Adjunctive Acetylsalicylic Acid and Ibuprofen for Tuberculosis: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Adjunctive Acetylsalicylic Acid and Ibuprofen for Tuberculosis (NCT04575519), a randomized phase 2 study. The primary outcome is Time to ≥ 67% Sustained Reduction in the TB Score.

2. Clinical Question

The trial record describes a phase 2b, randomized, double-blind, placebo-controlled study of two repurposed drugs added to standard WHO-recommended tuberculosis treatment. Its stated purpose was to assess efficacy and safety in drug-sensitive and multidrug-resistant tuberculosis. The three treatment groups were control, SoC TB plus ASA, and SoC TB plus IBU; the control group also received SoC TB. The registry lists tuberculosis infection among the conditions as well as pulmonary and multidrug-resistant tuberculosis. It does not report further participant characteristics in the outcome information summarized for the primary endpoint.

3. Trial Design

The registry identifies this as a phase 2 randomized trial with a parallel-group model and quadruple masking. It lists an overall enrollment of 426 and a terminated status. The recorded study start was 2021-03-04, and primary completion was 2023-12-19. The primary outcome description separately states that 221 participants were enrolled for that outcome population; 204 had at least one post-baseline assessment, while 17 discontinued after baseline without a post-baseline assessment. The registry does not explain the relationship between the overall enrollment figure and the primary-outcome population count.

All three groups received standard-of-care tuberculosis treatment. The control group received placebo, while the two intervention groups received ASA or IBU in addition to standard treatment. Each study drug or placebo was administered twice daily during the first 4 weeks and once daily for an additional 4 weeks. The arm descriptions do not state the dose of placebo or provide further dosing details for standard tuberculosis treatment. The registry describes the comparator as the standard WHO-recommended regimen.

The primary endpoint was time to sustained reduction in TB Score, with the analysis timeframe described as 24 weeks of treatment. The posted primary-outcome results include group medians and 95% confidence intervals. The sponsor also reports Cox-regression hazard ratios for control versus ASA and control versus IBU. Secondary outcomes include stable culture conversion, clinical signs and symptoms, lung function, the activity component of the RTBES, and health-related quality of life. Five secondary outcomes are listed as posted. Nine outcome measures and 24 analyses are recorded overall.

The registry record does not report the trial’s original sample-size justification, the planned interim analyses, or a fuller statistical analysis plan. It also does not report additional details of the randomization procedure or the masking roles. The trial’s terminated status is recorded, but a reason for termination is 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: 205 were excluded mainly due to: lack of microbiological TB confirmation; HIV-related exclusion criteria; major comorbid conditions or investigator's decision; prior TB treatment; ALT/AST above threshold; body weight, haemoglobin or neutrophil below threshold; alcohol use; age outside the range; allergy to NSAIDs; use of antacids; proton pump inhibitors or immune-modulating therapy; multiple exclusion criteria.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Of the 221 participants enrolled, 204 participants had at least one post-baseline outcome assessment and are included in the outcome measure. 17 participants discontinued after baseline and had no post-baseline assessments. All collected data for the pre-specified outcome are reported in the outcome measure.

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: All participants randomized

6. Primary Endpoint

The registry lists the primary outcome as Time to ≥ 67% Sustained Reduction in the TB Score, measured over 24 weeks of TB treatment.

The primary endpoint is the time, in weeks, to a sustained 67% reduction in TB Score during 24 weeks of tuberculosis treatment. The score is described as ranging from a minimum of 0 to a maximum of 13. The registry states that TB Score has been described as useful for monitoring response to tuberculosis treatment regardless of HIV status. This makes the endpoint a measure of the time course of a clinical score rather than a single score recorded at one fixed visit.

A time-to-event endpoint records how long it takes for a specified event to occur. In general, it can use information from participants who have not yet reached the event during the observation period, provided the analysis accounts for the observation process. The registry does not explain how censoring was handled for this outcome. It reports the timeframe as 24 weeks, while the listed treatment course for the study drugs spans the first 4 weeks followed by an additional 4 weeks.

The endpoint description contains an ambiguity: it says that higher TB Scores mean a “better or worse” outcome, without making the direction clear. The definition of the event is a sustained reduction, but the registry does not further specify the sustained-measurement rule or clarify the score’s direction in that sentence. These details matter when interpreting which event is represented by a higher hazard ratio. The posted summaries therefore support describing the recorded times and reported comparisons, but not assigning an unambiguous favorable direction to the hazard ratio solely from the endpoint wording.

7. Results Posted in the Registry

• Control Group vs SoC TB + ASA Group: hazard ratio 1.16 (95% CI 0.81–1.67), reported p = 0.419 (as reported in the registry).
• Control Group vs SoC TB + IBU Group: hazard ratio 1.25 (95% CI 0.87–1.79), reported p = 0.233 (as reported in the registry).

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is a time-to-event measure, and the sponsor used Cox regression for the two reported comparisons. The method estimates a hazard ratio: a comparison of the event rate over time between the groups, subject to the model’s assumptions. It does not directly compare the medians by subtracting one group’s median from another. The medians and their confidence intervals are useful descriptive summaries, while the hazard ratios and their confidence intervals describe the sponsor’s modeled comparisons.

What does a median time mean?

In general, a median time is the time by which half of the relevant event-time distribution has reached the event, under the way the analysis defines and estimates that distribution. The registry gives median times in weeks for the control, ASA, and IBU groups. A median does not describe every participant’s time, and it does not show the shape of the full time distribution. The confidence interval around a median expresses uncertainty about its estimated location.

For this endpoint, the event is described as reaching a sustained 67% reduction in TB Score. The registry does not give the detailed rule used to determine that a reduction was sustained, nor does it explain how participants who did not reach the event within the observation period were handled. Those details can affect time-to-event estimation and interpretation. The record identifies the timeframe as 24 weeks of treatment but does not describe censoring procedures.

How should the hazard ratios be read?

In general, a hazard ratio compares the instantaneous rate of an event between groups among participants still under observation and at risk of the event. A value at the no-difference point corresponds to equal event rates under the model. The direction of interpretation depends on which group is in the numerator and how the event is defined. The registry reports the comparisons as control versus ASA and control versus IBU, with hazard ratios of 1.161 and 1.245, respectively. The endpoint wording is not clear enough to attach a favorable or unfavorable meaning to a value above the no-difference point with confidence.

The Cox model is a regression approach for time-to-event data. In general, its standard interpretation relies on the relative hazard being adequately represented over follow-up; the registry does not report whether this assumption was assessed or what diagnostics were used. The record names Cox regression but does not supply further model specifications, covariate adjustments, stratification details, or handling of ties. Such details are not reported in the registry record.

What do the confidence intervals and p-values add?

In general, a confidence interval gives a range of estimates compatible with the data and analysis under its statistical assumptions. A wider interval indicates less precision than a narrower interval. The reported 95% intervals for both hazard ratios include the no-difference value, and each reported p-value is 0.419 or 0.233. These summaries do not demonstrate a clear separation from no difference in the sponsor’s superiority comparisons. They also do not prove that the groups are identical: the intervals remain compatible with more than one possible effect size and direction.

A p-value is a measure of how unusual data at least as incompatible with a specified null model would be if that model and the analysis assumptions held. It is not the probability that the null hypothesis is true, and it does not measure the clinical importance of an estimate. The registry’s reported p-values should therefore be read alongside the estimates, confidence intervals, endpoint definition, and analysis population, rather than in isolation.

Why can time-to-event methods matter?

In general, time-to-event methods are useful when participants reach an event at different times and some observations may be incomplete by the end of follow-up. They can account for the observed time under follow-up without treating every participant as if an event occurred at the same fixed visit. This benefit depends on appropriate event definitions and censoring information. The registry does not report enough detail to assess the specific censoring approach for the primary outcome.

The group medians are 5.0, 4.9, and 4.1 weeks for control, ASA, and IBU, respectively. The sponsor’s hazard ratios are separate, model-based summaries. Neither set of estimates should be treated as a direct calculation from the other. The registry does not report a separate recalculated hazard ratio; the reported Cox analyses are the sponsor’s analyses used for interpretation.

What is and is not reported about the analysis?

The record names a superiority analysis and Cox regression for each comparison. It reports the confidence level for the hazard-ratio intervals and the associated p-values. It does not report the original sample-size justification, interim analyses, a full statistical analysis plan, multiplicity adjustment, or the exact analysis population for the Cox models. These omissions limit assessment of whether analysis decisions were prespecified and how multiple outcomes and comparisons were handled.

In general, over-dispersion is relevant when count data vary more than a model assumes, which can make standard errors too small if ignored. That concept is not central to the posted primary endpoint, which is time-to-event, and the registry does not report a count-model analysis for it. The appropriate statistical interpretation should follow the reported Cox model and the stated limitations of the endpoint and analysis details, rather than assume methods that are not recorded.

10. Confidence Intervals and Precision

The sponsor’s hazard-ratio estimates are 1.161 for control versus ASA and 1.245 for control versus IBU. Their 95% confidence intervals are 0.809 to 1.666 and 0.868 to 1.786, respectively. Each interval includes the no-difference value for a hazard ratio. The estimates are therefore not precise enough to distinguish a clear difference from no difference based on these intervals alone. They also leave room for effects in either direction, depending on the event coding and the model’s interpretation.

The median-time estimates also have uncertainty. The control median is 5.0 weeks, with an interval from 4.0 to 7.1; the ASA median is 4.9 weeks, with an interval from 3.0 to 6.0; and the IBU median is 4.1 weeks, with an interval from 3.1 to 6.7. The intervals overlap. Comparing medians and their intervals is not a substitute for the sponsor’s modeled comparison, and interval overlap alone is not a formal test of a difference.

In general, a confidence interval represents uncertainty under the chosen model and its assumptions; it does not account automatically for every source of uncertainty, such as missing outcome data, measurement issues, or unreported analysis choices. The registry reports that 204 participants had a post-baseline assessment for the primary outcome, but does not explain how missing post-baseline data entered the Cox analysis. That missing detail affects how fully the reported precision can be assessed.

The estimates are best read as uncertain rather than as evidence of equivalence. No equivalence margin or non-inferiority framework is reported. The range of values in each interval means the results do not narrowly pinpoint a single effect size, and the ambiguity in the endpoint wording further constrains directional interpretation.

11. 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 illustrations based on the observed hazard-ratio effect, not the original trial’s design calculation. For these time-to-event comparisons, every displayed figure is a total number of events, not participants per arm. The planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, a normal approximation, and detection of the stated fraction of the observed effect. The trial’s own original design assumptions are not reported in the registry record.

The 80% power column means the illustrative total event count associated with an 80% chance of detecting the specified effect under those assumptions, if the assumed effect and model conditions hold. The 90% power column represents a higher target chance of detecting that effect and therefore generally requires more events. These are planning targets, not estimates of what happened during the trial. The figures are expressed as total events because the analysis is time-to-event; they should not be read as participants per arm.

The rows describe planning for the full observed effect and smaller fractions of that observed effect. As the effect to detect becomes smaller, more events are needed to distinguish it from no difference under the same assumptions. The curve communicates this same general relationship between the effect size being targeted and the required event count. It does not replace the stated assumptions or establish how many participants would have been needed in practice, since event occurrence and follow-up also determine the total event count.

This is not observed power. The calculations are planning illustrations derived from the observed effect and do not describe the trial’s achieved probability of detecting an effect. The registry does not report the original sample-size rationale, so these figures should not be mistaken for the planned enrollment target or the design basis used by the investigators.

12. 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

d is the total number of events needed (Schoenfeld's formula) with 1:1 allocation and proportional hazards.

Worked calculation for this trial

1. Hazard ratio HR = 1.161, so ln(HR) = 0.1493.
2. d = 4 × (1.96 + 0.842)² / [ln(1.161)]² = 1,408.8, rounded up to 1,409 events in total 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
hr <- 1.161                              # observed hazard ratio
events_needed <- function(power, frac = 1) ceiling(round(4 * (z_a + qnorm(power))^2 / log(hr^frac)^2, 6))   # Schoenfeld, 1:1 allocation
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: events = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(events_needed(0.80, f), big.mark = ","), format(events_needed(0.90, f), big.mark = ",")))

# Simulation: given d total events under proportional hazards, events in the treatment arm are Binomial(d, hr / (1 + hr)).
# The score (log-rank type) statistic is (D1 - d / 2) / sqrt(d / 4).
set.seed(4575519)
d    <- events_needed(0.80)
reps <- 20000
D1 <- rbinom(reps, d, hr / (1 + hr))
z  <- (D1 - d / 2) / sqrt(d / 4)
cat(sprintf("Simulated power with %s events: %.3f (%d replicates)\n", format(d, big.mark = ","), mean(abs(z) > z_a), reps))

Output from running the code

100% of observed effect: events = 1,409 (80% power), 1,887 (90% power)
 75% of observed effect: events = 2,505 (80% power), 3,353 (90% power)
 50% of observed effect: events = 5,636 (80% power), 7,545 (90% power)
Simulated power with 1,409 events: 0.798 (20000 replicates)

The simulation uses the fact that, with d events in total and proportional hazards, the number of events in the treatment arm is binomial. It is an approximation that conditions on the total number of events, and it should land close to the target power.

13. Analyses Reported by the Sponsor

The sponsor’s own primary-outcome comparisons are reported as Cox-regression hazard ratios. For control versus ASA, the reported estimate is 1.161, with a 95% confidence interval from 0.809 to 1.666. For control versus IBU, it is 1.245, with a 95% confidence interval from 0.868 to 1.786. The corresponding reported p-values are 0.419 and 0.233. These are the analyses to use when describing the sponsor’s inferential results.

The planning illustrations are not an alternative sponsor analysis of the trial outcomes. They use the observed effects to estimate event counts under stated planning assumptions, and should be kept separate from the posted treatment comparisons. No recalculated hazard-ratio result is reported in the registry information summarized for this analysis. The registry record does not flag a discrepancy between the sponsor’s reported result and a recalculation, so there is no conflicting recalculated estimate to substitute.

The sponsor’s reported hazard ratios should be interpreted with their confidence intervals and the endpoint definition. The event wording is not fully clear about score direction and sustained reduction, so a hazard ratio above the no-difference value should not be assigned a favorable or unfavorable meaning without that clarification. The analyses are reported as superiority comparisons; the record does not report an equivalence or non-inferiority analysis.

14. Multiplicity, Missing Data and Analysis Populations

The registry lists nine outcome measures and 24 analyses overall. It identifies one primary outcome and lists five secondary outcomes: time to stable culture conversion at Week 8 and Week 16, improvement or resolution of clinical signs and symptoms, improvement of lung function, reduction of the activity component of the RTBES, and improvement of health-related quality of life. The availability of multiple outcomes and analyses raises the general issue of multiplicity: when many statistical comparisons are made, the chance of at least one apparently notable result can increase.

The registry record does not report whether the investigators adjusted for multiple comparisons, defined a hierarchy among secondary outcomes, or used another multiplicity strategy. It also does not report interim analyses or the broader prespecified analysis plan. Without these details, the family of tests and the intended interpretation of secondary findings cannot be fully assessed. The number of listed analyses alone does not establish whether multiplicity was handled.

For the primary outcome, the registry states that 221 participants were enrolled, 204 had at least one post-baseline assessment, and 17 discontinued after baseline without a post-baseline assessment. It says all collected data for the prespecified outcome are reported. However, the record does not explain whether the Cox analysis used only participants with outcome assessments, how incomplete follow-up was handled, or what assumptions were made for missing data. The missing-data method is not reported in the registry record.

The record also does not specify the complete analysis population for the hazard-ratio comparisons, whether analyses followed an intention-to-treat principle, or whether any per-protocol population was used. These are important distinctions: the population included in an analysis can affect both the estimate and its interpretation. The available outcome description identifies participants with post-baseline assessments, but does not establish that this was the analysis population for every reported comparison.

These gaps do not invalidate the reported estimates; they limit the ability to judge their robustness and how they fit within the trial’s complete analysis plan. The reported endpoint results should therefore be interpreted alongside the explicit information about outcome participation and the absence of registry entries on multiplicity, missing-data procedures, and analysis populations.

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 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: toxic drug-induced hepatitis (4.1%), death (2.7%), acute peritonitis (1.4%), hydropneumothorax (1.4%), haemoptysis (1.4%).

The registry reports serious adverse events for 73 participants at risk in the control group, 74 in the ASA group, and 74 in the IBU group. The numbers affected by serious adverse events were 10, 8, and 4, respectively. Other adverse events affected 17 participants in the control group, 19 in the ASA group, and 12 in the IBU group. Recorded deaths were 1 in control, 0 in ASA, and 2 in IBU.

These are descriptive counts. The registry information does not provide a statistical comparison of safety outcomes, exposure-adjusted rates, or a detailed account of event severity beyond the serious-event category. The figures should not be read as evidence that one regimen is safer or less safe than another without appropriate comparative analyses and context about follow-up and exposure.

The listed serious-event terms include toxic drug-induced hepatitis at 4.1%, death at 2.7%, acute peritonitis at 1.4%, hydropneumothorax at 1.4%, haemoptysis at 1.4%, and arm fracture at 1.4%. The record does not specify in this listing which treatment groups contributed each term, so these percentages should not be attributed to a particular arm. The death counts by group are reported separately above.

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

The posted results describe the time to a sustained reduction in TB Score and provide the sponsor’s modeled comparisons of the control group with each adjunct-treatment group. The medians are 5.0 weeks for control, 4.9 weeks for ASA, and 4.1 weeks for IBU. The hazard-ratio confidence intervals include the no-difference value, and the reported p-values are 0.419 and 0.233. Together, these results do not establish a clear difference in the sponsor’s reported superiority analyses.

That conclusion should not be turned into a claim that the groups are equivalent or that an adjunct does or does not work. Equivalence would require an appropriate design and a prespecified margin, neither of which is reported. Failure to establish a clear difference is also not proof that no meaningful difference exists. The confidence intervals remain compatible with a range of effect sizes, and the primary endpoint description does not clearly state the direction of the score’s interpretation.

The registry lists a trial enrollment of 426, but the primary-outcome description reports 221 enrolled participants, including 204 with at least one post-baseline assessment. These counts refer to different registry entries and the record does not explain their relationship. Missing post-baseline outcomes and the absence of detail on the Cox analysis population make it harder to assess how representative the primary-outcome results are of all enrolled participants.

Safety counts are also descriptive rather than definitive comparative evidence. The groups have recorded counts for serious and other adverse events, as well as deaths, but the registry information does not provide a formal comparative safety analysis. The listed serious-event terms are not assigned to specific arms in the summary. Interpretation should therefore remain limited to what was recorded, with no claim about a treatment’s overall safety based on these counts alone.

Overall, the record gives useful estimates and uncertainty intervals, but incomplete methodological detail constrains stronger conclusions. The findings are best understood as the posted results of a terminated phase 2 trial, rather than as a definitive estimate of comparative efficacy or safety.

17. Why This Trial Matters Statistically

This trial is statistically informative because it uses a time-to-event endpoint rather than relying only on a score measured at a single visit. The endpoint asks when participants reached a sustained reduction in TB Score, which captures timing as well as occurrence. The sponsor’s use of Cox regression is consistent with analyzing time-to-event comparisons, while the group medians provide a more direct descriptive summary of timing.

The results also illustrate why estimates and uncertainty intervals should be read together. The point estimates alone may invite a simple ranking of the groups, but the reported confidence intervals are broad and include the no-difference value for each hazard ratio. The median-time intervals overlap as well. These features caution against treating the numerical ordering of estimates as a conclusive treatment contrast.

Another important statistical issue is the difference between overall trial enrollment and the reported primary-outcome population. The primary-outcome description records 204 participants with a post-baseline assessment and 17 without one, while the registry’s overall enrollment is 426. Clear reporting of analysis populations and missing-data handling is essential for understanding which participants contribute to an estimate and how broadly it applies.

The sample-size illustrations demonstrate a general planning principle for time-to-event studies: smaller effects require more events to detect under the same assumptions. Their role is planning, not retrospective proof of whether the trial was adequately powered. The registry does not report the original design rationale, so the illustration cannot establish what the investigators planned.

Finally, the record brings together an efficacy endpoint and safety outcomes, but the posted safety counts are descriptive and the multiplicity strategy is not reported. This makes transparent statistical reporting especially important: endpoint definitions, missingness, analysis populations, and plans for multiple comparisons all shape how a trial’s estimates should be read.

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 primary endpoint description has a wording ambiguity about whether higher TB Scores mean a better or worse outcome. It defines the endpoint as time to a sustained 67% reduction but does not provide the detailed rule for sustained reduction. This limits the ability to interpret the direction and exact clinical meaning of the reported hazard ratios.

The registry lists overall enrollment of 426, while the primary-outcome description says 221 participants were enrolled for that outcome and identifies 204 with a post-baseline assessment. It does not explain the relationship between these figures. The record also does not state how the participants without post-baseline assessments were handled in the Cox analyses, nor does it specify the complete analysis population.

Although Cox regression is named, further model details and diagnostics are not reported. The record does not describe censoring, covariate adjustment, assessment of model assumptions, or other technical specifications. Multiplicity adjustment, interim analyses, and the original sample-size justification are also not reported. These omissions constrain assessment of the robustness and prespecification of the analyses.

The trial is listed as terminated, but the reason is not reported in the registry record. The available safety information gives counts and a list of serious-event terms, without a formal comparative analysis or arm assignment for each listed term. The registry’s overall enrollment and outcome information also do not provide additional participant characteristics needed to assess the composition of the analyzed population.

These limitations concern what can be interpreted from the registry record; they do not establish that unreported methods were or were not used. Results should be read as the posted estimates with these reporting gaps in mind.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Adjunctive Acetylsalicylic Acid and Ibuprofen for Tuberculosis — NCT04575519.
• Registry record last updated 2026-06-01; status last verified 2026-01.
• Results first posted 2026-06-01.
• 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

NCT04575519 is a randomized, parallel-group, quadruple-masked phase 2 trial of ASA or IBU added to standard tuberculosis treatment, compared with standard treatment plus placebo. The registry lists 426 participants overall and records the trial as terminated. The primary outcome is time to a sustained 67% reduction in TB Score over 24 weeks of tuberculosis treatment.

The primary-outcome description reports 221 enrolled participants, including 204 with at least one post-baseline assessment. Median times were 5.0 weeks for control, 4.9 weeks for ASA, and 4.1 weeks for IBU. The sponsor reports Cox-regression hazard ratios of 1.161 for control versus ASA and 1.245 for control versus IBU; both 95% confidence intervals include the no-difference value. The registry also lists secondary outcomes and descriptive adverse-event counts. Details on missing-data handling, multiplicity, analysis populations, and the reason for termination are not reported in the registry record.