This page separates reported trial results from statistical interpretation. Every numerical result on this page is taken from the ClinicalTrials.gov record for ACTT-3. The registry provides the official trial record.
1. Trial at a Glance
ACTT-3 was a completed phase 3 randomized, parallel-group, double-blind clinical trial evaluating remdesivir plus interferon beta-1a versus remdesivir plus placebo in COVID-19. The registry reports 969 enrolled participants and four registered primary endpoints, all centered on time to recovery during Day 1 through Day 29.
| Feature | ACTT-3 |
|---|---|
| Trial name | Adaptive COVID-19 Treatment Trial 3 (ACTT-3) |
| NCT identifier | NCT04492475 |
| Phase | Phase 3 |
| Condition | COVID-19 |
| Allocation | Randomized |
| Design model | Parallel |
| Masking | Double |
| Primary purpose | Treatment |
| Enrollment | 969 |
| Primary endpoints | 4 registered endpoints |
| Primary endpoint type | Time-to-event |
| Primary hypothesis type | Superiority |
| Lead sponsor | National Institute of Allergy and Infectious Diseases (NIAID) |
| Sponsor type | NIH |
| Status | Completed |
2. Clinical Question
The central statistical question was whether participants assigned to remdesivir plus interferon beta-1a experienced a different time to recovery during Day 1 through Day 29 than participants assigned to remdesivir plus placebo.
Population
Participants enrolled in the phase 3 ACTT-3 trial with the condition COVID-19. The ClinicalTrials.gov record identifies the primary analysis population as the modified intention-to-treat population.
Intervention
Remdesivir plus interferon beta-1a.
Comparator
Remdesivir plus placebo.
Primary question
Does the addition of interferon beta-1a alter time to recovery compared with remdesivir plus placebo?
3. Trial Design
Remdesivir Plus Interferon Beta-1a
- Remdesivir
- Interferon beta-1a
- Randomized treatment assignment
Remdesivir Plus Placebo
- Remdesivir
- Placebo
- Randomized treatment assignment
The design matters statistically because randomization creates the framework for comparing outcomes between treatment assignments. Double masking is intended to reduce the influence of treatment knowledge on trial conduct and outcome assessment. The parallel structure means the two randomized groups are followed as distinct treatment groups rather than being exposed sequentially to different randomized treatments.
4. Endpoints
The registry lists four primary endpoints. All have the same Day 1 through Day 29 time frame and are based on time to recovery, with additional analyses by race, ethnicity, or sex.
| Registered primary endpoint | Time frame | Type |
|---|---|---|
| Time to Recovery for Participants With Baseline Ordinal Score 4, 5 and 6 | Day 1 through Day 29 | Time-to-event |
| Time to Recovery for Participants With Baseline Ordinal Score 4, 5 and 6 by Race | Day 1 through Day 29 | Time-to-event |
| Time to Recovery for Participants With Baseline Ordinal Score 4, 5 and 6 by Ethnicity | Day 1 through Day 29 | Time-to-event |
| Time to Recovery for Participants With Baseline Ordinal Score 4, 5 and 6 by Sex | Day 1 through Day 29 | Time-to-event |
Definition of recovery
The registry defines the day of recovery as the first day on which the subject satisfies one of three categories from the ordinal scale: 1) not hospitalized, with no limitations on activities; 2) not hospitalized, but with a new or increased limitation on activities and/or a new or increased requirement for home oxygen; or 3) hospitalized, not requiring supplemental oxygen and no longer requiring ongoing medical care.
5. Statistical Analysis Populations
| Population | Registry description | Role |
|---|---|---|
| Modified intention-to-treat (mITT) | Includes all participants who were randomized. Participants were classified by their randomized treatment assignment and their baseline ordinal score. | Primary time-to-event efficacy analyses |
| mITT with ethnicity reported | Includes all randomized participants for whom ethnicity was reported. | Ethnicity primary-endpoint analyses |
| Safety population | Includes all participants with available data post baseline, analyzed as treated. | Safety analyses |
This distinction between randomized efficacy analysis and treated safety analysis is important. In the mITT framework, treatment assignment remains defined by randomization. In the safety population, participants are analyzed according to treatment received, which is more directly connected to exposure-related adverse-event reporting.
6. Statistical Methodology
Log-rank test
The registry reports a log-rank test for the principal time-to-recovery comparison. A log-rank test compares the survival or event-time experience of two groups across the observed follow-up rather than comparing only a single time point.
For ACTT-3, the event is recovery. A participant who has not experienced the defined recovery event by the relevant end of follow-up contributes information without being treated as if recovery occurred.
Cox proportional-hazards effect measure
The registry reports the treatment effect as a Cox proportional hazard, normalized here as a hazard ratio. The hazard ratio is a relative measure of the instantaneous event rate represented by the fitted Cox model.
For a recovery endpoint, the direction requires care. Unlike an endpoint where the event is death or disease progression, an event of recovery is generally favorable. Therefore an HR below 1 for time to recovery indicates a lower estimated recovery hazard, not a lower mortality hazard.
Intention-to-treat principle
The registry-reported analysis text explicitly identifies the mITT population and states that participants were classified by their randomized treatment assignment. This preserves the treatment comparison defined by randomization and avoids redefining the primary efficacy comparison simply because treatment exposure changed.
Risk difference for safety
The secondary safety analyses use risk difference as the effect measure. A risk difference is an absolute difference in the proportion experiencing an event between the two compared groups.
The registry reports the risk difference in percentage-point units for the adverse-event analyses. Unlike a hazard ratio, an RD describes an absolute difference in observed proportions over the specified safety time frame.
7. Primary Result: Time to Recovery
The principal primary analysis compares remdesivir plus interferon beta-1a with remdesivir plus placebo among participants with baseline ordinal scores 4, 5 and 6. The time frame was Day 1 through Day 29, and the analysis population was the mITT population.
Hazard ratio for time to recovery
95% CI: 0.87–1.13 · P = 0.880
Effect measure: Cox proportional hazard · Analysis: Log Rank
| Feature | Reported result |
|---|---|
| Endpoint | Time to Recovery for Participants With Baseline Ordinal Score 4, 5 and 6 |
| Time frame | Day 1 through Day 29 |
| Comparison | Remdesivir Plus Interferon Beta-1a vs Remdesivir Plus Placebo |
| Analysis population | Modified intention-to-treat |
| Analysis method | Log-rank test |
| Effect measure | Cox proportional hazard / hazard ratio |
| Hazard ratio | 0.99 |
| 95% CI | 0.87–1.13 |
| P-value | 0.880 |
| Hypothesis | Superiority |
The estimated hazard ratio of 0.99 is very close to 1. Under the reported Cox model, the estimated instantaneous rate of achieving the defined recovery event was approximately the same in the two randomized groups.
The HR does not mean that 99% of participants recovered, nor does it mean that the groups had identical individual recovery times. It is a relative model-based comparison of event rates over the analyzed time-to-event framework.
The 95% CI of 0.87–1.13 describes uncertainty around the estimated hazard ratio. Because the interval includes 1, the data are compatible with a range of relative recovery hazards on either side of the null value.
The P = 0.880 value addresses evidence against the null hypothesis under the reported statistical test; it does not measure the size or clinical importance of an effect. A p-value should therefore be interpreted together with the hazard ratio and confidence interval rather than as a standalone measure of treatment effect.
Because the endpoint is recovery, an HR below 1 has a different substantive direction from an HR below 1 for death or disease progression. The proportional-hazards interpretation also depends on the Cox-model framework; the ClinicalTrials.gov record does not report a separate assessment of the proportional-hazards assumption.
8. Primary Endpoint Analyses by Race
The registry includes race-specific analyses of the same time-to-recovery endpoint. These analyses use the mITT population and the same randomized comparison. Four race-specific estimates are posted.
| Race subgroup | HR | 95% CI | P-value |
|---|---|---|---|
| Asian participants | 0.92 | 0.59–1.45 | Not reported |
| Black and African American participants | 0.92 | 0.66–1.27 | Not reported |
| White participants | 1.02 | 0.86–1.21 | Not reported |
| Race of Other participants | 0.84 | 0.59–1.19 | Not reported |
The race-specific hazard ratios range from 0.84 to 1.02, but the confidence intervals are relatively broad compared with the overall estimate. The intervals for all four reported race analyses include 1.
These estimates should be read as subgroup-specific descriptions rather than as proof that the treatment effect differs by race. A difference between subgroup estimates does not itself establish treatment-effect modification; a formal interaction analysis would be needed to make that claim.
The confidence intervals also emphasize precision. For example, the Asian-participant estimate of 0.92 has a 95% CI of 0.59–1.45, which spans a comparatively wide range of possible hazard ratios. The ClinicalTrials.gov record does not provide p-values or an interaction test for these race analyses.
9. Primary Endpoint Analyses by Ethnicity
Two ethnicity-specific analyses are posted for the same Day 1 through Day 29 time-to-recovery endpoint. The ethnicity analysis population includes all randomized participants for whom ethnicity was reported.
| Ethnicity subgroup | HR | 95% CI | P-value |
|---|---|---|---|
| Not Hispanic or Latino participants | 1.02 | 0.86–1.19 | Not reported |
| Hispanic or Latino participants | 0.83 | 0.65–1.05 | Not reported |
The reported ethnicity-specific estimates are 1.02 for participants who were not Hispanic or Latino and 0.83 for participants who were Hispanic or Latino. Their 95% confidence intervals are 0.86–1.19 and 0.65–1.05, respectively.
These estimates describe the randomized comparison within the reported ethnicity categories. They do not establish that ethnicity changes the treatment effect. The ClinicalTrials.gov record contains no formal interaction p-value, and no subgroup p-values are reported.
The distinction between an estimate and its precision is important: the point estimate of 0.83 alone should not be interpreted as a definitive treatment-effect difference when its confidence interval extends from 0.65 to 1.05.
10. Primary Endpoint Analyses by Sex
The registry also posts two sex-specific analyses of time to recovery from Day 1 through Day 29.
| Sex subgroup | HR | 95% CI | P-value |
|---|---|---|---|
| Male participants | 0.93 | 0.78–1.10 | Not reported |
| Female participants | 1.05 | 0.86–1.29 | Not reported |
The male-participant estimate is 0.93, while the female-participant estimate is 1.05. Their 95% confidence intervals are 0.78–1.10 and 0.86–1.29.
The two point estimates lie on opposite sides of 1, but that observation alone is not evidence of a sex-by-treatment interaction. The confidence intervals overlap the null value, and the ClinicalTrials.gov record does not report a formal interaction test.
Subgroup analyses are particularly useful for examining consistency and generating questions, but the precision and multiplicity of subgroup comparisons must be considered before treating individual subgroup estimates as independent confirmatory findings.
11. Secondary Time-to-Event Results
The registry also posts several secondary time-to-event analyses. These use the mITT population and report Cox proportional-hazard effect measures with two-sided 95% confidence intervals. No p-values are posted on ClinicalTrials.gov for these analyses in the ClinicalTrials.gov record.
| Secondary endpoint | Comparison | HR | 95% CI |
|---|---|---|---|
| Time to an Improvement of One Category Using an Ordinal Scale | Baseline ordinal score 4 and 5 | 1.04 | 0.90–1.19 |
| Time to an Improvement of One Category Using an Ordinal Scale | Baseline ordinal score 6 | 0.37 | 0.21–0.66 |
| Time to an Improvement of Two Categories Using an Ordinal Scale | Baseline ordinal score 4 and 5 | 1.04 | 0.91–1.19 |
| Time to an Improvement of Two Categories Using an Ordinal Scale | Baseline ordinal score 6 | 0.44 | 0.24–0.82 |
| Time to Discharge or to a National Early Warning Score (NEWS) of <= 2 and Maintained for 24 Hours, Whichever Occurs First | Baseline ordinal score 4 and 5 | 1.08 | 0.93–1.26 |
| Time to Discharge or to a National Early Warning Score (NEWS) of <= 2 and Maintained for 24 Hours, Whichever Occurs First | Baseline ordinal score 6 | 0.39 | 0.21–0.72 |
| Time to Recovery for Patients With a Baseline Ordinal Score of 4 and 5 | Baseline ordinal score 4 and 5 | 1.04 | 0.90–1.19 |
The pattern is notable because the analyses restricted to baseline ordinal score 6 have hazard ratios below 1 for improvement by one category, improvement by two categories, and the discharge/NEWS endpoint. By contrast, the corresponding estimates for baseline ordinal scores 4 and 5 are close to 1. These are different endpoints and populations, so they should not be collapsed into a single treatment-effect estimate.
12. Safety Results
The ClinicalTrials.gov record reports secondary safety analyses for grade 3 and 4 clinical and/or laboratory adverse events and for serious adverse events. These analyses use the safety population, defined as participants with available post-baseline data and analyzed as treated.
Grade 3 and 4 clinical and/or laboratory adverse events
| Baseline group | Comparison | Risk difference | 95% CI |
|---|---|---|---|
| Ordinal score 4 and 5 | Remdesivir Plus Interferon Beta-1a vs Remdesivir Plus Placebo | 7.2 | 0.9–13.4 |
| Ordinal score 6 | Remdesivir Plus Interferon Beta-1a vs Remdesivir Plus Placebo | 23.6 | 0.0–43.9 |
Serious adverse events
| Baseline group | Comparison | Risk difference | 95% CI |
|---|---|---|---|
| Ordinal score 4 and 5 | Remdesivir Plus Interferon Beta-1a vs Remdesivir Plus Placebo | 1.4 | -3.2–6.0 |
| Ordinal score 6 | Remdesivir Plus Interferon Beta-1a vs Remdesivir Plus Placebo | 35.8 | 12.3–54.2 |
The ClinicalTrials.gov record also provide affected/at-risk counts for serious adverse events by arm:
| Baseline group | Remdesivir Plus Interferon Beta-1a | Remdesivir Plus Placebo |
|---|---|---|
| Ordinal score 4 and 5 | 65/442 | 58/435 |
| Ordinal score 6 | 21/32 | 8/31 |
The risk-difference framework provides an absolute comparison rather than a time-to-event comparison. For example, the reported serious-adverse-event RD of 35.8 for baseline ordinal score 6 has a 95% CI of 12.3–54.2. The ClinicalTrials.gov record therefore describe a substantial positive difference in the reported event proportions for this comparison, with the entire reported confidence interval above 0.
For baseline ordinal scores 4 and 5, the reported serious-adverse-event RD is 1.4 with a 95% CI of -3.2–6.0. That interval includes 0, illustrating why the confidence interval is essential when interpreting an absolute risk difference.
The safety results should not be combined with efficacy into a single numerical "net benefit" measure. Efficacy and safety endpoints describe different dimensions of the randomized treatment comparison.
13. Statistical Methods Explained
Why use a time-to-event endpoint for recovery?
A binary recovery outcome would record only whether recovery occurred by a selected cutoff. A time-to-event endpoint retains information about when recovery occurred during the Day 1 through Day 29 window. That distinction can make timing clinically and statistically important.
What does an HR of 0.99 mean when the event is recovery?
An HR of 0.99 is close to 1, so the fitted model estimates nearly identical instantaneous recovery hazards between the randomized treatment groups. It should not be translated into a statement that "1% fewer patients recovered." Hazard ratios and absolute recovery proportions are different quantities.
Why is the interpretation of an HR below 1 different here?
For an endpoint such as death, a hazard ratio below 1 generally corresponds to a lower event rate, which is favorable. In ACTT-3, the event is recovery. Therefore an HR below 1 means a lower estimated instantaneous rate of reaching recovery under the model. The meaning of the numerical direction depends on what event is being modeled.
What does the 95% confidence interval tell us?
The confidence interval describes statistical uncertainty around the estimated effect. For the main analysis, the estimate is 0.99 and the 95% CI is 0.87–1.13. The interval includes the null value of 1, so the reported estimate is not precise enough to exclude values on either side of the null under this confidence-interval framework.
Why does the p-value not measure effect size?
The primary p-value is 0.880. A p-value describes how compatible the observed data are with the specified null hypothesis under the statistical test. It does not tell us how large the treatment effect is. The HR and its confidence interval are the quantities that describe the estimated relative effect and its precision.
Why should the race, ethnicity, and sex analyses not be treated as separate trials?
These analyses are subgroup analyses within the randomized trial. The point estimates can differ between subgroups simply because of sampling variation. A formal claim that the treatment effect differs by race, ethnicity, or sex requires an interaction or heterogeneity analysis rather than comparing the subgroup estimates informally.
Why is the analysis population important?
The primary time-to-event analyses use the mITT population, with participants classified according to randomized treatment assignment. The safety analyses instead use participants with available post-baseline data and analyze them as treated. Changing the analysis population changes the estimand and therefore changes what the resulting statistic describes.
14. Confidence Intervals, Null Values, and Precision
ACTT-3 provides a useful example of why effect estimates should be read together with their confidence intervals.
| Analysis | Estimate | 95% CI | Null value |
|---|---|---|---|
| Primary time to recovery | HR 0.99 | 0.87–1.13 | 1 |
| Asian participants | HR 0.92 | 0.59–1.45 | 1 |
| Black and African American participants | HR 0.92 | 0.66–1.27 | 1 |
| White participants | HR 1.02 | 0.86–1.21 | 1 |
| Hispanic or Latino participants | HR 0.83 | 0.65–1.05 | 1 |
| Male participants | HR 0.93 | 0.78–1.10 | 1 |
| Female participants | HR 1.05 | 0.86–1.29 | 1 |
For hazard ratios, the null value is 1. For risk differences, the null value is 0. This distinction is basic but important: an interval that crosses 1 for a hazard ratio is interpreted differently from an interval that crosses 0 for a risk difference.
Relative effect
A hazard ratio compares event rates within a time-to-event model. It is not a percentage of patients who benefited.
Absolute effect
A risk difference compares event proportions directly and expresses their absolute separation in the reported percentage-point scale.
Precision
A narrow confidence interval indicates greater statistical precision than a wide interval, all else being equal.
Statistical significance
A confidence interval crossing its null value and a large p-value are evidence considerations, not measurements of clinical importance.
15. Reading the Primary Analysis Correctly
The main result can be reduced to three related quantities:
ACTT-3 primary statistical result
95% CI 0.87–1.13 · P = 0.880
These numbers answer different questions:
- HR 0.99: What relative treatment effect was estimated by the reported Cox model?
- 95% CI 0.87–1.13: How much statistical uncertainty surrounds that estimate?
- P = 0.880: How much evidence against the specified null hypothesis was produced by the reported test?
A statistically careful interpretation does not replace these three quantities with a single label. In particular, the p-value should not be treated as a measure of treatment magnitude, and the hazard ratio should not be interpreted as an absolute probability of recovery.
16. Subgroup Analysis: What Can and Cannot Be Concluded
The ACTT-3 registry data provide nine primary-endpoint analyses: one overall analysis, four race-specific analyses, two ethnicity-specific analyses, and two sex-specific analyses.
| Dimension | Number of reported analyses | Range of HR estimates |
|---|---|---|
| Overall | 1 | 0.99 |
| Race | 4 | 0.84–1.02 |
| Ethnicity | 2 | 0.83–1.02 |
| Sex | 2 | 0.93–1.05 |
There are two separate statistical questions here. The first is whether the treatment comparison within a subgroup differs from the null value. The second, which is often more clinically interesting, is whether the treatment effect itself differs between subgroups. The second question requires an interaction or heterogeneity analysis.
17. Ordinal Outcomes and Baseline Severity
Several secondary endpoints use an ordinal clinical scale and distinguish participants by baseline ordinal score. This is statistically informative because the same numerical treatment assignment can be associated with different event-time estimates in different baseline severity groups.
| Baseline group | Endpoint | HR | 95% CI |
|---|---|---|---|
| Ordinal score 4 and 5 | One-category improvement | 1.04 | 0.90–1.19 |
| Ordinal score 6 | One-category improvement | 0.37 | 0.21–0.66 |
| Ordinal score 4 and 5 | Two-category improvement | 1.04 | 0.91–1.19 |
| Ordinal score 6 | Two-category improvement | 0.44 | 0.24–0.82 |
| Ordinal score 4 and 5 | Discharge or NEWS <= 2 maintained for 24 hours | 1.08 | 0.93–1.26 |
| Ordinal score 6 | Discharge or NEWS <= 2 maintained for 24 hours | 0.39 | 0.21–0.72 |
The contrast between baseline ordinal score 4 and 5 versus baseline ordinal score 6 is therefore a major part of the statistical story contained in the posted secondary analyses. However, these are secondary endpoints, and the ClinicalTrials.gov record does not provide formal multiplicity-adjusted p-values for them.
18. Multiplicity and Multiple Analyses
The registry reports four primary endpoints and a total of 20 statistical analyses, including nine primary-endpoint analyses and multiple secondary analyses. That breadth matters when interpreting individual estimates.
Primary endpoints
Four registered primary endpoints are reported, all involving time to recovery and analyses by race, ethnicity, or sex.
Primary analyses
Nine primary-endpoint analyses have posted statistical estimates and confidence intervals.
Secondary analyses
The posted secondary results include ordinal improvement, discharge/NEWS, recovery, and safety outcomes.
Interpretive caution
The ClinicalTrials.gov record does not describe a multiplicity-adjustment procedure for the posted secondary and subgroup estimates.
Multiplicity does not make an estimate meaningless. It changes the evidentiary context in which multiple estimates should be interpreted. When many endpoints and subgroup analyses are examined, the probability of observing an apparently notable result somewhere in the collection increases unless the statistical design explicitly controls that multiplicity.
19. Kaplan-Meier Estimation and Censoring
Kaplan-Meier estimation is a standard way to display and estimate time-to-event distributions. The registry-reported ACTT-3 registry data identify time-to-event endpoints and a log-rank comparison, but they do not explicitly report a Kaplan-Meier method in the normalized statistical-method field.
Here, di represents events at an event time and ni represents participants at risk immediately before that time. The method allows participants with incomplete event-time observation to contribute information up to their censoring time.
The important conceptual point is that time-to-event analysis does not require every participant to experience the event during the observation period. This is one reason time-to-recovery analysis differs from a simple comparison of the proportion recovered at one fixed time point.
20. Why the Log-Rank Test and Cox Model Work Together
The ACTT-3 primary analysis illustrates two related but distinct statistical functions.
| Method | Primary role | ACTT-3 use |
|---|---|---|
| Log-rank test | Compare event-time experience between groups | Reported primary analysis method |
| Cox proportional-hazards model | Express the relative event rate as a hazard ratio | Reported effect measure |
The log-rank test and hazard ratio should not be treated as interchangeable. One is a hypothesis-testing framework for comparing time-to-event experience; the other is an effect measure derived from a proportional-hazards model. Reporting both provides complementary information.
For ACTT-3, the reported combination of a log-rank analysis with a Cox proportional-hazard effect measure means that the statistical story has both a comparison component and an effect-estimation component. The p-value of 0.880 belongs to the reported hypothesis-testing result, while the HR of 0.99 and its 95% CI of 0.87–1.13 describe the estimated relative effect and its precision.
21. Important Limitations and Interpretation Issues
- Endpoint direction: the principal event is recovery. Hazard ratios below 1 therefore cannot automatically be interpreted using the language used for adverse events such as death or progression.
- Proportional-hazards assumption: the reported Cox effect measure is model-based. The ClinicalTrials.gov record does not report a separate assessment of the proportional-hazards assumption.
- Subgroup precision: race, ethnicity, and sex estimates have their own confidence intervals and should not be treated as equally precise simply because they come from the same trial.
- Interaction testing: differences between subgroup point estimates do not establish treatment-effect heterogeneity without an appropriate interaction or heterogeneity analysis.
- Multiple analyses: the registry contains many primary and secondary analyses. The ClinicalTrials.gov record does not specify a multiplicity-adjustment procedure for the posted secondary and subgroup results.
- Analysis populations: primary efficacy analyses use the mITT population, whereas safety analyses use participants with available post-baseline data analyzed as treated.
- No reconstructed survival curves: the ClinicalTrials.gov record contains summary estimates rather than the underlying individual event and censoring times needed to independently reconstruct a Kaplan-Meier curve.
- Safety interpretation: risk differences describe absolute event-rate differences and should not be interpreted as time-to-event hazard ratios.
22. Why This Trial Matters Statistically
ACTT-3 is a useful teaching example because it combines randomized treatment assignment with a clinically meaningful time-to-event endpoint, subgroup analyses, ordinal clinical outcomes, and absolute safety comparisons.
| Concept | How it appears in ACTT-3 |
|---|---|
| Randomization | Randomized parallel-group phase 3 design |
| Blinding | Double masking |
| Intention-to-treat analysis | Primary analyses use the modified intention-to-treat population and randomized treatment assignment |
| Time-to-event endpoint | Time to recovery during Day 1 through Day 29 |
| Log-rank test | Reported method for the principal primary comparison |
| Hazard ratio | Cox proportional-hazard effect measure |
| Confidence interval | 95% two-sided intervals accompany the reported effect estimates |
| Subgroup analysis | Primary endpoint analyses by race, ethnicity, and sex |
| Ordinal outcomes | One- and two-category improvement analyses by baseline ordinal score |
| Risk difference | Secondary safety analyses for grade 3 and 4 AEs and serious AEs |
| Safety population | Participants with available post-baseline data, analyzed as treated |
23. Overall Statistical Interpretation
The central reported ACTT-3 result is a hazard ratio of 0.99 for time to recovery among participants with baseline ordinal scores 4, 5 and 6, with a two-sided 95% CI of 0.87–1.13 and P = 0.880. Statistically, this is an estimate close to the null value of 1, with a confidence interval that spans the null.
The subgroup analyses provide additional descriptive estimates rather than a separate set of independently randomized treatment comparisons. Race-specific HRs range from 0.84 to 1.02; ethnicity-specific HRs are 1.02 and 0.83; and sex-specific HRs are 0.93 and 1.05. Their confidence intervals should be considered alongside the point estimates.
The secondary analyses introduce a different pattern. For participants with baseline ordinal score 6, the reported hazard ratios are below 1 for one-category improvement, two-category improvement, and the discharge/NEWS endpoint. These estimates are accompanied by 95% confidence intervals of 0.21–0.66, 0.24–0.82, and 0.21–0.72, respectively. The corresponding baseline ordinal score 4 and 5 analyses are much closer to 1. These findings should be kept in their specific endpoint and population contexts rather than summarized as a single global effect.
The safety analyses use risk differences rather than hazard ratios. For baseline ordinal score 4 and 5, the serious-adverse-event RD is 1.4 with a 95% CI of -3.2–6.0. For baseline ordinal score 6, the corresponding RD is 35.8 with a 95% CI of 12.3–54.2. These absolute measures answer a different question from the time-to-recovery analyses.
24. Statistical Concepts in This Trial
Learn more about the methods used in this trial:
25. Related Statistical Calculators
26. Sources
- ClinicalTrials.gov: NCT04492475 — Adaptive COVID-19 Treatment Trial 3 (ACTT-3).
- PubMed: PMID 38618926.
- PubMed: PMID 36442063.
- PubMed: PMID 34672949.
- PubMed: PMID 34473343.
- PubMed: PMID 33148977.
Continue with the statistical methods
Explore the broader methods used to understand randomized clinical trials, time-to-event endpoints, effect measures, and statistical uncertainty.
27. Record Summary
ACTT-3 provides a compact example of how a randomized clinical trial can combine a primary time-to-event endpoint with subgroup analyses and secondary ordinal and safety outcomes. The main analysis used a modified intention-to-treat population, a log-rank comparison, and a Cox proportional-hazard effect measure. The principal reported estimate was HR 0.99 with a two-sided 95% CI of 0.87–1.13 and P = 0.880.
The statistical interpretation should remain closely tied to the endpoint definition. Because recovery is the event, an HR below 1 represents a lower estimated recovery hazard rather than the lower hazard of an adverse event. The race, ethnicity, and sex analyses provide additional subgroup estimates, while the secondary ordinal outcomes show different estimates according to baseline ordinal score. Safety analyses use risk differences and a separate treated safety population.