describes the analysis process. The recalculation is consequently best read as a transparent comparison based on the summary statistics, not as a replacement for the sponsor's model-based analysis.

In general, statistical analysis is strongest when the primary outcome, contrast, model, and handling of missing data are specified in advance and reported in enough detail to reproduce the reasoning. The registry record does not provide those details. This matters when interpreting a study with multiple outcomes and a factorial label, because the number and form of planned comparisons can affect how results should be evaluated.

11. Confidence Intervals and Precision

Confidence intervals express the range of values compatible with the estimate under the model and assumptions used to construct the interval. In general, a narrower interval indicates greater precision, while a wider interval reflects more uncertainty. An interval that includes zero does not establish that the true difference is zero; it indicates that zero is among the values compatible with the data and method.

For the recalculated primary comparisons, the interval for adalimumab versus placebo spans zero, as does the interval for NB-UVB versus placebo. The estimates are -0.015 and -0.027, respectively. Thus, the posted summaries do not pin down a single direction of between-group difference with high precision. They allow for a range of possible effects on either side of no difference.

The sponsor's registry results give p-values but no regression estimates or confidence intervals. As a result, the precision of the sponsor's own model-based contrasts cannot be assessed from the reported regression results alone. The recalculated intervals describe the simple unadjusted comparisons, not necessarily the sponsor's intended analysis.

In general, precision depends on the amount of information in the data and the variability of the endpoint, among other design and model features. The registry record does not report the original precision target or a clinically meaningful TBR difference. Consequently, it is not possible to say from these results whether the study was designed to estimate a particular clinically relevant effect with a specified level of precision. The intervals are useful for showing uncertainty, but do not resolve the endpoint's clinical significance.

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 expressed as participants per arm. They are not total event counts. The planning calculation assumes a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. It uses the observed effect as its starting point and considers detecting the stated fraction of that effect. The original design assumptions for the trial are not reported in the registry record.

The 80% power column gives the illustrative number of participants per arm for a design with an 80% chance of detecting the specified effect, if the planning assumptions and effect are correct. The 90% power column gives the corresponding per-arm number for a 90% chance. These are prospective planning quantities, not descriptions of the probability that the completed trial found an effect.

The rows that plan for 100% of the observed effect use the full observed contrast as the target. The rows for 75% and 50% of the observed effect plan for smaller contrasts. Smaller effects are harder to distinguish from random variation, so they require more participants under otherwise unchanged assumptions. This pattern is visible in the planning figures for the primary comparisons.

These calculations are based on the observed effect, which can be uncertain and may not represent the effect a future study should target. They do not account for details that are not stated in the planning assumptions, such as loss to follow-up or a different analysis model. This is not observed power: it is a planning illustration, not a retrospective measure of whether the completed study was adequately powered.

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 = -0.015; pooled standard deviation σ = 0.172.
2. n = 2 × (1.96 + 0.842)² × 0.172² / -0.015² = 2,057.2, rounded up to 2,058 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 <- -0.015                      # observed difference in means
sigma <- 0.171714692102543                     # 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(1553058)
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 = 2,058 (80% power), 2,754 (90% power)
 75% of observed effect: n per arm = 3,658 (80% power), 4,896 (90% power)
 50% of observed effect: n per arm = 8,229 (80% power), 11,016 (90% power)
power.t.test: 2058.1 
Simulated power at n = 2,058 per arm: 0.802 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Analyses Reported by the Sponsor

The registry record reports two sponsor analyses using linear regression: adalimumab versus placebo injection has p = 0.795, and NB-UVB phototherapy versus placebo injection has p = 0.647. These are the sponsor-reported results available for the primary endpoint. The record does not provide regression effect estimates, confidence intervals, model covariates, or additional details needed to reconstruct those analyses.

The recalculated comparisons use the posted means and standard deviations and are simple unadjusted calculations. They give mean differences of -0.015 for adalimumab versus placebo and -0.027 for NB-UVB versus placebo, with p-values of 0.722 and 0.186. The difference between these p-values and the sponsor-reported p-values cannot be resolved from the registry record. The analyses may differ in their model or assumptions, but the specific explanation is not reported.

The recalculation is useful as a transparent check on the posted summaries, but it should not be treated as a substitute for a prespecified sponsor analysis. Because the registry does not supply enough information to reproduce the regression, the sponsor's p-values and the unadjusted recalculation should be kept distinct rather than combined into a single result.

15. Multiplicity, Missing Data and Analysis Populations

The registry record includes a primary endpoint and multiple secondary outcomes. It also reports 18 outcome measures and 24 analyses. This creates a multiplicity issue: in general, when many outcomes or comparisons are examined, the chance of obtaining at least one apparently notable result by chance can increase. The size of that concern depends on which tests were planned, how they relate to one another, and whether any adjustment or hierarchy was prespecified.

The record does not report a multiplicity adjustment, a hierarchy for testing outcomes, or which secondary comparisons were designated confirmatory versus exploratory. The recalculated secondary p-values are unadjusted. They should not be read as if a family-wide error rate had been controlled. The sponsor's statistical approach to multiplicity is not reported in the registry record.

Missing-data procedures are also not reported. The registry record does not describe how missing primary or secondary measurements were handled, whether any observations were excluded from an analysis, or whether sensitivity analyses assessed the impact of missingness. The group summaries list outcome-specific sample sizes, but those summaries do not explain why data may be unavailable or how missing observations affect the analysis.

The analysis population is not reported in enough detail to establish whether results are based on all randomized participants, participants who received treatment, participants with available endpoint data, or another defined group. The record also does not explain whether the primary analysis followed an intention-to-treat principle.

These details matter because the interpretation of estimated effects and p-values depends on the analysis population, missing-data assumptions, and the set of tests being considered. Without them, the registry results can be described, but the complete confirmatory status and robustness of the analyses cannot be assessed.

16. 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 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: vasovagal syncope (6.1%).

The registry reports serious adverse events for the adalimumab, placebo-injection, and NB-UVB groups as 2, 0, and 0, respectively. It separately reports other adverse events as 7, 15, and 33. These are counts in the listed groups, not adjusted comparisons of risk. The registry does not report deaths for these groups; the death entries are not populated, so deaths are not reported in the registry record.

The record names vasovagal syncope as a serious adverse-event term at 6.1%, but does not provide enough context in the listed result to attribute that percentage to a particular group or determine its denominator. The aggregate serious-event counts do not show the types, timing, severity details, or relatedness for every event.

In general, safety counts from a trial are descriptive, and comparisons can be uncertain when event numbers are limited. The registry record does not provide a formal statistical comparison of serious adverse events or a detailed account of how events were classified. These counts should therefore be read as the reported observations, not as definitive evidence that risks were equal or different.

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

The primary result describes changes in an imaging measure of vascular inflammation over Baseline - Week 12. The group means were negative, and the recalculated between-group estimates were small relative to the uncertainty shown by their confidence intervals, which span zero. The sponsor's reported regression tests also do not provide evidence of a clear group separation in the registry results. These findings describe the posted data and do not establish that a treatment does or does not work.

The endpoint is a biomarker measured by FDG-PET/CT, not a clinical cardiovascular outcome. The registry record does not report a clinically meaningful threshold for the TBR change or a link between a particular change and later cardiovascular events. It is therefore not possible to translate the observed changes into a claim about cardiovascular benefit, harm, or prevention.

Likewise, within-group changes should not be interpreted as treatment effects in isolation. A treatment effect is assessed through a between-group comparison, and the relevant comparison remains uncertain. The interval estimates and the absence of detailed sponsor model results limit how precisely the size and direction of any difference can be stated.

The secondary outcomes address different domains and are subject to uncertainty, incomplete reporting, and unreported multiplicity procedures. Safety counts are also descriptive. Together, these sources may help characterize what the study measured, but they do not provide a complete basis for broad conclusions across inflammation, psoriasis symptoms, quality of life, cardiovascular outcomes, and safety.

The registry record is most informative when interpreted narrowly: it reports an imaging endpoint, selected patient-reported measures, adverse-event counts, and sponsor regression p-values. It does not report enough information to answer every question about the analysis plan, missing data, clinical importance, or longer-term outcomes.

18. Why This Trial Matters Statistically

This trial illustrates the distinction between a within-group change and a comparative treatment effect. All primary endpoint group means are negative, but the key question is whether change differed between a treatment group and placebo. The recalculated contrasts and their uncertainty make that distinction visible: a direction in each arm does not by itself establish a between-group difference.

It also illustrates why an imaging biomarker should not be conflated with a clinical outcome. FDG-PET/CT provides a measure of vascular inflammation in the stated aortic segments. The registry does not show that a change in this measure translates into a change in cardiovascular events, nor does it provide a threshold for clinical importance. Statistical interpretation must stay aligned with what the endpoint measures.

The record offers a useful comparison between sponsor-reported regression tests and simple unadjusted recalculations from summary statistics. The difference between these analyses highlights the value of reporting model estimates, intervals, covariates, and analysis populations—not just p-values. Without those details, readers can describe each result but cannot fully reconcile them.

Finally, the study has multiple outcomes and analyses, while multiplicity and missing-data methods are not reported. This is a practical reminder that isolated secondary findings deserve cautious interpretation and that a registry record may provide results without the complete information needed to evaluate the full statistical plan.

19. Limitations

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

The registry record does not describe the factorial structure beyond labeling the model factorial. It does not explain how interventions were allocated within that structure, which contrasts were prespecified, or how those contrasts were analyzed. The meaning of triple masking and the parties who were masked are also not reported.

The primary-endpoint summaries do not include sponsor regression estimates or confidence intervals. The registry gives regression p-values but not enough model detail to reproduce or reconcile them with the unadjusted calculations. The original statistical analysis plan, sample-size justification, and any interim analyses are not reported in the registry record.

The analysis population and missing-data procedures are not stated. The record does not explain whether all randomized participants were included in each analysis, why outcome-specific sample sizes vary, or whether sensitivity analyses were conducted. These gaps limit assessment of potential bias from unavailable measurements or analysis exclusions.

The posted results focus on change through week 12 for the primary endpoint and selected patient-reported measures. A longer-term primary outcome or a clinical cardiovascular event result is not reported in the registry record. The record also does not state a clinically meaningful threshold for TBR, so the practical importance of the observed contrast cannot be determined from the endpoint summaries alone.

Multiple outcomes and analyses are reported, but a strategy for multiplicity is not stated. Numerical secondary results are available for selected measures rather than every outcome listed. Safety reporting gives group counts, but does not provide a full event-level description or formal comparative analysis. These limitations should shape interpretation of both positive-looking and null-looking results.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Vascular Inflammation in Psoriasis Trial (The VIP Trial) — NCT01553058.
• Registry record last updated 2018-05-22; status last verified 2018-04.
• Results first posted 2018-05-22.
• 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.

23. Record Summary

The VIP Trial is registered as a completed, phase 4, randomized, triple-masked study with a factorial model. It compared adalimumab, placebo injection, and NB-UVB phototherapy in people with moderate to severe psoriasis. The primary endpoint was change in FDG-PET/CT vascular inflammation, measured as TBR from baseline to week 12.

The posted primary summaries show negative mean changes in all groups. Recalculated unadjusted comparisons with placebo have confidence intervals that span zero. Sponsor-reported linear-regression p-values are also available, but model estimates and details are not reported in the registry record. Selected secondary results and adverse-event counts are posted; the multiplicity strategy, missing-data procedures, analysis populations, and original sample-size justification are not reported.