Impact of Chronic Kidney Disease on the Effects of Ticagrelor in Patients With Diabetes and Coronary Artery Disease: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Impact of Chronic Kidney Disease on the Effects of Ticagrelor in Patients With Diabetes and Coronary Artery Disease (NCT02539160), a randomized phase 4 study. The primary outcome is Platelet Reactivity Measured by Vasodilator Stimulated Phosphoprotein (VASP) Platelet Reactivity Index (PRI %).

2. Clinical Question

The clinical question is about a biological response measured in the study, not about whether the treatment changes clinical events. VASP-PRI reflects platelet reactivity: higher values indicate higher reactivity and a lower antiplatelet effect. The registry notes that PRI greater than 50% represents an inadequate response to antiplatelet medications. This threshold gives context to the measure, but it does not replace the comparison between kidney-disease groups or establish an individual patient's response.

Kidney-disease status was a basis for comparing cohorts, while ticagrelor dose was varied within the crossover design. The registry record does not describe random assignment to CKD status. Accordingly, differences between CKD and non-CKD cohorts should be interpreted as observed group contrasts, not as evidence that CKD itself caused a change in platelet reactivity. The question is also restricted to the measured pharmacodynamic outcome and does not establish effects on atherothrombotic events or other clinical outcomes.

3. Trial Design

This completed Phase 4 study was randomized, unmasked, and used a crossover model. Its stated focus was the impact of chronic kidney disease on pharmacodynamic and pharmacokinetic effects of ticagrelor in patients with diabetes mellitus and coronary artery disease. The registry lists enrollment of 101.

Participants in each kidney-disease cohort received both ticagrelor doses. The CKD sequences began with ticagrelor 90 mg twice daily followed by 60 mg twice daily, or began with 60 mg twice daily followed by 90 mg twice daily. The non-CKD sequences followed the same alternatives. Each dose period is described as lasting 7-10 days. The registry record does not report a washout period, so none should be assumed.

A crossover design allows observations under different treatments from the same participant, which can make within-person contrasts informative when the analysis accounts for the pairing and the order of treatment. The sequence assignment was randomized, but the registry record does not give details of the randomization procedure, sequence balance, or the analysis used to account for period and order effects. The posted group summaries alone do not show the within-person association between measurements.

The primary endpoint was VASP-PRI after ticagrelor 90 mg, comparing the CKD and non-CKD cohorts at 7 days. VerifyNow P2Y12 platelet reactivity was a secondary outcome. Although the study description refers to pharmacokinetic and pharmacodynamic profiles, pharmacokinetic results are not reported in the registry record. The registry also does not report the original sample-size justification or other design assumptions. These omissions limit how fully the design and analysis can be reconstructed from the 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: 101 patients were consented and enrolled in the study; 9 patients were not eligible for randomization due to the presence of exclusion criteria. A total of 92 patients (non-CKD, n=48; CKD, n=44) were randomized and exposed to at least one dose of study medication.

Phase 1 Pre-crossover

Reasons for not completing this period:

Phase 2 Post-crossover

Analysis population for the primary outcome, as defined in the registry: The pharmacodynamic (PD) population included all patients with any PD data on study drug and without a major protocol deviation thought to affect significantly the PD findings. The PD population was used for analysis of all primary and secondary PD variables.

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: 77 patients (DM-CKD, n=38; DM-non-CKD, n=39) had pharmacodynamic (PD) data on study drug and represented the PD population that was used for the analysis.

6. Primary Endpoint

The registry lists the primary outcome as Platelet Reactivity Measured by Vasodilator Stimulated Phosphoprotein (VASP) Platelet Reactivity Index (PRI %), measured over 7 days.

The primary endpoint was platelet reactivity measured by the Vasodilator Stimulated Phosphoprotein Platelet Reactivity Index, or VASP-PRI, expressed as PRI%. The registry describes the endpoint as assessed after treatment with ticagrelor 90 mg and compares the diabetes-and-CKD cohort with the diabetes-without-CKD cohort. The stated timeframe is 7 days.

VASP-PRI is a pharmacodynamic measure: it describes platelet reactivity during antiplatelet treatment rather than a clinical event. The direction matters. Higher PRI values represent higher platelet reactivity and a lower effect of antiplatelet medication; lower values represent less reactivity on this measure. The registry states that PRI greater than 50% represents an inadequate response to antiplatelet medications. That threshold is useful context, but a group mean does not reveal how many individuals were above or below it.

The measure is used to assess whether platelet response differs across the kidney-disease cohorts after the same ticagrelor dose. It is not itself a measure of heart attack, stroke, bleeding, or survival. Nor can a difference in this laboratory endpoint alone establish a difference in those clinical outcomes. The record reports means and standard deviations for the groups, but does not report individual-level distributions or the number of participants meeting the stated threshold.

7. Results Posted in the Registry

• CKD - Ticagrelor 60: mean 32.00 versus 25.00 on control; difference 7.00 (95% CI 0.93 to 13.07), standardized effect d = 0.52; z-test p = 0.024.
• Non-CKD - Ticagrelor 90: mean 31.00 versus 25.00 on control; difference 6.00 (95% CI -1.70 to 13.70), standardized effect d = 0.35; z-test p = 0.126.
• Non-CKD - Ticagrelor 60: mean 38.00 versus 25.00 on control; difference 13.00 (95% CI 5.30 to 20.70), standardized effect d = 0.75; z-test p = <0.001.

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.

Platelet Reactivity Measured by VerifyNow P2Y12

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • CKD - Ticagrelor 60: mean 59.00 versus 39.00 on control; difference 20.00 (95% CI -5.41 to 45.41), standardized effect d = 0.35; z-test p = 0.123.
  • Non-CKD - Ticagrelor 90: mean 51.00 versus 39.00 on control; difference 12.00 (95% CI -12.39 to 36.39), standardized effect d = 0.22; z-test p = 0.335.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between CKD - Ticagrelor 60 and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Non-CKD - Ticagrelor 90 and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcome, VerifyNow P2Y12 platelet reactivity, follows a broadly similar descriptive pattern to VASP-PRI: posted means are higher with the 60 mg regimen than with the 90 mg regimen in both kidney-status cohorts. The registry does not provide sponsor-reported inferential analyses for this secondary outcome. Recalculated unadjusted comparisons therefore add only limited context and do not establish a confirmed difference.

The general alignment in direction between the platelet-reactivity measures offers descriptive consistency, but it does not turn either measure into evidence about clinical events. The primary endpoint remains VASP-PRI, and the sponsor's own analyses concern CKD versus non-CKD comparisons at the same dose. The secondary summaries do not resolve the uncertainty in those primary cohort comparisons, nor do they establish that a dose difference is statistically reliable in a crossover analysis.

Unadjusted secondary results carry less weight because outcomes and comparisons beyond the primary question create more opportunities to observe an apparently notable result by chance. A multiplicity adjustment can account for a family of tests, but the registry record does not report whether one was planned or used. The secondary endpoint has no sponsor-reported analysis in the record, which further limits inferential interpretation. Its values should therefore be treated as exploratory descriptions rather than independent confirmation of the primary result.

The record reports platelet reactivity at the stated 7-day timeframe. It does not report pharmacokinetic results, despite the study's broader stated aim, or additional secondary clinical outcomes. Conclusions should remain limited to the posted platelet-reactivity measurements and the uncertainty in their comparisons.

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

• Platelet Reactivity Measured by VerifyNow P2Y12

9. Statistical Interpretation

10. Statistical Methods Explained

These results combine registry-reported analyses with simple unadjusted recalculations from posted group summaries. They answer related but distinct statistical questions. The reported analyses compare CKD and non-CKD cohorts at each ticagrelor dose. The recalculations compare each posted group mean with the CKD 90 mg group. Keeping those contrasts distinct is essential, especially because the registry record flags a discrepancy and the sponsor's own analysis takes precedence.

What does a mean describe?

A mean is the arithmetic average of the measured values in a group. It provides a compact description of the group's central level, but it does not show the full distribution. In this study, mean VASP-PRI values summarize platelet reactivity within each dose-and-kidney-status group. A mean difference describes how far apart two group averages are, with the direction depending on which group is subtracted from which. The standard deviation describes the spread of individual values around a group's mean; it is not the uncertainty in the mean itself.

The registry also reports standard deviations for VerifyNow P2Y12 values. Those summaries likewise describe variation among observations. Considerable variability can coexist with a difference between group means, and overlap in the distributions cannot be assessed precisely from means and standard deviations alone.

What does a t-test assess?

The sponsor's reported analyses are two-sided t-tests. In general, a two-sided test evaluates whether the data are compatible with differences in either direction, rather than testing only for a higher or lower value. A p-value summarizes how unusual the observed data, or data more extreme, would be under the test's null model. It is not the probability that the null hypothesis is true, and it does not measure the size or clinical importance of a difference.

The registry reports p = 0.105 for the 90 mg cohort contrast and p = 0.112 for the 60 mg contrast. The confidence intervals for both reported estimates include zero. These results do not provide strong statistical evidence of a difference in the sponsor's analyses, but they do not prove the cohorts are identical. The unadjusted recalculated p-values are based on different contrasts and should not be substituted for those sponsor-reported tests.

Why does the crossover structure matter?

In a crossover study, each participant receives more than one regimen, so measurements from the same person may be related. A paired analysis can use that within-person relationship and may have different uncertainty from an analysis that treats observations as independent. The posted arm means and standard deviations do not provide the within-person covariance needed to reconstruct a paired analysis. The registry record does not report enough detail to determine how period, sequence, or within-person pairing were handled in the sponsor's analysis. The recalculations use posted summary statistics and are unadjusted; they should not be interpreted as reproducing a crossover-model analysis.

In addition, CKD status defines cohorts rather than a randomized treatment assignment in the record. The crossover changes dose exposure, but it does not randomize participants to develop or not develop CKD. Therefore, an observed difference between the CKD and non-CKD groups is an association in these study cohorts and is not by itself a causal estimate of the effect of CKD.

How should the confidence intervals and p-values be read?

A confidence interval gives a range of effect estimates compatible with the data and the analysis procedure at its stated confidence level. A wider interval indicates less precision; an interval that includes zero is compatible with no group difference as well as with differences in either direction. For sponsor-reported results, the registry gives 95% confidence intervals. The recalculated intervals are based on the unadjusted summary-statistic comparisons and are not the sponsor's reported intervals.

The registry record does not report the sponsor's full statistical analysis plan, handling of missing values, or multiplicity procedure. It is therefore not possible to determine from the record whether the reported p-values were adjusted for multiple outcomes or comparisons. Statistical significance should not be inferred from a collection of unadjusted comparisons without considering that limitation.

11. Confidence Intervals and Precision

Precision is reflected in the range of values compatible with an estimate, rather than in the estimate alone. The sponsor-reported primary-dose contrast has an estimated median difference (net) of 6.4 and a 95% confidence interval from -1.1 to 14.3. The interval spans zero, so the data are compatible with no difference as well as with values on either side of zero. The reported p-value is 0.105. The result does not pin down a precise direction or magnitude of the cohort difference.

For the reported 60 mg cohort comparison, the mean difference (final values) is 6, with a 95% confidence interval from -1.5 to 13.7 and p = 0.112. This interval also spans zero. It leaves uncertainty about whether the cohorts differ and, if they do, by how much. A non-significant result does not establish equivalence: equivalence requires a prespecified margin and an analysis designed to assess whether the full interval lies within that margin. Such a margin is not reported in the registry record.

The recalculated unadjusted comparisons have their own intervals, including intervals that are narrower or wider depending on the particular comparison. They arise from contrasts different from the sponsor-reported CKD-versus-non-CKD analyses. The standard deviations also indicate appreciable variation in observed platelet reactivity, particularly for some group summaries. Group averages and intervals do not describe every participant's value, and the record does not provide individual-level distributions.

Because the crossover pairing is not represented in the posted summary statistics, the recalculated precision may not match a paired analysis that uses within-person data. The registry record does not report the full details needed to assess that issue or the handling of missing observations. Thus, the sponsor-reported confidence intervals are the most relevant precision estimates for its stated cohort comparisons; the recalculated intervals should be treated as supplementary, unadjusted descriptions.

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 illustrative, not the trial's original design calculations. For these continuous outcomes, the figures are participants per arm, not total events. The planning 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 original design assumptions and sample-size justification are not reported in the registry record.

The 80% power column describes the number of participants per arm that a planning calculation estimates would be needed to have an 80% chance of detecting the specified effect if that effect were the true one, under the stated assumptions. The 90% power column makes the same kind of estimate for a 90% chance. Higher target power generally requires more participants for the same effect and assumptions. These figures do not describe how likely the trial was to find a result after it was completed.

Rows planning for 75% or 50% of the observed effect illustrate the effect-size dependency: smaller effects require more participants to detect with the same target power and assumptions. The values are tied to the particular observed contrasts and should not be read as a recommended sample size for a future study without considering its design, outcome, analysis, and target effect. In particular, a crossover design may use within-person information that is not represented by an equal-allocation two-arm illustration based on summary statistics. These calculations are not observed power.

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, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = 7.000; pooled standard deviation σ = 13.509.
2. n = 2 × (1.96 + 0.842)² × 13.509² / 7.000² = 58.5, rounded up to 59 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
delta <- 7                      # observed difference in means
sigma <- 13.5092560861063                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^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 (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(2539160)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 59 (80% power), 79 (90% power)
 75% of observed effect: n per arm = 104 (80% power), 140 (90% power)
 50% of observed effect: n per arm = 234 (80% power), 314 (90% power)
power.t.test: 59.4 
Simulated power at n = 59 per arm: 0.800 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-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 sponsor's own reported analyses compare CKD and non-CKD cohorts at the same ticagrelor dose. For ticagrelor 90 mg, the reported median difference (net) is 6.4, with a 95% confidence interval from -1.1 to 14.3 and p = 0.105. For ticagrelor 60 mg, the reported mean difference (final values) is 6, with a 95% confidence interval from -1.5 to 13.7 and p = 0.112. Both intervals include zero.

The recalculated comparisons use simple unadjusted differences from the posted means and compare the CKD 90 mg group with other dose-and-kidney-status groups. They therefore do not reproduce the sponsor's same-dose CKD-versus-non-CKD contrasts. In addition, the sponsor labels its 90 mg estimate as a median difference (net), while the posted arm summaries are means and standard deviations. The two approaches are not interchangeable.

Because the registry record indicates a discrepancy, the sponsor's own analysis takes precedence when describing its stated primary cohort comparison and the other reported cohort comparison. The recalculations are useful only as supplementary, unadjusted readings of the posted summaries. The registry record does not explain the discrepancy or provide sufficient analysis-plan detail to reconcile the estimates further.

15. Multiplicity, Missing Data and Analysis Populations

The registry record identifies a primary endpoint and a secondary platelet-reactivity outcome, and it reports multiple dose and cohort comparisons. It does not report whether the sponsor prespecified a multiplicity strategy, such as adjustment of significance thresholds or a hierarchy for testing outcomes. Without that information, it is not possible to determine whether the reported p-values account for the number of comparisons considered. Unadjusted secondary findings should be interpreted cautiously, since testing more outcomes can increase the chance of apparently noteworthy results.

The primary pharmacodynamic population is described as including patients with any pharmacodynamic data on study drug and without a major protocol deviation thought to significantly affect the pharmacodynamic findings. This description clarifies the intended population for primary and secondary pharmacodynamic analyses. The registry record does not report the number excluded for protocol deviations, the amount or pattern of missing outcome data, or whether analyses used imputation or another missing-data method. Missing-data handling is therefore not reported in the registry record.

The record also does not report the sponsor's complete analysis plan, the full method used to account for crossover pairing, or how period and sequence effects were assessed. It does report two-sided t-tests for the sponsor's posted comparisons, but that alone does not establish the complete analytical procedure. Interim analyses, stopping rules, and sample-size justification are not reported in the registry record.

These gaps matter because analysis choices can affect estimates, uncertainty, and interpretation. They do not invalidate the posted results, but they limit independent assessment of how all observations and comparisons were handled. The sponsor-reported analyses remain the relevant results for the stated cohort comparisons, while the simple recalculations should be understood as unadjusted summaries rather than a reconstruction of the full trial analysis.

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: hypotension (2.6%), syncope (2.6%), hyperglycemia (2.6%), hypokalemia (2.6%).

The registry lists serious adverse events by treatment group, with affected counts of 1 in CKD - Ticagrelor 90, 1 in CKD - Ticagrelor 60, 0 in Non-CKD - Ticagrelor 90, and 1 in Non-CKD - Ticagrelor 60. Deaths are listed as 0 in each group. These are the posted serious-event figures; they do not establish a comparative safety effect.

The registry also reports other, non-serious adverse-event counts of 9, 6, 9, and 7 for those respective groups. Because this is a crossover study, the group listings should not be interpreted as a count of unique participants across the study. The record does not explain whether a participant could contribute events during more than one treatment period, nor does it provide a comparative statistical analysis of adverse events.

The listed serious terms include hypotension, syncope, hyperglycemia, and hypokalemia, each reported at 2.6%. Sparse serious-event counts provide limited information about uncommon harms. These figures describe what the registry reports during the study and should be considered alongside the study's limited duration and the absence of a reported safety comparison.

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

The results describe platelet reactivity measured after short periods of ticagrelor dosing in patients with diabetes and coronary artery disease, with outcomes considered by CKD status. The sponsor-reported cohort comparisons have confidence intervals that include zero, leaving uncertainty about whether platelet reactivity differed between the CKD and non-CKD groups at the same dose. The posted means provide descriptive context, but they do not replace the sponsor's analyses.

These findings do not show whether ticagrelor changes the risk of heart attack, stroke, or other atherothrombotic events. VASP-PRI and VerifyNow P2Y12 are pharmacodynamic measures, not clinical outcomes. A group-level average also cannot identify an individual participant's response or determine how many participants crossed the registry's stated PRI threshold.

The comparisons between CKD and non-CKD cohorts are observational with respect to kidney-disease status in the registry record. Even though dose sequence was randomized in a crossover design, CKD status was not reported as randomized. Differences between cohorts may reflect factors beyond kidney disease, so they cannot be attributed to CKD alone from these results.

The record does not report pharmacokinetic results, a clinical-event analysis, or enough detail to reconstruct all crossover analysis decisions. The appropriate interpretation is therefore narrow: the posted data give short-term platelet-reactivity summaries and sponsor-reported comparisons, with uncertainty that does not establish a clear cohort difference. They do not prove the cohorts are identical, establish equivalence, or support a conclusion about clinical benefit or harm.

18. Why This Trial Matters Statistically

This study raises a statistical question about whether kidney-disease status is associated with pharmacodynamic response to ticagrelor among patients with diabetes and coronary artery disease. Separating that question from treatment effects on clinical events is important. Platelet reactivity can be measured directly in a short study, whereas clinical events are different outcomes and are not reported as results.

The crossover structure is also statistically important. It exposes participants to both ticagrelor doses, so a well-specified analysis can potentially use within-person comparisons. However, group means and standard deviations do not retain the participant-level pairing needed to reproduce such an analysis. The distinction between a posted summary-statistic recalculation and the sponsor's analysis illustrates why design-aware methods and clearly reported estimands matter.

The record further shows how interpretation depends on matching the comparison to the question. The sponsor's reported analyses compare kidney-status cohorts at the same dose; the recalculations use different contrasts. Both can describe aspects of the posted data, but they should not be conflated. The discrepancy makes attention to the sponsor's stated analyses especially important.

Finally, confidence intervals communicate uncertainty that a p-value alone can obscure. The sponsor's intervals include zero and span a range of possible differences, so the results are not a precise demonstration of a cohort difference or of no difference. Transparent reporting of analysis populations, missing-data handling, multiplicity, and crossover methods would help readers assess how firmly the results support each statistical conclusion.

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 registry record leaves several trial-specific uncertainties. It does not report the washout arrangements between dose periods, the detailed randomization procedure, or how the crossover analysis handled within-person pairing, period effects, or sequence effects. Those details are relevant to interpreting repeated measurements, but they cannot be inferred from the arm summaries.

The sponsor's own primary comparison is reported as a median difference (net), while the posted endpoint summaries are means and standard deviations. The record does not provide enough detail to reconcile that distinction or the flagged discrepancy between sponsor analyses and simple recalculations. The sponsor's analyses should take precedence, but the exact source of the discrepancy is not reported in the registry record.

The study description includes pharmacokinetic aims, but pharmacokinetic results are not reported in the registry record. The posted outcomes focus on platelet reactivity at the specified timeframe, not longer-term outcomes or clinical events. The primary result is thus limited to a pharmacodynamic measure.

Details about missing observations, exclusions beyond the stated primary population definition, multiplicity, and the original sample-size justification are not reported. The available summaries also do not show individual-level distributions or the within-person correlation across dose periods. Finally, CKD status is a cohort characteristic rather than a randomized assignment, limiting causal interpretation of differences between those groups. These limitations constrain precision and generalizability without implying that unreported methods were or were not used.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Impact of Chronic Kidney Disease on the Effects of Ticagrelor in Patients With Diabetes and Coronary Artery Disease — NCT02539160.
• Registry record last updated 2022-01-28; status last verified 2022-01.
• Results first posted 2022-01-28.
• 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

NCT02539160 was a completed Phase 4 randomized, unmasked crossover study sponsored by the University of Florida. It enrolled 101 patients with diabetes and coronary artery disease and examined ticagrelor 90 mg and 60 mg twice daily in cohorts with and without chronic kidney disease. Each dose period was described as lasting 7-10 days.

The primary endpoint was VASP-PRI after ticagrelor 90 mg, comparing CKD and non-CKD cohorts. The sponsor reported a median difference (net) of 6.4, with a 95% confidence interval from -1.1 to 14.3 and p = 0.105. The secondary outcome was VerifyNow P2Y12 platelet reactivity; sponsor-reported inferential results for that outcome are not reported in the registry record.

The sponsor's analyses take precedence over unadjusted recalculations because the registry record flags a discrepancy and the comparisons differ. The sponsor-reported intervals include zero. Results describe platelet-reactivity measurements and do not establish clinical effects. Pharmacokinetic results and several analysis details are not reported in the registry record.