AZD7442 for Inpatients With COVID-19 (An ACTIV-3/TICO Treatment Trial): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for AZD7442 for Inpatients With COVID-19 (An ACTIV-3/TICO Treatment Trial) (NCT05780437), a randomized phase 3 study. The primary outcome is Number of Participants With Sustained Recovery.

2. Clinical Question

3. Trial Design

This was a Phase 3, randomized, triple-masked, parallel-group trial. The registry record names it as an ACTIV-3/TICO treatment trial and describes its broader purpose as evaluating investigational therapeutics for hospitalized patients with COVID-19. The sponsor was the National Institute of Allergy and Infectious Diseases (NIAID). The trial status is completed.

The registry record lists enrollment of 1455. The posted primary-outcome results give 710 participants in the AZD7442 plus standard-of-care group and 707 in the placebo plus standard-of-care group. Both groups received standard of care, with remdesivir provided unless contraindicated for an individual patient. The active group received AZD7442 by IV infusion; the comparator group received placebo by IV infusion.

The recorded start date is 2021-02-10, and the primary completion date is 2022-01-28. These dates describe the registry record and do not, by themselves, specify the timing of individual participant follow-up or the dates of analysis.

Random allocation is intended to support a fair comparison by reducing systematic differences between groups at entry. Masking can limit the influence of expectations on care, reporting, and assessment. The registry lists triple masking, but does not identify in the record which roles were masked. The protocol’s allocation procedures, masking details, and original design assumptions are not reported in the registry record.

4. Participant Flow and Accounting

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

Before assignment: The number of participants consented was not collected, so these numbers are the number of participants randomized.

Overall Study

Reasons for not completing this 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 Number of Participants With Sustained Recovery, measured over Through Day 90.

The primary endpoint counts participants who achieved sustained recovery through Day 90. Recovery required discharge from the index hospitalization, followed by being alive and at home for 14 consecutive days before Day 90. “Home” was defined as the level of residence or facility where the participant lived before the hospitalization that led to enrollment.

The definition allows readmission after a first discharge home. If readmission occurred within 14 days of that discharge, the endpoint was not reached until the participant had subsequently been at home for 14 consecutive days. This makes the outcome more specific than discharge alone: it incorporates survival and a sustained period at home, while accounting for an early readmission.

A binary endpoint is useful when the clinical question concerns whether each participant did or did not meet a defined recovery criterion within a specified follow-up period. It turns each participant’s course into an event count and a proportion for each group, which can then be compared. Such a summary is easier to interpret than a single measurement of health status, but it does not describe every detail of recovery, the timing of discharge, or health after the endpoint is met. Those details are not captured by the primary measure as defined in the registry record.

7. Results Posted in the Registry

• Placebo Plus SOC: 84.0% (594/707) versus 86.9% (617/710) on control; risk difference -2.9 percentage points (95% CI -6.6 to 0.8), risk ratio 0.97 (0.93–1.01); unadjusted two-proportion z-test p = 0.124.

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.

Number of Participants Who Died From All Causes

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Placebo Plus SOC: 12.2% (86/707) versus 8.6% (61/710) on control; risk difference 3.6 percentage points (95% CI 0.4 to 6.7), risk ratio 1.42 (1.04–1.93); unadjusted two-proportion z-test p = 0.027.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for Placebo Plus SOC than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcomes add context to the primary recovery result, but they answer different questions. The registry lists safety outcomes through Day 5, Day 28, and Day 90, as well as all-cause death through Day 90. The posted material includes a numerical comparison for death, while results for the listed safety outcomes at those follow-up times are not reported in the registry record.

A secondary outcome can be clinically or scientifically informative even when the primary outcome is not conclusive. However, a pattern across outcomes is most useful when the outcomes, analysis methods, and interpretation hierarchy were prespecified and transparently reported. The registry record does not report a multiplicity strategy or a statistical analysis plan. Without that information, the secondary results should be regarded as additional descriptive and inferential evidence, rather than as a set of independent confirmatory tests.

Multiplicity matters because evaluating several outcomes creates several opportunities for an apparently notable result to arise by chance. An unadjusted p-value addresses a single comparison under its stated model; it does not account for the broader set of outcomes unless the method specifically does so. The death result’s unadjusted p-value therefore deserves more cautious interpretation than a result whose place in a prespecified testing hierarchy is documented.

The secondary outcomes should not be used to replace the primary endpoint or to resolve its uncertainty by themselves. They provide different views of outcomes during follow-up, and their relevance depends on how they were defined, collected, and analyzed. The registry record does not report the results of the safety outcomes through the specified days, so the full secondary-outcome pattern cannot be assessed from the recorded results.

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

• Number of Participants With a Safety Outcome Through Day 5
• Number of Participants With a Safety Outcome Through Day 28
• Number of Participants With a Safety Outcome Through Day 90
• Number of Participants Who Died From All Causes

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is binary: each participant either met the sustained-recovery definition through Day 90 or did not. The posted group results are counts of participants meeting that definition, alongside the group sizes. A group proportion expresses the event count relative to the number of participants in that group. Comparing proportions is a natural way to summarize a binary outcome when follow-up is framed around whether an event occurred by a stated time.

What does the risk difference express?

The risk difference is the difference between the two group proportions. In the primary comparison, the registry expresses the contrast as placebo minus AZD7442. A negative value therefore means that the observed proportion was lower in the placebo group. A value of zero would indicate equal observed proportions. The risk difference uses the same scale as the proportions, which makes it possible to understand the contrast in absolute rather than relative terms.

The risk difference is an unadjusted comparison of the posted group summaries. It does not account for participant characteristics or other variables. The registry record does not report an adjusted model or a covariate adjustment strategy for this result. A simple unadjusted comparison can describe the observed groups, but it should not be treated as a substitute for a prespecified analysis plan that is not documented in the registry record.

How should a confidence interval be understood?

A confidence interval gives a range of estimates that reflect sampling uncertainty under the method used to calculate it. It is not a guarantee that the true effect lies within the interval, nor is it a direct probability statement about the effect. For the primary risk difference, the interval extends from -0.066 to 0.008. Because that range includes zero, the result is compatible with no difference as well as with differences in either direction. The width also conveys that the point estimate is not exact.

What does a p-value add?

A p-value describes how unusual data at least as incompatible with a specified no-difference model would be if that model and the analysis assumptions were correct. It does not measure the size or importance of an effect, and it is not the probability that the no-difference model is true. The primary unadjusted p-value is 0.124. That figure should be interpreted together with the risk difference and confidence interval, rather than used as a stand-alone verdict.

The death comparison has its own risk difference, confidence interval, and unadjusted p-value. Since it is a secondary outcome and the registry record does not report a multiplicity adjustment, its p-value does not carry the same evidential weight as a result from a fully specified analysis plan that addresses multiple outcomes. The registry record lists four secondary outcomes, including safety outcomes at different follow-up times and all-cause death through Day 90.

What does randomization contribute?

Randomization is a design method intended to make treatment groups comparable on average at the time of allocation, including for factors that are not measured. It supports causal interpretation when allocation, follow-up, outcome measurement, and analysis are appropriately conducted. The registry identifies the trial as randomized, but the allocation sequence, concealment procedures, analysis population, and handling of departures from assigned treatment are not reported in the registry record. Those details matter for judging how closely the analysis preserves the advantages of randomization.

Masking is another design feature that can reduce the influence of expectations on behavior and assessment. The registry calls the trial triple-masked, but does not specify which groups of people were masked. It is therefore possible to describe the reported masking status, but not to assess the exact masking procedures from the registry record alone.

What are the planning illustrations?

The planning figures are based on the observed group effect and specified fractions of that effect. They use a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. The figures describe participants per arm for the binary outcomes. They are planning illustrations rather than observed trial findings, and they are not observed power. The original trial’s own sample-size assumptions and justification are not reported in the registry record.

11. Confidence Intervals and Precision

Precision is about how narrowly the data estimate a group difference. The primary risk difference is -0.029, with a 95% confidence interval from -0.066 to 0.008. The interval includes zero and spans values that would correspond to differences in either direction. This means the observed point estimate alone should not be read as a precise determination of the direction or size of the underlying difference.

The width of a confidence interval depends on the amount of information in the data and on the variability of the outcome. More information generally narrows an interval, while limited information widens it. For a binary outcome, the number of participants with and without the event in each group contributes to the uncertainty of the estimated proportions and their contrast.

The death comparison has a risk difference of 0.036, with a 95% confidence interval from 0.004 to 0.067. Unlike the primary interval, this interval does not include zero. It nevertheless remains an estimate with uncertainty, and its interpretation must account for the fact that it is a secondary comparison with an unadjusted p-value. The interval should not be considered in isolation from the broader set of outcomes and the unreported analysis plan.

Confidence intervals are useful because they show both the direction and the range of values reasonably compatible with the data under the calculation method. They do not resolve limitations in the design or reporting. In particular, the registry record does not report missing-data handling, analysis populations, or the prespecified multiplicity strategy. Those omissions limit how fully the precision and inferential status of the posted comparisons can be assessed.

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 illustrations state participants per arm for the binary outcomes. They use the observed effect as a starting point and show planning scenarios for detecting 100% of that effect, 75% of the observed effect, and 50% of the observed effect. The calculation assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. These are planning assumptions for the illustrations; the trial’s original design assumptions are not reported in the registry record.

The 80% power column gives the modeled participants per arm under which the specified planning method would have an 80% chance of detecting the chosen effect if the assumptions hold. The 90% power column gives the corresponding per-arm figure for a higher chance under those same assumptions. These columns describe hypothetical future planning, not the outcome of the completed trial. The figures are not observed power.

The effect being targeted matters. A smaller effect is harder to distinguish from ordinary sampling variation, so planning for a smaller fraction of the observed effect requires more participants per arm. The figures can therefore be read as sensitivity scenarios: they show how the required group size changes when the target effect is made smaller, without claiming that any one scenario was the trial’s original target.

The registry record’s sample-size assumptions describe these illustrations, not the design rationale used before enrollment. The original justification, including any anticipated effect, planned power, or other design considerations, is not reported in the registry record.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.869; treatment proportion p₁ = 0.840; average p̄ = 0.855.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.4985 = 0.9771.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.4981 = 0.4192.
4. n = (0.9771 + 0.4192)² / (-0.0288)² = 2,343.4, rounded up to 2,344 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
p0 <- 0.869014084507042                          # control proportion
p1 <- 0.84016973125884                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(5780437)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 2,344 (80% power), 3,137 (90% power)
 75% of observed effect: n per arm = 4,081 (80% power), 5,463 (90% power)
 50% of observed effect: n per arm = 8,988 (80% power), 12,031 (90% power)
power.prop.test: 2343.4 
Simulated power at n = 2,344 per arm: 0.797 (20000 replicates)

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

14. Multiplicity, Missing Data and Analysis Populations

The registry record does not report how multiplicity was addressed. This is important because the trial lists a primary endpoint and several secondary outcomes, including safety outcomes at different follow-up times and all-cause death. If multiple outcomes are tested, the chance of at least one apparently unusual result can increase unless the analysis plan accounts for the family of comparisons or defines a testing hierarchy.

The posted comparison p-values are unadjusted. They describe the individual comparisons as reported, but do not establish that the overall error rate across outcomes was controlled. No adjustment method, hierarchy, or distinction between confirmatory and exploratory secondary testing is reported in the registry record. The death comparison should therefore be treated as a secondary finding requiring cautious interpretation, rather than as an independently conclusive result.

Missing-data procedures are also not reported in the registry record. For the primary endpoint, participants who do not have enough recorded information to determine whether they met the sustained-recovery definition could affect the estimated proportions. The record does not state how such cases were classified, whether any imputation was used, or how incomplete follow-up was handled.

The analysis populations are not reported in the registry record. The posted group counts do not, by themselves, establish whether the results used an intention-to-treat population, a modified intention-to-treat population, or another analysis set. Details about treatment adherence, crossovers, exclusions after randomization, and protocol deviations are also not reported. These choices can affect how well an analysis retains the comparability created by randomization.

The registry identifies the trial as randomized and triple-masked, but does not report the full statistical analysis plan or the original design assumptions. Consequently, the posted estimates can be described as recorded, while important aspects of their prespecification and analysis remain unavailable in the registry record.

15. 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 0% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: pneumothorax (0.6%), anemia (0.3%), hypertransaminasemia (0.3%), acute kidney injury (0.3%), respiratory failure (0.3%).

The posted safety figures list serious adverse events in 36 of 710 participants in the AZD7442 plus standard-of-care group and 39 of 707 in the placebo plus standard-of-care group. Other adverse events are listed for 176 of 710 and 184 of 707 participants, respectively. The registry also lists deaths through Day 90 as 61 and 86 participants, respectively; death is separately identified as a secondary outcome.

These counts describe what was recorded in each group. They do not, on their own, establish that an event was caused by AZD7442 or placebo, and the figures do not adjust for differences in follow-up or other factors. Serious adverse-event terms reported most often include pneumothorax at 0.6%, and anemia, hypertransaminasemia, acute kidney injury, respiratory failure, and cardiac arrest at 0.3% each.

The registry lists safety outcomes through Day 5, Day 28, and Day 90, but does not report those outcome results in the registry record. The adverse-event counts should therefore be interpreted as descriptive safety information, not as a complete account of the prespecified safety outcomes.

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

The primary result describes the proportion of participants who met the registry’s definition of sustained recovery through Day 90. The observed proportions were higher in the AZD7442 group than in the placebo group, but the posted risk-difference confidence interval includes zero and the unadjusted p-value is 0.124. The estimate is therefore uncertain: the data do not identify a clear difference in either direction with high precision.

This does not mean that the groups were proven to be identical. A result that does not clearly distinguish a difference from no difference may reflect limited precision, a small underlying difference, or both. The confidence interval is essential to understanding what sizes and directions of difference remain compatible with the data.

The secondary death comparison is a separate result. Its confidence interval does not include zero, but it is an unadjusted secondary analysis, and the registry record does not report a multiplicity strategy. It should not be treated as if it replaced the primary outcome or as if it settled the overall interpretation without regard to the other outcomes and the missing analysis details.

The posted adverse-event counts are descriptive and do not by themselves establish causation. The registry record does not report results for the safety outcomes at the stated follow-up days, nor does it document the analysis population, missing-data approach, or full statistical analysis plan. Those limitations constrain interpretation of both efficacy and safety findings.

These results apply to the trial population and treatment comparison described in the registry record: hospitalized people with COVID-19, AZD7442 plus standard of care compared with placebo plus standard of care. The posted results alone do not support claims beyond that study context, and they do not capture every aspect of participants’ clinical courses.

17. Why This Trial Matters Statistically

This trial illustrates why a binary clinical endpoint needs a careful definition. “Sustained recovery” is not simply discharge: it requires being alive and at home for 14 consecutive days before Day 90, with a specific rule for readmission soon after discharge. That definition gives the group comparison a clear target, while also making the result dependent on the details of follow-up and outcome ascertainment.

It also demonstrates the importance of reading an estimate together with its interval. The primary risk difference is a point estimate, but the confidence interval spans zero. The interval communicates uncertainty that is lost if attention is restricted to whether a p-value passes a threshold. Reporting the effect size and its precision together allows a more measured statistical interpretation.

The distinction between primary and secondary outcomes is also consequential. A secondary comparison can be informative, but the evidential weight of an unadjusted result depends on how many outcomes were examined and whether the analysis plan addressed that multiplicity. The registry record does not report such a plan, making that uncertainty part of the statistical reading rather than a minor technical detail.

Finally, the planning illustrations are not evidence of the trial’s original design assumptions or its achieved power. They show how assumed effect size and power targets relate to hypothetical participant requirements under stated calculation assumptions. Keeping planning quantities separate from observed trial results helps prevent misinterpretation of a completed study.

18. 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 several details needed for a full assessment of the analyses. These include the statistical analysis plan, original sample-size justification, analysis populations, handling of missing data, and the method used to address multiplicity. The record also does not identify which roles were masked under the triple-masked design or describe allocation concealment.

The primary endpoint depends on discharge, survival, residence, and the timing of any readmission. The registry definition is detailed, but the record does not report how endpoint status was established for participants with incomplete follow-up or uncertain residence information. Those operational details can affect a binary outcome that requires a sustained period at home.

The registry lists safety outcomes through Day 5, Day 28, and Day 90, but their results are not reported in the registry record. The posted adverse-event counts provide descriptive information, but do not supply the full results for these listed secondary outcomes or establish whether observed events were attributable to a study intervention.

The primary comparison is unadjusted, and the registry record does not report adjusted analyses. The posted results are therefore limited to the recorded group summaries and comparisons. The generalizability of the findings beyond hospitalized participants with COVID-19 receiving the described standard of care is not established by the registry record alone.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: AZD7442 for Inpatients With COVID-19 (An ACTIV-3/TICO Treatment Trial) — NCT05780437.
• Registry record last updated 2025-02-04; status last verified 2025-01.
• Results first posted 2024-07-30.
• 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.

22. Record Summary

The registry record describes a completed, randomized, triple-masked, parallel-group Phase 3 trial of AZD7442 plus standard of care versus placebo plus standard of care in hospitalized people with COVID-19. Enrollment is listed as 1455. The recorded start date is 2021-02-10, and primary completion is dated 2022-01-28.

The primary outcome was sustained recovery through Day 90. The posted risk difference, expressed as placebo minus AZD7442, was -0.029, with a 95% confidence interval from -0.066 to 0.008 and an unadjusted p-value of 0.124. The interval includes zero, so the primary comparison remains uncertain.

The registry also posts a secondary comparison for all-cause death through Day 90. Important analysis details, including missing-data procedures, analysis populations, and multiplicity methods, are not reported in the registry record.