An Efficacy and Safety Study of Sirukumab in Participants With Major Depressive Disorder: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for An Efficacy and Safety Study of Sirukumab in Participants With Major Depressive Disorder (NCT02473289), a randomized phase 2 study. The primary outcome is Change From Baseline in Hamilton Depression Rating Scale (HDRS-17) Total Score at Week 12.

2. Clinical Question

3. Trial Design

This was a Phase 2, randomized, double-blind, parallel-group study comparing sirukumab with placebo as an addition to a monoaminergic antidepressant in adults with major depressive disorder. The registry reports enrollment of 193. The study is marked completed; its recorded start was 2015-07-23 and its primary completion was 2018-05-22.

The treatment period for the primary comparison was 12 weeks. Sirukumab 50 mg or matching placebo was administered by subcutaneous injection on Day 1, Day 28, and Day 56. Both groups continued adjunctive treatment alongside antidepressant therapy. The record describes participants as having a suboptimal response to their current standard oral antidepressant therapy.

The primary analysis population was narrower than the overall study population. It comprised randomized participants with hsCRP at least 3.00 mg/L at both screening and baseline who received at least one dose and had baseline and at least one postbaseline HDRS-17 score. A cohort with hsCRP below 0.300 mg/dL was also enrolled to support understanding of the relationship between CRP and clinical changes. The primary results reported in this record concern the high-hsCRP analysis set, not an overall estimate across both hsCRP cohorts.

The registry lists changes in HDRS-17, CGI-S, PHQ-9, SHAPS, and FACIT-Fatigue, as well as HDRS-17 response and remission, among the outcomes. Several measures were scheduled at additional follow-up times. Details of the randomization sequence, concealment procedures, treatment adherence, and the original sample-size justification 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.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Modified Intent-to-treat 1 (mITT1) analysis set: all randomized participants with high sensitivity c-reactive protein (hsCRP) \>= 3.00 milligram per liter (mg/L) at screening and baseline who receive at least 1 dose of study drug and have both baseline and at least one postbaseline HDRS-17 total score in double-blind (DB) treatment period.

5. Baseline Characteristics

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

6. Primary Endpoint

The registry lists the primary outcome as Change From Baseline in Hamilton Depression Rating Scale (HDRS-17) Total Score at Week 12, measured over Baseline and Week 12.

The primary endpoint was change from baseline in the Hamilton Depression Rating Scale, 17-item version (HDRS-17), total score at Week 12. The scale is administered by a clinician to assess depression symptom severity. Its total score ranges from 0 to 52, and higher scores indicate a more severe condition. The total is formed by adding ratings across the 17 items, each of which uses a rating scale with either three or five points.

Change from baseline expresses how the score at follow-up differs from the participant’s starting score. A negative change indicates a lower symptom score than at baseline; because higher HDRS-17 scores indicate greater severity, a decline in score represents improvement on this measure. The endpoint therefore captures average change in clinician-rated symptoms over the treatment period, rather than the proportion of participants who crossed a response or remission threshold.

This kind of continuous endpoint retains information about the magnitude of score changes across participants. A group mean can, however, conceal variation in individual changes and does not by itself describe how many participants met a clinically defined response or remission criterion. The registry record does not report the threshold definitions for the secondary response and remission outcomes.

7. Results Posted in the Registry

• Sirukumab 50 mg: mean -11.40 versus -10.60 on control; difference -0.80 (95% CI -4.89 to 3.29), standardized effect d = -0.08; z-test p = 0.701.

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.

Percentage of Participants With Remission as Assessed by HDRS-17 Total Score 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:
  • Sirukumab 50 mg: 15.9% (7/44) versus 19.0% (8/42) on control; risk difference -3.1 percentage points (95% CI -19.2 to 12.9), risk ratio 0.84 (0.33–2.10); unadjusted two-proportion z-test p = 0.701.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Sirukumab 50 mg and the control. The interval gives the range of effects that remain compatible with the data.

Percentage of Participants With Response as Assessed by HDRS-17 Total Score 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:
  • Sirukumab 50 mg: 34.1% (15/44) versus 33.3% (14/42) on control; risk difference 0.8 percentage points (95% CI -19.2 to 20.7), risk ratio 1.02 (0.57–1.85); unadjusted two-proportion z-test p = 0.941.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Sirukumab 50 mg and the control. The interval gives the range of effects that remain compatible with the data.

The posted secondary outcomes include HDRS-17 response and remission at Week 12 and changes in symptom, global-severity, pleasure, and fatigue measures at scheduled follow-up visits. The two secondary binary outcomes with posted group results have broadly similar proportions between treatment groups. Their unadjusted comparisons do not indicate a clear separation. The registry record does not provide posted results for every listed secondary measure in the registry record for this analysis.

This overall pattern does not contradict the primary result: both the primary estimate and the available secondary comparisons leave substantial uncertainty about the treatment contrast. Secondary outcomes can add context because they look at different summaries or aspects of participants’ experiences, but they do not replace the prespecified primary endpoint. Response and remission also classify participants according to thresholds, whereas the primary endpoint compares mean change in a continuous score.

Unadjusted secondary results carry less weight because multiple endpoints and time points create multiple opportunities for apparently notable findings. Without a reported multiplicity strategy, p-values from separate secondary comparisons should not be interpreted as if each were the only analysis performed. The registry record does not report whether a hierarchy, family-wise error control, or another multiplicity procedure was prespecified. The secondary findings are therefore best treated as descriptive and supportive rather than as independent confirmatory evidence.

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

• Change From Baseline in HDRS-17 Total Score at Weeks 1, 4 and 8
• Percentage of Participants With Remission as Assessed by HDRS-17 Total Score at Week 12
• Percentage of Participants With Response as Assessed by HDRS-17 Total Score at Week 12
• Change From Baseline in Clinical Global Impression - Severity (CGI-S) Total Score at Weeks 1, 4, 8, 12, 16, and 22
• Change From Baseline in Patient Health Questionnaire (PHQ-9) Total Score at Weeks 1, 4, 8, 12, 16, and 22
• Change From Baseline in Snaith Hamilton Pleasure Scale (SHAPS) Total Score (Definition 1) at Weeks 1, 4, 8, 12, 16, and 22
• Change From Baseline in Snaith Hamilton Pleasure Scale (SHAPS) Total Score (Definition 2) at Weeks 1, 4, 8, 12, 16, and 22
• Change From Baseline in Functional Assessment of Chronic Illness Therapy (FACIT)-Fatigue Total Score at Weeks 1, 4, 8, 12, 16, and 22

9. Statistical Interpretation

10. Statistical Methods Explained

The sponsor’s primary analysis used a mixed model for repeated measures (MMRM) and reported a difference in least-squares means. In general, a repeated-measures model analyzes outcome observations collected at multiple visits while accounting for the fact that observations from the same participant are related. This can use the pattern of observed scores across visits rather than treating each visit as an unrelated analysis. The registry record does not report the model’s covariance structure, fixed effects, adjustment variables, or detailed handling of missing observations.

What does a least-squares mean represent?

In general, a least-squares mean is a model-based group mean, estimated while accounting for the terms included in the statistical model. It can differ from a raw arithmetic mean if the model adjusts for other variables or uses information across repeated visits. The reported difference of least-squares means is the treatment-group contrast from that model. The record reports the contrast as -0.8 HDRS-17 units, but it does not provide enough detail to reconstruct the model specification.

How should the unadjusted recalculation be understood?

The recalculated comparison uses the posted group means and standard errors to estimate a simple, unadjusted difference. It is useful as a transparent check on the direction and rough scale of the posted contrast. It does not reproduce the sponsor’s repeated-measures analysis and should not be treated as a replacement for it. The recalculated estimate is -0.8, with an interval from -4.89 to 3.29 and p = 0.701. The sponsor’s model-based result remains the primary reported analysis; the recalculation supplies a different, less model-dependent summary of the posted data.

The posted group summaries give standard errors of 1.43 for placebo and 1.52 for sirukumab. A standard error describes the uncertainty of an estimated mean, not the spread of individual participant scores. The recalculated pooled standard deviation is 9.693 and the standardized difference is -0.083. These are derived from the posted summary statistics and are not sponsor-reported model estimates.

What does a p-value say?

In general, a p-value measures how incompatible the observed data are with a specified null hypothesis, under the assumptions of the analysis. It is not the probability that the null hypothesis is true, nor the probability that the result arose “by chance.” The sponsor’s p-value of 0.310 and the unadjusted recalculated p-value of 0.701 come from different analyses. Neither value describes the size of the effect or its clinical importance; the estimate and its interval are needed to understand those aspects.

Why does over-dispersion matter for binary outcomes?

For binary endpoints such as response or remission, an analysis commonly compares proportions. In general, the uncertainty of a proportion depends on the number of participants and the event frequency. Over-dispersion means that observed variability exceeds what a simple binomial model would predict. When present, treating observations as less variable than they are can make standard errors too small and intervals too narrow. The registry record does not describe an over-dispersion adjustment for the posted secondary comparisons, so no such adjustment should be assumed.

The posted recalculations for binary outcomes are unadjusted comparisons. They do not account for the repeated assessment structure of other outcomes, nor do they incorporate a correction for the number of outcomes examined. The sponsor’s primary MMRM result and these secondary recalculations answer different statistical questions and should be interpreted separately.

The original statistical analysis plan, including model diagnostics, prespecified covariates, missing-data assumptions, and any planned sensitivity analyses, is not reported in the registry record. Therefore, details beyond the named MMRM method and reported model contrast cannot be verified from this record.

11. Confidence Intervals and Precision

The sponsor’s reported primary contrast is -0.8 HDRS-17 units. Its 75% confidence interval runs from -2.77 to 1.10. A confidence interval describes the range of estimates reasonably compatible with the data and the analysis procedure, under that procedure’s assumptions. The interval includes zero and extends to values on both sides of zero, so the result does not pin down the direction of the group difference with high precision.

The reported interval is a 75% interval, not a 95% interval. Its confidence level matters when comparing intervals or interpreting their coverage. The registry record does not report a different confidence level for the sponsor’s primary interval. The interval is based on the sponsor’s MMRM analysis, while the unadjusted recalculation gives a separate interval from -4.89 to 3.29. The two intervals differ because the analyses use different methods and uncertainty estimates.

Precision is distinct from statistical significance and from clinical importance. A narrow interval would indicate greater precision about the estimated contrast; it would not by itself establish that the effect is important. Conversely, an interval that includes zero does not prove that the groups are equivalent. No equivalence margin or noninferiority margin is reported in the registry record, and the interval does not establish that all meaningful effects are ruled out.

The primary estimate pertains to the mITT1 high-hsCRP analysis population. Its precision should not be generalized to participants outside that population. The record does not report precision estimates for the lower-hsCRP cohort’s primary comparison.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning figures are illustrative sample sizes based on the observed effect, not the study’s original design. For continuous outcomes such as the primary HDRS-17 comparison, the figures are participants per arm, not a total across arms and not total events. The 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. These planning assumptions are known; the trial’s own original design assumptions and sample-size justification are not reported in the registry record.

The 80% power column gives the estimated participants per arm for a hypothetical study to have an 80% chance of detecting the specified effect if that effect were the true one, under the planning assumptions. The 90% power column describes the corresponding planning target at 90% power. These are design calculations, not estimates of the probability that the completed study detected an effect.

The rows planning for 100%, 75%, and 50% of the observed effect show how the required enrollment changes when the target effect is made smaller. Smaller effects need more participants to distinguish them from random variation with the same planned power and significance level. In this study, the planning illustrations based on the primary observed effect require large per-arm sample sizes, particularly when targeting a fraction of that effect.

These figures are not observed power. Observed power calculated after a study would mainly re-express the observed estimate and its uncertainty, rather than supply new evidence about the result. The planning calculations are best read as conditional illustrations of what a future design might require under the stated assumptions, not as a judgment that the completed trial was adequately or inadequately designed.

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 = -0.800; pooled standard deviation σ = 9.693.
2. n = 2 × (1.96 + 0.842)² × 9.693² / -0.800² = 2,304.6, rounded up to 2,305 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 <- -0.800000000000001                      # observed difference in means
sigma <- 9.69326877393841                     # 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(2473289)
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 = 2,305 (80% power), 3,086 (90% power)
 75% of observed effect: n per arm = 4,098 (80% power), 5,485 (90% power)
 50% of observed effect: n per arm = 9,219 (80% power), 12,341 (90% power)
power.t.test: 2305.6 
Simulated power at n = 2,305 per arm: 0.795 (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 sponsor’s own primary analysis is the MMRM comparison of least-squares means: -0.8 HDRS-17 units, with a 75% confidence interval from -2.77 to 1.10 and p = 0.310. It is the registry’s reported inferential analysis for the primary endpoint. The record does not flag a discrepancy between the sponsor’s result and the recalculated point estimate.

The simple recalculation also estimates a mean difference of -0.8, but its interval is -4.89 to 3.29 and its unadjusted p-value is 0.701. It is based on posted summary statistics and does not reproduce the repeated-measures model. Agreement in the point estimate does not make the analyses identical: they differ in method and in the reported uncertainty.

The sponsor’s result should therefore be read as the primary model-based analysis, and the recalculation as a supplementary unadjusted check. The registry does not give enough model detail to reproduce the sponsor’s estimates independently. The reported 75% confidence level should also be kept in view when interpreting its interval.

15. Multiplicity, Missing Data and Analysis Populations

The record lists one primary outcome and several secondary measures, including assessments at multiple follow-up times. Examining multiple outcomes and time points raises a multiplicity issue: the chance of at least one apparently unusual result can increase as more comparisons are made. A prespecified strategy can address this, for example by defining an order for testing or adjusting the criterion for inference. The registry record does not report whether such a strategy was planned or used.

The posted secondary remission and response comparisons are unadjusted. Their p-values should not be treated as confirmatory evidence without knowing how the full set of planned analyses was handled. The record also does not report a multiplicity adjustment for the primary result, nor does it describe any hierarchy among secondary outcomes. This absence of detail does not establish that no strategy was used; it means that the strategy is not reported in the registry record.

The primary population is described as the mITT1 set, requiring randomization, high hsCRP at screening and baseline, at least one dose, and baseline plus at least one postbaseline HDRS-17 score. The number analyzed by treatment arm is reported for this endpoint, but the record’s description does not provide a full account of every participant excluded from the analysis or the reasons for exclusion.

Missing-data handling is particularly relevant in a repeated-measures analysis. An MMRM can use available repeated observations, but its validity depends on assumptions about the relationship between missingness and observed or unobserved outcomes. The model specification and missing-data assumptions are not reported in the registry record. The record also does not report sensitivity analyses designed to test whether conclusions change under alternative assumptions about missing outcomes.

These reporting gaps limit assessment of how robust the primary and secondary inferences are to analytic choices. They do not, by themselves, show that the analyses were inappropriate; they identify details that cannot be evaluated from the registry record.

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: acute myocardial infarction (1.1%), cellulitis (1.1%), depression suicidal (1.1%), transaminases increased (1.0%), suicide attempt (1.0%).

For serious adverse events, the registry reports 2 affected participants among 99 at risk in the placebo group and 3 among 94 at risk in the sirukumab group. Deaths were 0 in each group. These counts describe participants with at least one serious adverse event as recorded in the registry; they do not indicate the total number of serious events, event duration, or severity beyond the serious classification.

For other adverse events, the record reports 13 affected participants among 99 at risk with placebo and 19 among 94 at risk with sirukumab. These figures should be read as group-level safety summaries, not as proof that a treatment caused or prevented an event. The registry lists Acute Myocardial Infarction, Cellulitis, Depression Suicidal, Transaminases Increased, and Suicide Attempt among the serious adverse event terms, with the listed percentages ranging from 1.0% to 1.1%. The record does not connect these listed terms to a specific treatment group in the information.

Adverse-event counts alone do not establish comparative safety. Interpretation also depends on event definitions, ascertainment, exposure, follow-up, and the clinical context. Further details on those aspects are not reported in the registry record.

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

The primary result is an estimate of the difference between groups in average change in clinician-rated depressive symptoms at Week 12 among participants in the high-hsCRP mITT1 analysis set. The estimate favors a slightly larger decline in the sirukumab group in the observed means, but the sponsor’s reported interval includes zero and the reported p-value is 0.310. The data therefore do not provide a precise estimate of the direction or size of the treatment contrast.

This is not the same as demonstrating equivalence or proving that there is no effect. The registry record does not report an equivalence or noninferiority design, or a margin defining effects small enough to be considered unimportant. The interval remains compatible with differences in either direction. Nor does a p-value above a conventional threshold show that the null hypothesis is true.

The result is specific to the endpoint, follow-up, and analysis population used. It does not by itself establish the effect among participants with lower hsCRP, in other populations, or over longer follow-up. The record also does not report a treatment-by-hsCRP interaction, so the separate cohort cannot be used from these registry entries to conclude that hsCRP predicts a different treatment response.

Secondary response and remission outcomes offer a different view of symptom change, but their unadjusted results should be interpreted cautiously in light of the multiple outcomes and time points. Safety counts describe reported events in the study groups and do not establish causation. Overall, the registry results support a cautious reading: the estimated primary contrast is small in the posted summary, but its uncertainty and the limits of registry reporting prevent a definitive conclusion about a treatment effect.

18. Why This Trial Matters Statistically

This trial illustrates why the estimated treatment contrast matters more than looking at change within each group alone. Average HDRS-17 scores declined in both groups, but the randomized comparison asks whether the changes differ between groups. Improvement from baseline in both arms is not, by itself, evidence of a difference attributable to the assigned adjunctive treatment.

It also highlights the distinction between a model-based analysis and a simple recalculation. The sponsor used an MMRM and reported a least-squares mean contrast, while the unadjusted recalculation used summary statistics. Their point estimates agree, but their uncertainty summaries differ. Reading the methods alongside the estimate helps avoid treating a recalculation as though it reproduced the sponsor’s analysis.

The confidence interval is important because a single point estimate can make an uncertain result appear more definite than it is. Here the sponsor’s 75% interval includes zero. The interval’s confidence level and model basis should be considered when judging the precision of the result.

The study also emphasizes the importance of specifying the analysis population. The primary result concerns participants meeting the high-hsCRP criteria and other mITT1 requirements, while a lower-hsCRP cohort was also enrolled. Without a reported interaction analysis, results from the primary population should not be interpreted as establishing how hsCRP relates to treatment effect.

Finally, multiple secondary endpoints create a need for clear multiplicity and missing-data reporting. These details help readers assess how much weight to place on secondary findings and how sensitive conclusions may be to analysis choices.

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 report the full MMRM specification, including its covariance structure, adjustment variables, or detailed handling of missing observations. This limits independent evaluation of the sponsor’s model-based result and its assumptions. Sensitivity analyses for missing data are also not reported in the registry record.

The primary endpoint analysis is restricted to the high-hsCRP mITT1 population. The record describes an additional lower-hsCRP cohort, but a primary comparison for that cohort and an interaction analysis assessing whether the treatment contrast differs by hsCRP are not reported. The primary estimate should not be generalized to that cohort based on the information reported.

Multiplicity procedures for the multiple secondary outcomes and visits are not reported. The posted secondary comparisons are unadjusted, which limits their value as confirmatory evidence. The registry also does not report the definitions used for response and remission in the available outcome details.

The original sample-size justification and design assumptions are not reported in the registry record. The planning illustrations are based on the observed effect and stated hypothetical assumptions, so they cannot establish whether the original design had a particular planned power. The record does not provide enough information to assess adherence, treatment exposure, or the full reasons participants may not have contributed to the primary analysis.

These limitations concern what can be evaluated from the registry record. They should not be taken as evidence that unreported procedures were not performed.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: An Efficacy and Safety Study of Sirukumab in Participants With Major Depressive Disorder — NCT02473289.
• Registry record last updated 2025-04-29; status last verified 2025-04.
• Results first posted 2019-06-11.
• 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 registry describes a completed Phase 2 randomized, double-blind, parallel-group study of sirukumab 50 mg versus matching placebo as adjunctive treatment to a monoaminergic antidepressant in adults with major depressive disorder. Overall enrollment was 193.

The primary endpoint was change from baseline in HDRS-17 total score at Week 12 in the high-hsCRP mITT1 analysis set. The sponsor reported an MMRM difference of least-squares means of -0.8, with a 75% confidence interval from -2.77 to 1.10 and p = 0.310. The unadjusted recalculation produced the same point estimate but a different interval and p-value.

The posted secondary results and safety summaries provide additional descriptive context, but multiplicity procedures and several analysis details are not reported in the registry record. The findings are best interpreted as an uncertain estimate for the defined primary population and endpoint.