Study to Assess the Efficacy, Safety, and Tolerability of SAR440340/REGN3500/Itepekimab in Chronic Obstructive Pulmonary Disease (COPD): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Study to Assess the Efficacy, Safety, and Tolerability of SAR440340/REGN3500/Itepekimab in Chronic Obstructive Pulmonary Disease (COPD) (NCT04701983), a randomized phase 3 study. The primary outcome is Annualized Rate of Adjudicated Moderate or Severe Acute Exacerbation of Chronic Obstructive Pulmonary Disease (AECOPD) Events Over the Placebo-Controlled Treatment Period.

2. Clinical Question

The comparison concerns exacerbation frequency in a specified population and treatment period. Moderate exacerbations were defined by worsening respiratory symptoms requiring systemic corticosteroids and/or antibiotics. Severe exacerbations involved hospitalization, observation for more than 24 hours in an emergency department or urgent-care facility, or death. Events had to meet the registry’s separation criteria to be counted as distinct events, and a third party adjudicated them.

The question is not limited to exacerbations. The registry also lists outcomes involving lung function, respiratory symptoms, severe exacerbations, and health-related quality of life, as well as safety and pharmacokinetics. Those outcomes provide additional descriptions of the trial, but they do not replace the prespecified primary endpoint.

3. Trial Design

This was a randomized, parallel-group, placebo-controlled phase 3 study of itepekimab in people with moderate-to-severe COPD. The official title calls it double-blind, while the registry’s masking designation is quadruple. Those descriptions are both recorded; further detail explaining the masking designation is not reported in the registry record. Sanofi is listed as sponsor. The registry lists the study as completed, with enrollment of 1127, a start date of 2020-12-16, and primary completion on 2025-04-11.

The listed groups were placebo Q2W, itepekimab 300 mg Q4W, and itepekimab 300 mg Q2W. The registry reports group sizes of 375, 377, and 375, respectively. Participants in the placebo group received matching subcutaneous injections every 2 weeks. Those assigned to Q2W itepekimab received active treatment every 2 weeks. In the Q4W group, active treatment was given every 4 weeks with matching placebo at the intervening 2-week interval. Each schedule was described as continuing for up to 52 weeks.

The primary endpoint timeframe was baseline through Week 52 for initial randomized participants, and baseline through Week 24 to 52 for additional randomized participants. The primary population included randomized participants from both treatment-duration portions. This means participants could have different lengths of observation within the stated timeframe. The registry record does not report the original sample-size justification, the trial’s detailed statistical analysis plan, or whether interim analyses were conducted. These details should not be inferred from the posted enrollment or the reported analyses.

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 planned intervention period was 52 weeks for initial randomized participants or variable 24-52 weeks for additional randomized participants. The post-treatment follow-up period was 20 weeks. Participants who completed end-of treatment (EOT) visit were offered to participate in long-term extension (LTS18133 \[NCT06208306\]) when and where available.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: The intent-to-treat (ITT) population included randomized participants from both 52 weeks treatment duration portion and variable treatment duration portion.

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: The randomized population included all participants with a treatment kit number allocated and recorded in the interactive response technology database, and regardless of whether the treatment kit was used or not.

6. Primary Endpoint

The registry lists the primary outcome as Annualized Rate of Adjudicated Moderate or Severe Acute Exacerbation of Chronic Obstructive Pulmonary Disease (AECOPD) Events Over the Placebo-Controlled Treatment Period, measured over Baseline (Day 1) up to Week 52 for initial randomized participants; Baseline (Day 1) up to Week 24 to 52 for additional randomized participants.

The primary endpoint is the annualized rate of adjudicated moderate or severe acute COPD exacerbation events over the placebo-controlled treatment period. An exacerbation was recorded by the investigator and then adjudicated by a third party. A moderate event required acute worsening of respiratory symptoms treated with systemic corticosteroids and/or antibiotics. A severe event involved hospitalization, observation for more than 24 hours in an emergency department or urgent-care facility, or death. For events to count separately, the registry required a specified interval between treatment courses or, for severe events, between discharge and a new admission.

The rate uses the number of qualifying events relative to total observation duration and is expressed as events per participant year. This approach accounts for differing observation time, which matters when participants do not all contribute the same duration of follow-up. It also distinguishes recurrent-event frequency from a simple yes-or-no measure of whether a participant ever had an exacerbation.

General statistical context: an annualized rate can make event frequency more interpretable when follow-up varies, but it does not by itself describe how events are distributed across participants. A rate can be influenced by participants with repeated events, and its interpretation depends on the event definition, adjudication, and observation time. The registry states that the primary rate was estimated using negative binomial regression. That model is commonly used for event counts when variation across participants is greater than a basic Poisson model would allow.

7. Results Posted in the Registry

• Itepekimab 300 mg Q4W: 0.71 versus 0.89 (events per participant year) on control; rate ratio 0.79 (95% CI 0.63–1.00, derived from the posted confidence limits); p ≈ 0.046.
• Itepekimab 300 mg Q2W: 0.65 versus 0.89 (events per participant year) on control; rate ratio 0.73 (95% CI 0.58–0.92, derived from the posted confidence limits); p ≈ 0.007.

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.

Annualized Rate of Adjudicated Severe Acute Exacerbation of Chronic Obstructive Pulmonary Disease Events Over the Placebo-Controlled Treatment Period

• Endpoint type: Event rate: events per unit of follow-up, compared as a rate ratio.
• Test: Poisson rate ratio, with the standard error taken from the posted confidence limits.
• Result:
  • Itepekimab 300 mg Q4W: 0.09 versus 0.14 (events per participant year) on control; rate ratio 0.65 (95% CI 0.39–1.10, derived from the posted confidence limits); p ≈ 0.108.
  • Itepekimab 300 mg Q2W: 0.08 versus 0.14 (events per participant year) on control; rate ratio 0.56 (95% CI 0.32–0.96, derived from the posted confidence limits); p ≈ 0.034.
• Interpretation:
  • The 95% confidence interval includes no difference (a ratio of 1), so these data do not show a statistically significant difference between Itepekimab 300 mg Q4W and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval excludes no difference (a ratio of 1), so the event rate is statistically lower for Itepekimab 300 mg Q2W than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change From Baseline in Pre-Bronchodilator Forced Expiratory Volume in One Second at Week 24

• 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 errors.
• Result:
  • Itepekimab 300 mg Q4W: mean 0.04 versus 0.03 on control; difference 0.01 (95% CI -0.03 to 0.05), standardized effect d = 0.03; z-test p = 0.649.
  • Itepekimab 300 mg Q2W: mean 0.03 versus 0.03 on control; difference 0.01 (95% CI -0.03 to 0.04), standardized effect d = 0.02; z-test p = 0.762.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Itepekimab 300 mg Q4W 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 Itepekimab 300 mg Q2W and the control. The interval gives the range of effects that remain compatible with the data.

Change From Baseline in Evaluating Respiratory Symptoms in Chronic Obstructive Pulmonary Disease (E-RS: COPD) Total Score at Week 24

• 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 errors.
• Result:
  • Itepekimab 300 mg Q4W: mean -1.54 versus -0.97 on control; difference -0.57 (95% CI -1.34 to 0.19), standardized effect d = -0.11; z-test p = 0.141.
  • Itepekimab 300 mg Q2W: mean -1.72 versus -0.97 on control; difference -0.75 (95% CI -1.51 to 0.02), standardized effect d = -0.14; z-test p = 0.055.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Itepekimab 300 mg Q4W 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 Itepekimab 300 mg Q2W and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists secondary outcomes spanning severe exacerbations, pulmonary function, respiratory symptoms, health-related quality of life, and other measures. Across the detailed results, the pattern is not uniform across outcome types or treatment schedules. Some estimates are more compatible with a difference from placebo than others, while intervals for some comparisons include values consistent with no group difference. These secondary endpoints add context to the primary event-rate result but do not independently confirm or explain it.

For severe exacerbations, the sponsor’s reported result is more compatible with a lower rate for Q2W than for placebo, while the Q4W interval includes one. The Week 24 pre-bronchodilator lung-function comparisons have confidence intervals spanning no difference. The respiratory-symptom results include a Q2W comparison whose interval reaches the null boundary, alongside a Q4W comparison with an interval spanning no difference. These are secondary results and should not be given the same evidential weight as a prespecified primary result without knowing the multiplicity strategy.

Unadjusted secondary p-values are vulnerable to false-positive findings when many outcomes and comparisons are examined. The registry lists 18 secondary outcomes, and the record does not report whether or how multiplicity was controlled. A nominally small p-value in one secondary comparison therefore should not be interpreted as definitive evidence in isolation. The secondary results are best read as a collection of supporting or exploratory observations, with attention to the size and precision of estimates, consistency across outcomes, and the analysis plan. That plan is not reported in the registry record.

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

• Annualized Rate of Adjudicated Severe Acute Exacerbation of Chronic Obstructive Pulmonary Disease Events Over the Placebo-Controlled Treatment Period
• Change From Baseline in Pre-Bronchodilator Forced Expiratory Volume in One Second at Week 24
• Change From Baseline in Evaluating Respiratory Symptoms in Chronic Obstructive Pulmonary Disease (E-RS: COPD) Total Score at Week 24
• Change From Baseline in Post-Bronchodilator Forced Expiratory Volume in One Second at Week 24
• Change From Baseline in St. George's Respiratory Questionnaire (SGRQ) Total Score at Week 24
• Percentage of Participants With a Decrease From Baseline of at Least 4 Points in St. George's Respiratory Questionnaire Total Score at Week 24
• Rate of Change in Post-Bronchodilator Forced Expiratory Volume in One Second From Baseline (Post-Bronchodilator Forced Expiratory Volume in One Second Slope) After Week 4
• Change From Baseline in Post-Bronchodilator Forced Expiratory Volume in One Second at Week 52

9. Statistical Interpretation

10. Statistical Methods Explained

The primary endpoint is a recurrent-event rate, not a continuous measurement or a one-time binary outcome. The registry defines the annualized rate as the total number of moderate or severe exacerbation events divided by total observation duration. It reports the unit as events per participant year and says the estimate was obtained with negative binomial regression. The model-based rate ratio compares each itepekimab schedule with placebo.

Why use a negative binomial model?

General statistical context: event-count models need to account for the fact that participants may contribute different numbers of events. A Poisson model assumes that the variability of counts is closely tied to their average. In clinical event data, counts may vary more than that assumption allows, for example because some participants have more recurrent events than others. This extra variability is called over-dispersion. A negative binomial model allows greater variability and is often used for recurrent-event rates. The registry identifies this as the sponsor’s primary model. The posted record does not provide the full model specification, covariates, or details of how follow-up time entered the analysis beyond its endpoint description.

What does the rate ratio express?

A rate ratio compares estimated event rates between groups. A value below one indicates a lower estimated rate in the itepekimab group relative to placebo; a value above one indicates a higher estimated rate. It is a relative comparison, not an absolute count of prevented events and not the probability that an individual participant will experience an event. The registry’s reported rate ratios come from negative binomial regression, and the corresponding confidence intervals and p-values are part of those model-based analyses.

What do confidence intervals and p-values contribute?

General statistical context: a confidence interval describes a range of values compatible with the observed data and the stated statistical procedure. Its width reflects precision: wider intervals indicate more uncertainty than narrower intervals. A p-value assesses how unusual the data would be under a specified null hypothesis and model. It does not give the probability that a treatment effect is real, nor does it establish clinical importance. The registry reports 95% confidence intervals for the primary model estimates.

There is also a separate set of simple recalculations based on posted summary statistics. Such recalculations are not the same as reproducing the sponsor’s negative binomial analysis: summary-level calculations may use different assumptions and cannot recover unreported participant-level modeling details. The comparison calculations use a Poisson-based approximation, while the registry’s primary analysis is negative binomial. Since the record flags a discrepancy, the sponsor’s own analysis takes precedence.

How are other endpoint types analyzed?

The registry lists secondary outcomes that include event rates, lung-function measurements, respiratory symptom scores, and health-related quality of life. For the detailed Week 24 continuous outcomes, the sponsor reports mixed model for repeated measures (MMRM) analyses. General statistical context: MMRM is designed to analyze repeated measurements over time and can estimate group differences while accounting for correlations among measurements from the same participant. The posted summary does not provide enough detail to reconstruct the model specification or missing-data assumptions.

Several secondary outcomes are expressed as change from baseline. Their reported estimates are least-squares means, which are model-based rather than necessarily raw arithmetic averages. The registry reports standard errors for group-level estimates and sponsor confidence intervals and p-values for comparisons. Those quantities answer different questions: a group estimate describes change within a group under the model, while a between-group contrast compares estimated changes. A within-group change alone is not evidence that the groups differ.

The primary population is described as intent-to-treat and includes randomized participants from both treatment-duration portions. The registry does not report the detailed analysis population rules for every secondary outcome, handling of missing observations, sensitivity analyses, or all adjustment variables. Such choices can affect estimates, especially for repeated outcomes or unequal observation periods, and should not be filled in by assumption.

For event definitions, the registry specifies investigator recording, third-party adjudication, severity criteria, and separation rules for counting events. These rules help make event counting more consistent, but the endpoint still depends on clinical classification and the observation period. The results should therefore be read as model-based comparisons of events defined and collected in this trial, rather than as a direct measure of every aspect of COPD burden.

11. Confidence Intervals and Precision

The sponsor’s primary rate-ratio estimate for Q4W itepekimab is 0.795, with a 95% confidence interval from 0.654 to 0.966. For Q2W itepekimab, the estimate is 0.729, with a 95% confidence interval from 0.598 to 0.890. Both reported intervals lie below one, the value corresponding to equal rates in the two groups. The intervals nevertheless span a range of possible relative rate differences, so the point estimates should not be read as exact values.

General statistical context: a confidence interval is a measure of uncertainty under the model and analysis used. A narrower interval indicates greater precision than a wider interval, while an interval’s location indicates which effect values are more compatible with the data. A 95% confidence interval is not a guarantee that the true value lies in the particular interval, and it is not a range of individual participants’ outcomes.

For severe exacerbations, the sponsor reports a rate ratio of 0.659 for Q4W versus placebo, with a 95% confidence interval from 0.430 to 1.012. For Q2W versus placebo, the reported estimate is 0.556, with an interval from 0.356 to 0.869. The Q4W interval includes one, whereas the Q2W interval lies below one. This describes the uncertainty in those secondary estimates; it does not establish that the schedules differ from one another.

The registry’s primary endpoint spans different follow-up durations for initial and additional randomized participants. Unequal observation time is incorporated into the annualized rate, but it remains relevant context when judging precision and generalizability. The record does not report all model details or a multiplicity procedure, so the confidence intervals should be understood as reported for their individual analyses rather than assumed to provide simultaneous coverage across every endpoint and 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 participants per arm, not total events. They are illustrative calculations based on the observed effect, not the trial’s original design assumptions. The calculation 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 set to the stated fraction of the observed effect. The trial’s own sample-size justification is not reported in the registry record.

The 80% power column gives the illustrative number of participants per arm that would, under those assumptions and for the specified effect, yield an 80% chance of rejecting the null hypothesis if that effect were the true one. The 90% power column uses the same general idea but targets a higher chance of detecting the specified effect. These are design calculations, not observed power, and they do not tell us the probability that the trial’s result is correct.

Rows planning for 100%, 75%, and 50% of the observed effect ask about progressively smaller effects. Smaller effects are harder to distinguish from random variation, so they require more participants under the same assumptions. The figures are particularly sensitive to the effect estimate used as their starting point; an observed effect may not be a reliable estimate of the effect in a future study. The estimates also do not account for design features that are not included in the stated assumptions.

For the outcomes displayed in the planning material, the calculation reports participants per arm. The stated exception in the general calculation description concerns time-to-event outcomes, for which totals refer to events; the primary outcome analyzed is an event rate, and its planning figures are presented as participants per arm. These illustrations should not be treated as the trial’s target enrollment, an assurance of adequate power, or a substitute for the sponsor’s design rationale.

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, λ₀ and λ₁ are event rates per patient-year, and T is follow-up per participant in years. This assumes Poisson counts and equal follow-up.

Worked calculation for this trial

1. Control rate λ₀ = 0.8910; treatment rate λ₁ = 0.7080 events per patient-year; follow-up T = 0.00 years.
2. n = (1.96 + 0.842)² × (1/0.8910 + 1/0.7080) / (0.00 × [ln(0.795)]²) = 137,485.3, rounded up to 137,486 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
lambda0 <- 0.891                      # control rate, events per patient-year
lambda1 <- 0.708                      # treatment rate
tt      <- 0.0027378507871321                       # follow-up per participant, years
n_per_arm <- function(power, frac = 1) {
  l1 <- lambda0 * (lambda1 / lambda0)^frac   # smaller effect = fraction of the observed log rate ratio
  ceiling(round((z_a + qnorm(power))^2 * (1 / lambda0 + 1 / l1) / (tt * log(l1 / lambda0)^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 = ",")))

# Simulation 1: Poisson counts. Simulation 2: over-dispersed counts (variance = 1.5 x mean), analysed with the matching variance.
set.seed(4701983)
n    <- n_per_arm(0.80)
reps <- 20000
m0 <- lambda0 * n * tt; m1 <- lambda1 * n * tt
x0 <- rpois(reps, m0); x1 <- rpois(reps, m1)
z  <- log(x1 / x0) / sqrt(1 / x0 + 1 / x1)
cat(sprintf("Simulated power, Poisson counts, n = %s per arm: %.3f\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE)))
phi <- 1.5
y0 <- rnbinom(reps, mu = m0, size = m0 / (phi - 1)); y1 <- rnbinom(reps, mu = m1, size = m1 / (phi - 1))
z2 <- log(y1 / y0) / sqrt(phi * (1 / y0 + 1 / y1))
cat(sprintf("Simulated power, over-dispersed counts (phi = 1.5), same n: %.3f\n", mean(abs(z2) > z_a, na.rm = TRUE)))

Output from running the code

100% of observed effect: n per arm = 137,486 (80% power), 184,054 (90% power)
 75% of observed effect: n per arm = 236,812 (80% power), 317,023 (90% power)
 50% of observed effect: n per arm = 516,665 (80% power), 691,668 (90% power)
Simulated power, Poisson counts, n = 137,486 per arm: 0.802
Simulated power, over-dispersed counts (phi = 1.5), same n: 0.636

The first simulation draws Poisson counts and should land close to the target power. The second allows extra variability (variance 1.5 times the mean, a purely illustrative value), which lowers the power at the same sample size, so rate trials usually need more participants than the Poisson formula suggests.

14. Analyses Reported by the Sponsor

The registry reports sponsor analyses using negative binomial regression for the primary rate endpoint. The Q4W comparison is reported as a rate ratio of 0.795, with a 95% confidence interval from 0.654 to 0.966 and p = 0.021. The Q2W comparison is reported as 0.729, with a 95% confidence interval from 0.598 to 0.890 and p = 0.002.

The separate simple recalculations from posted summary statistics do not exactly match the sponsor estimates and intervals. The discrepancy flag is true, so the sponsor’s own analysis takes precedence. The recalculations are unadjusted checks and do not reproduce the full negative binomial model. They should not be presented as the trial’s official inference or used to replace the reported analysis.

This distinction matters because the sponsor’s model accounts for the event-rate analysis as reported in the registry, while summary-level recalculation relies on simplified assumptions. Differences in model and calculation approach can lead to different point estimates, interval limits, or p-values. The trial’s detailed model specification and the reasons for the discrepancy are not reported in the registry record. The appropriate reading is therefore to retain the sponsor-reported analyses as the primary inferential results and treat the separate calculations as supplementary context only.

15. Multiplicity, Missing Data and Analysis Populations

The registry contains a primary endpoint and 18 secondary outcomes, with multiple treatment-versus-placebo comparisons. When many outcomes or comparisons are tested, the chance of obtaining at least one apparently notable result by chance can increase. Statistical methods that address this issue may adjust significance thresholds, control an error rate, or define a hierarchy for testing. Whether such a procedure was used in this trial is not reported in the registry record.

The sponsor’s reported p-values should therefore be read as values attached to the reported analyses, not assumed to be multiplicity-adjusted. The registry does not describe a testing hierarchy, family-wise error procedure, false-discovery procedure, or other multiplicity strategy. This absence does not establish that no procedure was used; it means the details are not reported in the registry record. Secondary findings, especially those near conventional thresholds, should be treated cautiously when their multiplicity status is unknown.

The primary endpoint population is described as intent-to-treat and includes randomized participants from both the 52-week and variable-duration portions. The record does not detail the handling of missing endpoint data, withdrawals, or incomplete follow-up, nor does it report sensitivity analyses assessing those choices. It also does not provide a complete statistical analysis plan or details of interim analyses. These items are not reported in the registry record, and no assumptions about them should be made.

Missing data can matter differently across endpoints. Event rates depend on observed time and event ascertainment, while repeated lung-function or symptom measurements depend on the availability of assessments over time. General statistical context: a model can use available observations under stated assumptions, but those assumptions and sensitivity checks are important for judging robustness. The registry summaries do not provide enough detail to assess those assumptions fully.

The reported endpoint-level estimates remain interpretable as the analyses recorded, but uncertainty about multiplicity and missing-data methods limits how far they can support broader confirmatory claims. The primary result and secondary findings should be kept distinct, and the unreported analysis details should remain explicit limitations rather than being reconstructed from the outcome summaries.

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: chronic obstructive pulmonary disease (7.8%), pneumonia (4.5%), infective exacerbation of chronic obstructive airways disease (2.4%), covid-19 (1.3%), covid-19 pneumonia (1.3%).

The registry reports serious adverse events among 82 of 374 participants at risk in the placebo group, 72 of 377 in the Q4W group, and 68 of 374 in the Q2W group. Other adverse events are reported for 96 of 374, 89 of 377, and 83 of 374, respectively. Death counts are listed as 9, 4, and 5 for the placebo, Q4W, and Q2W groups. These are descriptive counts and denominators as recorded; they do not by themselves establish that an event was caused by the assigned treatment.

The registry also lists serious-event terms with percentages, including chronic obstructive pulmonary disease at 7.8%, pneumonia at 4.5%, and infective exacerbation of chronic obstructive airways disease at 2.4%. It lists Covid-19 and Covid-19 pneumonia at 1.3% each, and influenza at 0.5%. The record excerpt does not specify an arm for these term percentages, so they should not be assigned to a particular group.

Safety comparisons require context about event definitions, follow-up, and attribution. The registry figures alone do not establish comparative risk or explain the causes of deaths or serious events. The full safety analysis and event-level details are not reported in the registry record.

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

The primary result describes a model-based comparison of annualized moderate or severe COPD exacerbation rates during the placebo-controlled treatment period. The sponsor-reported rate ratios are below one for both itepekimab schedules relative to placebo, and both primary confidence intervals lie below one. This is a statistical description of the posted results for the trial population and endpoint, not a general claim about every person with COPD or every treatment setting.

The endpoint captures qualifying recurrent exacerbations, as defined and adjudicated in the study. It does not encompass all symptoms, lung-function changes, quality of life, or other aspects of COPD. The secondary results address some of those domains, but they vary in precision and are subject to the uncertainty around multiple comparisons and analysis details not reported in the registry record.

A rate ratio is a relative measure. It does not directly state how many participants experienced an event, how many events an individual participant had, or what a participant’s personal outcome would be. The group-level annualized rates and rate ratios also cannot establish an individual treatment response. Similarly, a p-value does not indicate the chance that an intervention is beneficial, and a confidence interval does not describe the range of responses for individual participants.

These findings should not be generalized automatically beyond former smokers with moderate-to-severe COPD, the treatment schedules studied, and the placebo-controlled follow-up described. The record includes treatment observation from baseline through Week 52 for initial randomized participants and from baseline through Week 24 to 52 for additional randomized participants. Differences in population, care, follow-up, or outcome definitions could affect results elsewhere.

The registry results do not, on their own, settle the overall balance of efficacy and safety, establish clinical importance, or replace a full assessment of the trial report. They provide a statistical account of specified outcomes and comparisons. The registry record does not report enough detail about multiplicity, missing-data handling, or the full statistical plan to resolve every inferential question.

18. Why This Trial Matters Statistically

This trial is statistically informative because its primary endpoint concerns recurrent exacerbations, which are event counts accumulated over observation time rather than a single measurement. Annualizing the rate allows comparisons when participants contribute different follow-up durations, while the registry’s negative binomial model addresses event-count variation beyond a basic Poisson assumption. The endpoint definition and adjudication process are also central to understanding what is being counted.

The study compares two itepekimab schedules with placebo and reports model-based rate ratios with confidence intervals. That gives readers information about both the direction and uncertainty of the primary estimates. The sponsor’s reported primary intervals lie below one, while the secondary results are less uniform. Keeping the primary and secondary evidence distinct is important, particularly because the record does not report a multiplicity procedure.

The record also illustrates why statistical results must be tied to their analysis method. Simple recalculations from summary statistics differ from the sponsor’s negative binomial results, and the discrepancy is flagged. The sponsor’s analysis takes precedence; the difference cautions against treating a simplified calculation as interchangeable with the trial’s own model.

Finally, interpreting estimates requires attention to the population, endpoint definitions, follow-up, and incomplete reporting. Former smokers with moderate-to-severe COPD were studied, and the primary timeframe varied for some randomized participants. The registry identifies the intent-to-treat population but does not report full details on missing data, multiplicity, or the original design assumptions. Statistical significance is only one component of interpretation; precision, endpoint scope, and transparency about analytic choices matter as well.

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.
• Rate comparisons use a Poisson approximation unless the sponsor posted confidence limits; real event counts are often over-dispersed.

The primary endpoint depends on investigator-recorded events that meet the registry’s definitions and are adjudicated by a third party. That process supports consistent classification, but the rate still reflects the chosen criteria for moderate and severe exacerbations and for counting events separately. Results based on a different definition may not be directly comparable.

Follow-up duration was not identical for every participant: the registry describes baseline through Week 52 for initial randomized participants and baseline through Week 24 to 52 for additional randomized participants. Annualization accounts for observation time in the rate calculation, but variation in follow-up remains relevant to interpreting event accumulation and precision. The detailed approach to censoring or incomplete observation is not reported in the registry record.

The population was former smokers with moderate-to-severe COPD. The results should not automatically be extended to other COPD populations or settings. The registry describes Q2W and Q4W schedules but does not report subgroup findings in the registry record for this analysis.

Another limitation is the discrepancy between the simple unadjusted recalculations and the sponsor’s reported primary analysis. The sponsor’s negative binomial analysis takes precedence, but the reason for the difference and the full model specification are not reported in the registry record. The secondary analyses also involve numerous outcomes, and multiplicity handling is not reported. Missing-data methods, sensitivity analyses, and the trial’s original sample-size rationale are not reported in the registry record either.

The safety summaries are counts and term percentages, not a complete causal assessment. The listed adverse-event figures do not establish attribution, and the serious-term percentages are not assigned to treatment groups in the record excerpt. These limitations support a focused reading of the estimates as registry-reported results rather than a complete account of every clinical or analytic consideration.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Study to Assess the Efficacy, Safety, and Tolerability of SAR440340/REGN3500/Itepekimab in Chronic Obstructive Pulmonary Disease (COPD) — NCT04701983.
• Registry record last updated 2026-10-15; status last verified 2026-09.
• Results first posted 2026-10-15.
• 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

NCT04701983 is a completed, randomized, parallel-group, placebo-controlled phase 3 study sponsored by Sanofi. It enrolled 1127 participants with moderate-to-severe COPD and evaluated itepekimab 300 mg every 2 weeks or every 4 weeks against placebo. The population for the primary endpoint was former smokers, and the primary analysis population was intent-to-treat.

The primary outcome was the annualized rate of adjudicated moderate or severe COPD exacerbation events over the placebo-controlled treatment period. The sponsor reports negative binomial rate-ratio analyses for both itepekimab schedules versus placebo, with both reported primary confidence intervals below one. Simple summary-statistic recalculations differ, so the sponsor’s analysis takes precedence.

The registry lists secondary outcomes spanning exacerbations, lung function, respiratory symptoms, and health-related quality of life, alongside safety outcomes. The multiplicity approach, detailed missing-data methods, and original sample-size justification are not reported in the registry record.