Cardiovascular Inflammation Reduction Trial: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Cardiovascular Inflammation Reduction Trial (NCT01594333), a randomized phase 3 study. The primary outcome is Number of Subjects With Major Adverse Cardiovascular Events.

2. Clinical Question

3. Trial Design

The Cardiovascular Inflammation Reduction Trial was a randomized, phase 3, parallel-group, placebo-controlled trial. It was triple-masked, meaning the registry describes masking at three levels but does not identify those roles in the record. The trial was event-driven, according to its official title. Its enrollment was 4786 participants: 2391 assigned to methotrexate and 2395 assigned to placebo.

The intervention was weekly oral low-dose methotrexate with folic acid; the comparator was oral placebo with folic acid. The registry lists cardiovascular disease as the condition. The summary describes the target population as people with type 2 diabetes or metabolic syndrome who had a heart attack or multiple coronary blockages. The primary outcome description specifies all randomized subjects.

The primary outcome timeframe ran from randomization to trial end, identified as April 2, 2018, up to a maximum of 5 years. The registry lists the trial as completed and gives a primary completion date of 2019-04-15. These dates refer to different registry fields and should not be treated as interchangeable.

Brigham and Women's Hospital is listed as the sponsor. The trial summary says it was funded by the National Heart, Lung, and Blood Institute and the National Institutes of Health. The original design's sample-size justification, planned recruitment assumptions and any interim-analysis arrangements 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: 9321 subjects were screened, 2987 were found to be ineligible and 176 were discontinued due to premature trial closure prior to entering the open label run-in. 6158 started the run-in. Of those, 1171 were ineligible, 201 were discontinued due to premature trial closure and 4786 subjects were randomly assigned to either Methotrexate or Placebo

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: All randomized subjects

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 randomized participants

6. Primary Endpoint

The registry lists the primary outcome as Number of Subjects With Major Adverse Cardiovascular Events, measured over From randomization to trial end (April 2, 2018) up to a maximum of 5 years.

The primary endpoint counted participants with a first major adverse cardiovascular event. The event definition includes cardiovascular death, non-fatal myocardial infarction or non-fatal stroke. The registry specifies the first occurrence of one or more of these events, with the endpoint assessed from randomization to trial end, up to a maximum of 5 years. The primary population is all randomized subjects.

A composite endpoint combines several clinically defined event types into a single outcome. In general, this can capture more events than any one component alone and provide a broad summary of the outcomes chosen for the trial question. It also means the overall result does not, by itself, establish whether each component follows the same pattern. Component-specific results would be needed to assess that; the registry record does not give primary-outcome component counts in the results.

The registry reports the endpoint as a count of participants with an event in each group, alongside a time-to-event analysis. These summaries answer related but distinct questions: the counts describe how many participants experienced the endpoint, while a time-to-event model incorporates when events occurred and the follow-up available for participants. The choice of a composite cardiovascular endpoint and the time-to-event method therefore shape how the primary result should be read.

7. Results Posted in the Registry

• Methotrexate: 7.1% (170/2391) versus 7.0% (167/2395) on control; risk difference 0.1 percentage points (95% CI -1.3 to 1.6), risk ratio 1.02 (0.83–1.25); unadjusted two-proportion z-test p = 0.853.

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 Subjects With All-cause Mortality

• 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:
  • Methotrexate: 4.0% (96/2391) versus 3.5% (83/2395) on control; risk difference 0.5 percentage points (95% CI -0.5 to 1.6), risk ratio 1.16 (0.87–1.55); unadjusted two-proportion z-test p = 0.316.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Methotrexate and the control. The interval gives the range of effects that remain compatible with the data.

Number of Subjects With Hospitalization for Congestive Heart Failure

• 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:
  • Methotrexate: 2.0% (48/2391) versus 2.2% (53/2395) on control; risk difference -0.2 percentage points (95% CI -1.0 to 0.6), risk ratio 0.91 (0.62–1.34); unadjusted two-proportion z-test p = 0.621.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Methotrexate and the control. The interval gives the range of effects that remain compatible with the data.

Number of Subjects With New Onset Type 2 Diabetes

• 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:
  • Methotrexate: 0.7% (4/605) versus 1.0% (6/620) on control; risk difference -0.3 percentage points (95% CI -1.3 to 0.7), risk ratio 0.68 (0.19–2.41); unadjusted two-proportion z-test p = 0.551.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Methotrexate and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes cover all-cause mortality, hospitalization for congestive heart failure, new onset type 2 diabetes, and broader cardiovascular or composite outcomes that include coronary revascularization. The posted numerical results do not all have the same level of detail: arm-level comparisons and reported analyses are available for some outcomes, while results for the listed outcome combining major adverse cardiovascular events with coronary revascularization and the broader composite are not reported in the registry record.

Across the secondary results with numerical comparisons, the estimates do not establish a clear, consistent departure from no difference. Their intervals include the corresponding no-difference values, and the registry's reported analyses for mortality and heart-failure hospitalization are not statistically clear. These findings are broadly consistent with the primary result's lack of a clear group separation, but they do not prove that all outcomes are equivalent or that every component behaves alike.

Secondary outcomes can help describe the range of observed effects, but they generally carry less confirmatory weight than the primary endpoint. When multiple outcomes are examined, the chance of at least one apparently unusual result can increase. The registry lists 13 outcome measures and 8 analyses, but a multiplicity adjustment or hierarchy for interpreting the secondary comparisons is not reported in the registry record. Unadjusted secondary findings should therefore be treated cautiously and not as independent confirmation of a treatment effect.

The secondary outcomes also differ in meaning and, for new onset type 2 diabetes, the analyzed group sizes differ from those used for the primary endpoint. Those differences make it important to interpret each outcome on its own terms rather than treating the set as a single repeated test of the primary question.

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

• Number of Subjects With All-cause Mortality
• Number of Subjects With Major Adverse Cardiovascular Event or Any Coronary Revascularization
• Number of Subjects With Hospitalization for Congestive Heart Failure
• Number of Subjects With Major Adverse Cardiovascular Event, Coronary Revascularization, Hospitalization for Congestive Heart Failure or All Cause Mortality
• Number of Subjects With New Onset Type 2 Diabetes

9. Statistical Interpretation

10. Statistical Methods Explained

The registry reports a log-rank analysis with a Cox proportional hazards model for the primary outcome. In general, time-to-event methods use both whether an event occurred and the time until it occurred, while allowing participants to contribute different amounts of follow-up. The log-rank test compares event patterns over follow-up; the Cox model expresses the relative event rate over time as a hazard ratio. These are general descriptions of the methods, not additional details about the trial's implementation.

The posted Cox estimate is a hazard ratio of 1.01, with a 95% confidence interval from 0.82 to 1.25 and p = 0.91. A hazard ratio near the no-difference value indicates that the fitted comparison is close to no relative separation in event rates. The confidence interval reflects uncertainty in that estimate. Its range includes values below and above the no-difference value, so the result does not precisely rule out effects in either direction. General interpretation of a Cox estimate depends on the proportional-hazards assumption; whether and how that assumption was assessed is not reported in the registry record.

The unadjusted recalculation uses the event counts and randomized group sizes to estimate a risk difference. In general, risk difference expresses the absolute contrast between the proportions experiencing an event in two groups. The recalculated estimate is 0.001, with a 95% confidence interval from -0.013 to 0.016 and p = 0.853. This calculation is based on posted summary counts and is not the same analysis as the registry's time-to-event model. It does not account for timing of events or differing follow-up in the way a survival analysis does.

The posted results also give relative risk and odds ratio summaries for the primary endpoint. The recalculated relative risk is 1.02, with a 95% confidence interval from 0.830 to 1.253; the recalculated odds ratio is 1.021, with a 95% confidence interval from 0.818 to 1.274. In general, relative risk compares event probabilities, while an odds ratio compares event odds. Neither should be confused with the hazard ratio, which is based on time-to-event information. Each measure uses a different scale, so estimates that appear numerically different are not necessarily contradictory.

The p-value describes how unusual data at least as incompatible with the null as the observed data would be under the model and assumptions used. It is not the probability that the null hypothesis is true, nor does it quantify the size or clinical importance of an effect. The confidence interval complements the p-value by showing a range of estimates compatible with the data under the interval method. General interpretation requires attention to both the estimated effect and its uncertainty.

For binary outcomes, an event count is the number of participants recorded as having the event; it is not an event rate per unit of time. The primary endpoint is recorded as a participant count, while the sponsor's reported analysis is time-to-event. That distinction matters because a simple count comparison does not incorporate event timing or follow-up duration. The registry does not report additional information about censoring, event adjudication or the precise model specification.

The planning illustrations use the observed effect as a reference and show sample sizes for specified fractions of that effect. General planning calculations depend on assumptions, and the stated assumptions are a two-sided significance level of 0.05, equal allocation between arms and a normal approximation. The original trial's design assumptions and sample-size justification are not reported in the registry record. The planning illustrations should therefore be understood as a separate calculation, not as documentation of how the trial was designed.

For general context, over-dispersion matters when observed variability exceeds what a model assumes: standard errors may then be too small if the extra variability is ignored, making intervals too narrow and tests too optimistic. The primary outcome is reported as a binary participant count, and no dispersion measure is listed. The registry does not describe an over-dispersion assessment or a model for extra variability; this general issue should not be read as evidence that over-dispersion occurred in this trial.

11. Confidence Intervals and Precision

The primary unadjusted risk-difference estimate is 0.001, with a 95% confidence interval from -0.013 to 0.016. In general, a confidence interval represents the uncertainty around an estimate under the method used; it is not a range guaranteed to contain the true effect. This interval includes no difference and extends to estimates in both directions. The data therefore do not tightly locate the effect around a single value.

The reported time-to-event estimate is a hazard ratio of 1.01, with a 95% confidence interval from 0.82 to 1.25. This interval also spans the no-difference value, with values compatible with a lower or higher hazard. The recalculated relative risk interval, 0.830 to 1.253, and odds ratio interval, 0.818 to 1.274, likewise include their respective no-difference values. These measures have different interpretations, but each interval communicates uncertainty on its own scale.

Precision is affected by the number of observed events as well as the number of participants and the analysis method. The primary results include 170 events in the methotrexate group and 167 in the placebo group. Those counts, together with the observed group sizes and follow-up structure, inform the width of the estimates. The registry record does not report a prespecified precision target or the original sample-size justification.

A confidence interval that crosses the no-difference value should not be read as proof of no effect. It indicates that the posted data are compatible with a range of possibilities that includes no difference. Nor does a point estimate close to the null establish equivalence: that conclusion would require an appropriate equivalence or non-inferiority framework, which is not reported in the registry record.

12. Planning a Similar Trial: Sample Size

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

The planning figures are illustrations based on the observed effect, not a record of the trial's original design calculation. For these participant-count outcomes, the figures are participants per arm. In general, a time-to-event planning calculation using the stated Schoenfeld approach reports the total number of events instead; the meaning of a planning figure depends on the outcome and method.

The stated calculation assumptions are a two-sided significance level of 0.05, equal allocation between the two arms and a normal approximation. The effect to detect is set to the stated fraction of the observed effect. The registry record does not report the original sample-size assumptions or the justification used to plan the trial.

The 80% power column gives the planned number of participants per arm for a calculation with an 80% chance of detecting the specified effect under the stated assumptions, if that effect is real. The 90% power column uses a higher chance of detection and generally requires more participants. These are planning concepts, not guarantees about a future study's result.

The entries for planning for 100% of the observed effect, 75% of the observed effect and 50% of the observed effect illustrate how the assumed effect size changes the required sample. Smaller effects need more participants to detect under otherwise unchanged assumptions. In the primary outcome illustration, the very large sample requirements reflect the small observed risk difference used as the planning reference. This is not observed power: it does not describe the probability that this completed trial detected an effect after its results were known.

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 = 0.070; treatment proportion p₁ = 0.071; average p̄ = 0.070.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.3618 = 0.7092.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.3618 = 0.3045.
4. n = (0.7092 + 0.3045)² / (0.0014)² = 546,368.8, rounded up to 546,369 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 <- 0.0697286012526096                          # control proportion
p1 <- 0.0710999581764952                          # 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(1594333)
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 = 546,369 (80% power), 731,433 (90% power)
 75% of observed effect: n per arm = 969,138 (80% power), 1,297,400 (90% power)
 50% of observed effect: n per arm = 2,175,641 (80% power), 2,912,565 (90% power)
power.prop.test: 546368.8 
Simulated power at n = 546,369 per arm: 0.799 (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. Analyses Reported by the Sponsor

The registry's own primary analysis is a log-rank test with a Cox proportional hazards model. It reports a hazard ratio of 1.01, a 95% confidence interval from 0.82 to 1.25 and p = 0.91. The recalculation from the posted event counts is an unadjusted risk difference of 0.001, with a 95% confidence interval from -0.013 to 0.016 and p = 0.853.

These results are broadly similar in that both estimates are close to their respective no-difference values and both intervals include no difference. They are not expected to match exactly: the recalculation compares event proportions from summary counts, whereas the registry analysis uses time-to-event information and reports a hazard ratio. The registry record does not provide enough detail to reproduce the sponsor's model fully.

The reported analysis is the trial's registry-recorded analysis; the recalculation is a simple, unadjusted check based on posted summary statistics. Neither should be substituted for the other, and differences between their estimates or p-values do not by themselves indicate an error. The record does not flag a discrepancy between them.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists 13 outcome measures and 8 analyses. Several outcomes are secondary, and the trial also reports more than one statistical summary for some comparisons. In general, multiplicity is the problem of interpreting several tests or estimates together: the more comparisons made, the greater the chance that at least one result may appear notable by chance alone. A prespecified testing order or statistical adjustment can address parts of this issue, but neither a hierarchy nor an adjustment strategy is reported in the registry record.

The primary analysis population is described as all randomized subjects. That identifies the stated population for the primary outcome, but the record does not explain how participants with incomplete follow-up, missing outcome information or other deviations were handled. Missing-data procedures, censoring rules and any sensitivity analyses are not reported in the registry record. The effect of missingness on the estimates therefore cannot be assessed from these results alone.

The registry identifies the trial as event-driven and gives a primary outcome timeframe of randomization to trial end, up to a maximum of 5 years. The original event target, recruitment assumptions and sample-size justification are not reported in the registry record. Interim analyses and any associated decision rules are also not reported. These omissions limit what can be concluded about the planned monitoring and analysis strategy.

The record reports a Cox proportional hazards analysis, but does not describe model covariates, checks of model assumptions, stratification, or whether any additional analyses were prespecified. It is also not reported whether endpoint adjudication was independent of treatment assignment. These are not grounds to infer a flaw; they identify details needed for a fuller assessment of the analysis and its robustness.

16. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: any cancer (4.4%), chest pain (3.2%), non-basal-cell skin cancer (not known if sae) (1.4%), pneumonia (1.2%), syncope (1.0%).

The safety summary lists serious adverse events affecting 569 of 2391 participants in the methotrexate group and 549 of 2395 in the placebo group. It also lists other adverse events affecting 1488 and 1399 participants, respectively, and deaths of 96 and 83. These are posted group counts; they should be read alongside their group denominators and the registry's definitions, which are not elaborated in the safety summary.

The most frequent serious adverse event terms listed are Any Cancer (4.4%), Chest pain (3.2%), Non-basal-cell skin cancer (not known if SAE) (1.4%), Pneumonia (1.2%), Syncope (1.0%) and Renal failure acute (0.9%). The registry excerpt does not specify arm-specific percentages for these terms, so they should not be attributed to one group or used to infer a between-group difference.

Safety counts are descriptive. They do not, on their own, establish causation or provide a complete comparison of severity, timing or exposure-adjusted risk. The registry record does not report further detail on those aspects in this summary.

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

The results show that major adverse cardiovascular events were recorded in both randomized groups, with 170 participants affected in the methotrexate group and 167 in the placebo group. The registry's time-to-event analysis estimated a hazard ratio of 1.01, with a 95% confidence interval from 0.82 to 1.25 and p = 0.91. The unadjusted risk-difference calculation likewise has an interval that includes no difference. These results do not provide statistically clear evidence of a difference between groups on the primary endpoint.

That interpretation is not the same as concluding that the treatments are equivalent, that the true effect is exactly zero, or that every possible effect has been ruled out. The confidence intervals retain uncertainty and include estimates in both directions. The registry record does not report an equivalence or non-inferiority design, so those conclusions cannot be drawn from the reported superiority analysis.

The endpoint is a composite of cardiovascular death, non-fatal myocardial infarction and non-fatal stroke. The overall comparison does not establish how each component behaved separately. Nor does the result establish effects on outcomes beyond those measured, in populations not described by this trial, or over time beyond the stated maximum follow-up of 5 years.

Secondary outcomes and safety counts provide additional descriptive information, but they do not change the primary statistical conclusion. Their interpretation is limited by uncertainty, multiple comparisons and the absence of reported multiplicity procedures. The findings should be understood as evidence from this randomized trial and its posted analyses, rather than as a universal statement about methotrexate or cardiovascular risk.

18. Why This Trial Matters Statistically

This trial is statistically informative because it compares randomized groups using both observed event counts and a reported time-to-event analysis. The two approaches describe the result on different scales: counts and risk difference give an absolute comparison, while the Cox model gives a relative hazard estimate that incorporates event timing. Seeing both helps readers understand why a single number cannot capture every aspect of the data.

The primary confidence interval is also central to interpretation. The point estimate is close to no difference, but the interval covers a range on both sides of that value. This illustrates the distinction between an estimate and its precision: a result that is not statistically clear does not prove the absence of an effect, and a near-null estimate does not by itself establish equivalence.

The trial highlights the importance of separating confirmatory and secondary questions. A primary endpoint was defined using major cardiovascular events, while several additional outcomes were recorded. Without a reported multiplicity strategy, secondary findings warrant more caution than a single prespecified primary comparison. Likewise, a sample-size illustration based on an observed effect is not a substitute for the trial's original design justification.

Finally, the record shows why statistical interpretation depends on transparent reporting. Details about missing data, interim analyses, model specifications and multiplicity are not reported in the registry record. Readers can interpret the posted estimates and uncertainty, while recognizing that these unreported elements limit a complete reconstruction of the analysis plan.

19. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

The primary result is based on a composite endpoint, and the registry's posted primary summary does not give separate component counts for cardiovascular death, non-fatal myocardial infarction and non-fatal stroke. The overall estimate therefore cannot show whether the components had similar patterns. The registry also does not report detailed information on event adjudication or outcome ascertainment.

Follow-up is described as running from randomization to trial end, up to a maximum of 5 years, but the distribution of follow-up and censoring details are not reported in the registry record. The reported Cox model's covariate specification and assessment of the proportional-hazards assumption are also not reported. These missing details make it difficult to assess sensitivity to modeling and follow-up choices.

The registry does not describe the original sample-size justification, missing-data methods, interim analyses, or multiplicity handling. Those omissions limit assessment of the planned statistical strategy, particularly given the number of outcomes and analyses listed. Secondary results should accordingly be interpreted with caution.

The trial summary identifies a specific population: people with stable coronary artery disease and type 2 diabetes or metabolic syndrome, described as having had a heart attack or multiple coronary blockages. The results should not automatically be generalized to populations with different characteristics or to outcomes not measured by the trial. The registry record does not provide subgroup estimates in the results.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Cardiovascular Inflammation Reduction Trial — NCT01594333.
• Registry record last updated 2020-07-24; status last verified 2020-07.
• Results first posted 2020-07-24.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

23. Record Summary

The Cardiovascular Inflammation Reduction Trial was a randomized, triple-masked, parallel-group, phase 3 trial comparing weekly low-dose methotrexate with placebo. Enrollment was 4786 participants, and the registry lists the trial as completed. The primary endpoint was the first occurrence of cardiovascular death, non-fatal myocardial infarction or non-fatal stroke among all randomized subjects, followed from randomization to trial end up to a maximum of 5 years.

The primary event counts were 170 of 2391 in the methotrexate group and 167 of 2395 in the placebo group. The registry-reported Cox analysis gave a hazard ratio of 1.01, a 95% confidence interval from 0.82 to 1.25 and p = 0.91. The posted results do not show a statistically clear difference in the primary outcome. Important details about missing data, multiplicity and the original design assumptions are not reported in the registry record.