This page provides an independent statistical analysis and educational interpretation of publicly reported results. ClinicalTrials.gov provides the official trial registry record.
1. Trial at a Glance
CRYSTAL-AF was a randomized, parallel, unmasked phase 4 diagnostic study comparing continuous cardiac monitoring with the Reveal® XT Insertable Cardiac Monitor against a control arm in subjects with cryptogenic symptomatic transient ischemic attack or cryptogenic ischemic stroke. The primary endpoint was the percentage of subjects with atrial fibrillation detected within 6 months of follow-up.
| Feature | CRYSTAL-AF |
|---|---|
| Trial name | CRYSTAL-AF |
| NCT identifier | NCT00924638 |
| Phase | Phase 4 |
| Therapeutic area | Cardiovascular |
| Conditions | Cryptogenic Symptomatic Transient Ischemic Attack; Cryptogenic Ischemic Stroke |
| Allocation | Randomized |
| Design model | Parallel |
| Masking | None |
| Primary purpose | Diagnostic |
| Enrollment | 447 |
| Intervention | Reveal® XT Insertable Cardiac Monitor (device) |
| Primary endpoint type | Binary; analyzed as a time-to-event comparison in the posted statistical analysis |
| Hypothesis type | Superiority |
| Lead sponsor | Medtronic Cardiac Rhythm and Heart Failure |
| Sponsor type | Industry |
| Study dates | Start: 2009-06; Primary completion: 2013-05 |
| Results | Posted |
2. Clinical Question
The central question was whether continuous cardiac monitoring with the Reveal® XT Insertable Cardiac Monitor would detect atrial fibrillation more frequently, and earlier in the follow-up process, than the control strategy in subjects with cryptogenic symptomatic transient ischemic attack or cryptogenic ischemic stroke.
Population
Subjects with cryptogenic symptomatic transient ischemic attack or cryptogenic ischemic stroke.
Intervention
Reveal® XT Insertable Cardiac Monitor, an insertable cardiac monitoring device providing continuous monitoring.
Comparator
Control arm.
Primary question
Does continuous cardiac monitoring improve detection of atrial fibrillation within 6 months of follow-up?
3. Trial Design
Reveal® XT Insertable Cardiac Monitor
- Device intervention
- Continuous cardiac monitoring
- Compared with the control arm
- Primary AF detection assessment at 6 months
- Secondary assessments include 12-month outcomes
Control strategy
- Randomized comparator
- Compared with continuous monitoring
- Primary AF detection assessment at 6 months
- Secondary assessments include 12-month outcomes
- Used as the reference group for effect estimates
The registry identifies the study as randomized, parallel, and unmasked. The ClinicalTrials.gov record does not specify a crossover procedure, factorial structure, non-inferiority margin, interim-analysis framework, stratification factors, or Bayesian analysis.
4. Endpoints
The registry lists one primary endpoint and multiple secondary outcome measures. Although the primary endpoint is described in the registry as binary, the posted statistical analysis treats AF detection as a time-to-event endpoint and compares the randomized groups using a log-rank test with a hazard ratio.
| Role | Endpoint | Time frame | Definition / measure |
|---|---|---|---|
| Primary | AF Detection Rate Within 6 Months | 6 months | Percentage of subjects with AF detected within 6 months of follow-up. |
| Secondary | AF Detection Rate Within 12 Months | 12 months | AF detection analyzed as a time-to-event endpoint. |
| Secondary | Incidence of Recurrent Stroke or TIA (Transient Ischemic Attack) | 12 months | Incidence of recurrent stroke or TIA analyzed as a time-to-event endpoint. |
| Secondary | Use of Oral Anticoagulation (OAC) Drugs | 12 months | Use among subjects who completed the 12-months follow-up visit. |
| Secondary | Use of Antiarrhythmic Drugs | 12 months | Use among subjects who completed the 12 months follow-up visit. |
| Secondary | Clinical Disease Burden and Care Pathway | 12 months | Time-to-event analysis in the intention-to-treat population. |
| Secondary | Health Outcome as Evaluated by EQ-5D Questionnaire | 12 months | Units on a scale of 0 to 100. |
5. Analysis Populations
| Analysis | Population reported in the registry | Why it matters |
|---|---|---|
| Primary AF detection | Intention-to-treat (ITT) population (all randomized subjects) | Preserves randomized treatment assignment for the primary comparison. |
| 12-month AF detection | Intention-to-treat (ITT) population (all randomized subjects) | Maintains the randomized comparison while using follow-up time to the event. |
| Recurrent stroke or TIA | Intention-to-treat (ITT) population (all randomized subjects) | Uses the randomized population for the clinical-event comparison. |
| OAC use | Number of subjects who completed the 12-months follow-up visit | Different from ITT; the analysis is restricted to subjects completing the specified visit. |
| Antiarrhythmic drug use | Number of subjects who completed the 12 months follow-up visit | Different from ITT; completion of the specified visit defines the analysis population. |
| EQ-5D | Number of subjects who reported EQ-5D VAS score at the 12 months visit | The analysis is based on subjects with a reported score at that visit. |
The use of different analysis populations is an important statistical feature of CRYSTAL-AF. The primary AF endpoint and several time-to-event secondary outcomes use all randomized subjects, whereas the drug-use and EQ-5D analyses are based on subjects with the specified follow-up information.
6. Primary Result: AF Detection Rate Within 6 Months
The primary endpoint was the percentage of subjects with AF detected within 6 months of follow-up. The registry's posted formal analysis used a log-rank test in the intention-to-treat population and reported a hazard ratio for continuous monitoring versus the control arm.
Hazard ratio for AF detection
95% CI: 1.9–21.7 · P = 0.0006 · Two-sided
Analysis: log-rank test · Population: all randomized subjects
The registry notes that a hazard ratio greater than 1 indicates that continuous monitoring is superior to control in detecting AF.
The estimated hazard ratio of 6.4 means that, under the time-to-event analysis reported by the registry, the estimated instantaneous rate of AF detection was 6.4 times as high in the continuous-monitoring group as in the control group over the analyzed follow-up.
This does not mean that 6.4 times as many participants necessarily had AF detected, nor does it mean that the probability of AF detection was 6.4 times as high at every specific time point. A hazard ratio describes a relative rate of event occurrence over time.
The 95% confidence interval of 1.9–21.7 is wide. It indicates substantial statistical uncertainty around the estimated hazard ratio, even though the entire interval lies above 1. The width of the interval is important: the data are compatible with a substantially smaller relative effect than 6.4 as well as with a much larger one.
The P-value of 0.0006 addresses the evidence against the null hypothesis within the reported statistical framework. It does not measure the magnitude of the effect, the probability that the treatment works, or the clinical importance of the result.
Because the result is a time-to-event analysis, interpretation also depends on censoring and the assumptions underlying the hazard-ratio framework. The ClinicalTrials.gov record does not report a formal assessment of the proportional-hazards assumption, so that assumption should not be treated as independently verified here.
Why a hazard ratio is useful for AF detection
A fixed 6-month percentage can tell us whether AF was detected by a specified landmark. A time-to-event analysis adds information about when AF was detected. Someone whose AF is detected early and someone whose AF is detected shortly before the 6-month assessment can both count toward a 6-month detection percentage, but their event times are not equivalent for a survival analysis.
The reported HR therefore reflects the trial's use of follow-up time rather than only a simple comparison of two endpoint percentages. The log-rank test provides the formal comparison reported in the registry, while the hazard ratio provides a measure of the relative event rate.
7. Secondary Result: AF Detection Rate Within 12 Months
The 12-month AF detection endpoint used the same intention-to-treat population and the same reported log-rank approach. The registry again reported a hazard ratio for continuous monitoring versus control.
Hazard ratio for AF detection at 12 months
95% CI: 2.6–20.8 · P < 0.0001 · Two-sided
Analysis: log-rank test · Population: all randomized subjects
The reported hazard ratio of 7.3 indicates a higher estimated rate of AF detection in the continuous-monitoring group relative to the control group during the 12-month analysis.
The estimate is larger than the primary 6-month estimate of 6.4, but the two estimates should not be treated as independent measures of two unrelated treatment effects. They describe the same randomized comparison over different follow-up horizons.
The 95% CI of 2.6–20.8 remains entirely above 1, but is also wide. Thus, the result provides evidence of a higher detection rate while leaving substantial uncertainty about the precise magnitude of the relative effect.
The P-value < 0.0001 indicates strong evidence against the null hypothesis under the reported analysis. It is not a measure of effect size and should not be used as a substitute for the hazard ratio or its confidence interval.
As with the primary endpoint, the hazard ratio should not be interpreted as a fixed relative risk at every point in time. The time-to-event structure, censoring, and model assumptions remain relevant.
8. Secondary Result: Recurrent Stroke or TIA
Recurrent stroke or TIA was evaluated over 12 months in the intention-to-treat population. The registry reports a log-rank analysis and a hazard ratio comparing continuous monitoring with the control arm.
Hazard ratio for recurrent stroke or TIA
95% CI: 0.35–1.32 · P = 0.25 · Two-sided
12-month time frame · Analysis: log-rank test
The hazard ratio of 0.68 corresponds to an estimated event rate that is lower in the continuous-monitoring arm than in the control arm under the reported time-to-event analysis. In relative terms, 0.68 is 32% below 1, but that arithmetic should not be converted into a claim that continuous monitoring definitively reduced recurrent stroke or TIA by 32%.
The key reason is the 95% CI of 0.35–1.32. The interval crosses 1, so the data are compatible with a lower event rate, little difference, or a higher event rate under the modeled comparison.
The P-value of 0.25 does not provide evidence against the null hypothesis at conventional significance thresholds. More importantly, it does not establish that the treatment groups are equivalent. A non-significant result can reflect uncertainty rather than proof of no difference.
This endpoint also illustrates why the hazard ratio, confidence interval, and P-value should be considered together. The point estimate alone suggests a lower event rate, but the interval demonstrates that the estimate is not sufficiently precise to exclude materially different effects.
9. Secondary Result: Use of Oral Anticoagulation Drugs
Use of oral anticoagulation drugs was assessed at the 12-month visit among subjects who completed the 12-months follow-up visit. The registry reports a mean difference in final values but does not report the statistical method used.
Mean difference in OAC use
95% CI: 2.8–14.8 · Two-sided
12-month follow-up visit · Method: not reported
The registry specifies that a difference greater than 0 means that a higher percentage of subjects in the continuous-monitoring arm were using oral anticoagulation drugs at the 12-month visit compared with the control arm.
The reported mean difference of 8.8 is positive, consistent with a higher percentage using oral anticoagulation drugs in the continuous-monitoring group under the registry's stated direction of effect.
The 95% CI of 2.8–14.8 is entirely above 0, indicating that the reported estimate is separated from the null value of zero under the stated analysis framework.
However, the registry does not report the statistical method used for this endpoint. The result should therefore not be retroactively assigned a particular test or model. For a binary treatment-use endpoint, a two-group proportion comparison or a regression model could be appropriate depending on the prespecified analysis plan, but the ClinicalTrials.gov record does not identify which method was used.
There is also an important population distinction: this analysis is based on subjects who completed the specified 12-month follow-up visit rather than all randomized subjects. Consequently, it does not have the same direct ITT interpretation as the primary AF endpoint.
10. Secondary Result: Use of Antiarrhythmic Drugs
Use of antiarrhythmic drugs was also assessed at the 12-month follow-up visit among subjects who completed that visit. The registry reports a mean difference in final values and does not report the statistical method.
Mean difference in antiarrhythmic-drug use
95% CI: -2.3–3.1 · Two-sided
12-month follow-up visit · Method: not reported
The reported difference of 0.4 is positive, meaning that under the registry's stated direction a higher percentage of subjects in the continuous-monitoring arm were using antiarrhythmic drugs at the 12-month visit.
The 95% CI of -2.3–3.1 crosses zero. The data therefore remain compatible with a small lower percentage, essentially no difference, or a small higher percentage in the continuous-monitoring group.
The point estimate is close to zero relative to the uncertainty interval. It would therefore be inappropriate to interpret the estimate of 0.4 by itself as evidence of a meaningful difference.
As with OAC use, the analysis population is restricted to subjects who completed the specified follow-up visit, and the registry does not report the formal statistical method. These features limit how specifically the result can be interpreted.
11. Secondary Result: Clinical Disease Burden and Care Pathway
Clinical disease burden and care pathway was evaluated over 12 months in the intention-to-treat population using a log-rank analysis and hazard ratio.
Hazard ratio for clinical disease burden and care pathway
95% CI: 0.73–2.60 · P = 0.33 · Two-sided
12-month time frame · Analysis: log-rank test
The registry reports a hazard ratio of 1.37. Its accompanying analysis note describes a hazard ratio below 1 as corresponding to a lower incidence rate of cardiovascular or stroke/TIA-related hospitalization in the continuous-monitoring arm. The point estimate of 1.37 therefore does not indicate a lower estimated event rate for continuous monitoring under that direction-of-effect convention.
The 95% CI of 0.73–2.60 crosses 1, and the P-value of 0.33 does not provide evidence against the null hypothesis under the reported test.
The interval is important because it allows for a range of effects, including values below 1 and values above 1. The result should therefore not be converted into a claim that continuous monitoring increased or decreased clinical disease burden or hospitalization.
The endpoint's registry label is broader than a single clinical event, so its interpretation should remain tied to the registry definition rather than being reduced to a generic statement about hospitalization.
12. Secondary Result: Health Outcome as Evaluated by EQ-5D Questionnaire
Health outcome was assessed using the EQ-5D questionnaire at the 12-month visit. The outcome unit is reported as units on a scale of 0 to 100, and the statistical analysis used a two-sided t-test.
EQ-5D statistical comparison
12-month time frame · Two-sided t-test
Analysis population: subjects who reported an EQ-5D VAS score at the 12-month visit
The registry reports a P-value of 0.11 from a two-sided t-test. No effect estimate or confidence interval is reported in the provided statistical-analysis record.
Because no mean difference or confidence interval is reported here, the P-value cannot be translated into a quantified difference in EQ-5D score. A P-value alone does not indicate how large or clinically important a difference might be.
The analysis population is also restricted to subjects who reported an EQ-5D VAS score at the 12-month visit. That is distinct from an ITT analysis of all randomized subjects and should be recognized when interpreting the result.
13. Statistical Methodology
Log-rank test
The registry reports the log-rank test for the primary AF detection endpoint and several secondary time-to-event outcomes. The log-rank test compares the experience of two groups across follow-up rather than comparing only whether an event occurred by a single fixed date.
The log-rank framework uses the observed and expected numbers of events across event times to compare the groups over follow-up.
Hazard ratio
The principal effect measure for the registry's time-to-event analyses is the hazard ratio. A hazard ratio compares the instantaneous event rates between the two groups under the time-to-event analysis.
For the primary and 12-month AF detection analyses, the registry explicitly states that a hazard ratio greater than 1 indicates superiority of continuous monitoring for detecting AF.
Intention-to-treat analysis
The primary AF endpoint and several time-to-event secondary endpoints were analyzed in the intention-to-treat population, defined in the registry as all randomized subjects. This preserves the randomized treatment comparison and avoids redefining treatment groups according to events that occur after randomization.
t-test
The EQ-5D outcome used a two-sided t-test. A two-sample comparison of continuous outcomes can be expressed through a difference in group means, although the ClinicalTrials.gov record does not report the corresponding effect estimate or confidence interval for EQ-5D.
Mean difference
For OAC use and antiarrhythmic-drug use, the registry reports a mean difference in final values. The direction is explicitly defined by the registry: a positive value means that a higher percentage of subjects in the continuous-monitoring arm were using the corresponding drug at the 12-month visit.
For these endpoints, a value above 0 indicates a higher percentage in the continuous-monitoring arm according to the registry's stated interpretation.
Kaplan-Meier estimation and time-to-event endpoints
Kaplan-Meier estimation is a standard descriptive approach for displaying time-to-event data and is part of the trial's stated learning pathway. The ClinicalTrials.gov record does not explicitly identify Kaplan-Meier estimation as the reported formal method, so this page does not attribute a Kaplan-Meier analysis to the registry. Conceptually, however, Kaplan-Meier curves are useful for showing how the probability of remaining event-free changes over follow-up, while the log-rank test provides a formal group comparison.
14. Statistical Methods Explained
Why was a log-rank test used for AF detection?
AF detection is not merely a yes-or-no outcome when the timing of detection is observed. A subject whose AF is detected earlier contributes different information from a subject whose AF is detected later. The log-rank test is designed for this type of time-to-event comparison and uses information across the follow-up period.
What does an AF detection hazard ratio of 6.4 mean?
It means that the estimated instantaneous rate of AF detection was 6.4 times as high in the continuous-monitoring group as in the control group under the reported time-to-event analysis. It does not mean that 6.4 times as many subjects necessarily had AF detected, nor that every participant had a 6.4-fold probability of detection.
Why is the confidence interval so important for the primary HR?
The primary hazard ratio is 6.4, but the 95% confidence interval is 1.9–21.7. The interval communicates the uncertainty around the point estimate. Although the entire interval is above 1, its considerable width means that the precise size of the relative effect is uncertain.
Why doesn't P = 0.0006 measure the size of the treatment effect?
A P-value describes how compatible the observed data are with the null hypothesis under the specified statistical model and testing procedure. It does not quantify the magnitude of the effect. For magnitude, the hazard ratio and its confidence interval are more informative.
Why is the 12-month AF result not simply a larger version of the 6-month result?
The 6-month and 12-month analyses use different follow-up horizons. Both use time-to-event information, but extending follow-up changes the information available about when AF is detected. The HR of 7.3 at 12 months therefore should be interpreted as a separate estimate for the longer analysis period, not as a simple multiplication or confirmation of the 6-month HR of 6.4.
Why should the OAC and antiarrhythmic-drug results be interpreted differently from the primary endpoint?
Several features differ. These drug-use analyses are based on subjects who completed the specified 12-month follow-up visit rather than all randomized subjects, and the registry reports mean differences without identifying the formal statistical method. Those differences make their interpretation less directly comparable with the ITT log-rank analysis of AF detection.
15. Primary and Secondary Results at a Glance
| Endpoint | Time frame | Method | Effect measure | Estimate | 95% CI | P-value |
|---|---|---|---|---|---|---|
| AF Detection Rate Within 6 Months | 6 months | Log-rank | Hazard ratio | 6.4 | 1.9–21.7 | 0.0006 |
| AF Detection Rate Within 12 Months | 12 months | Log-rank | Hazard ratio | 7.3 | 2.6–20.8 | <0.0001 |
| Incidence of Recurrent Stroke or TIA | 12 months | Log-rank | Hazard ratio | 0.68 | 0.35–1.32 | 0.25 |
| Use of Oral Anticoagulation (OAC) Drugs | 12 months | Not reported | Mean difference | 8.8 | 2.8–14.8 | Not reported |
| Use of Antiarrhythmic Drugs | 12 months | Not reported | Mean difference | 0.4 | -2.3–3.1 | Not reported |
| Clinical Disease Burden and Care Pathway | 12 months | Log-rank | Hazard ratio | 1.37 | 0.73–2.60 | 0.33 |
| Health Outcome as Evaluated by EQ-5D Questionnaire | 12 months | Two-sided t-test | Not reported | Not reported | Not reported | 0.11 |
This table highlights an important statistical pattern in the trial: the strongest numerical evidence concerns AF detection, whereas the secondary clinical-event and patient-reported outcomes have different estimates, uncertainty, populations, and methods. The results should therefore be interpreted endpoint by endpoint rather than collapsed into a single overall statistic.
16. Multiplicity and Endpoint Interpretation
The ClinicalTrials.gov record identifies one primary endpoint and several secondary endpoints. The primary endpoint is AF detection within 6 months, while the registry also reports formal analyses for 12-month AF detection, recurrent stroke or TIA, OAC use, antiarrhythmic-drug use, clinical disease burden and care pathway, and EQ-5D health outcome.
| Endpoint role | Endpoint | Interpretive issue |
|---|---|---|
| Primary | AF Detection Rate Within 6 Months | Primary superiority comparison; formal log-rank analysis reported. |
| Secondary | AF Detection Rate Within 12 Months | Longer follow-up of the AF detection question; formal log-rank analysis reported. |
| Secondary | Recurrent Stroke or TIA | Clinical event endpoint with substantial uncertainty around the HR. |
| Secondary | OAC and antiarrhythmic-drug use | Visit-based analyses using subjects who completed the 12-month visit; formal method not reported. |
| Secondary | Clinical Disease Burden and Care Pathway | Time-to-event comparison with a CI crossing 1. |
| Secondary | EQ-5D health outcome | Two-sided t-test; effect estimate and CI not reported in the ClinicalTrials.gov record. |
Because multiple endpoints are evaluated, each P-value should be interpreted in the context of its endpoint role and the trial's prespecified statistical plan. The ClinicalTrials.gov record identifies the hypothesis type as superiority but do not provide an alpha-allocation or multiplicity-adjustment procedure. This page therefore does not infer one.
17. Missing Data, Censoring, and Analysis Population
The registry explicitly identifies the ITT population for the primary endpoint and several time-to-event secondary outcomes. For those analyses, all randomized subjects are included in the analysis population, while time-to-event methodology can account for subjects who do not experience the event during available follow-up through censoring.
The ClinicalTrials.gov record does not specify the censoring rules, missing-data imputation method, competing-risk methodology, or sensitivity analyses. Those details should not be inferred from the reported hazard ratios.
ITT protects randomization
Analyzing all randomized subjects according to randomized group preserves the principal comparison created by randomization.
Time-to-event data require censoring rules
A subject without an observed event contributes follow-up information until the relevant censoring point, but the ClinicalTrials.gov record does not specify the exact censoring rules.
Visit-based outcomes differ
OAC use, antiarrhythmic-drug use, and EQ-5D use specified populations based on 12-month follow-up information.
No imputation method reported
The ClinicalTrials.gov record does not identify a missing-data or imputation procedure.
18. Safety Results
The ClinicalTrials.gov record reports serious adverse events by randomized arm as affected subjects divided by subjects at risk. These are the only arm-specific safety results provided in the trial data.
| Safety measure | Continuous Monitoring | Control Arm |
|---|---|---|
| Serious adverse events | 68/221 | 58/220 |
The registry data do not provide a formal statistical comparison, confidence interval, or P-value for serious adverse events. Accordingly, the counts should be reported descriptively rather than converted into an unreported hypothesis test.
19. Design Features That Are Not Reported in the Supplied Data
Several statistical design features commonly discussed in clinical-trial analysis are not specified in the registry-reported CRYSTAL-AF trial data. They should not be reconstructed from the results.
| Design topic | What the ClinicalTrials.gov record reports |
|---|---|
| Non-inferiority margin | Not reported; the trial hypothesis type is superiority. |
| Crossover | Not reported. |
| Factorial design | Not reported; the design model is parallel. |
| Interim analysis | Not reported in the ClinicalTrials.gov record. |
| Alpha spending | Not reported. |
| Multiplicity adjustment | Not reported. |
| Stratification factors | Not reported. |
| Bayesian methods | Not reported. |
| Missing-data imputation | Not reported. |
| Proportional-hazards assessment | Not reported. |
This distinction is important because the absence of a reported method is not evidence that the method was not used. It means only that the ClinicalTrials.gov record does not provide enough information to attribute that method to the trial.
20. Interpreting the Primary Hazard Ratio in Context
The primary analysis estimated a substantially higher instantaneous rate of AF detection with continuous monitoring than with the control arm. The point estimate was 6.4, with a 95% CI of 1.9–21.7.
It does not say that 6.4 times as many subjects developed AF, that 640% of subjects benefited, or that each individual subject had the same relative increase in probability of detection. A hazard ratio is a time-to-event measure, not a simple percentage ratio.
The interval from 1.9 to 21.7 spans a broad range of plausible relative effects. The result is statistically separated from 1, but the point estimate should not be treated as a highly precise estimate of the true effect magnitude.
The P-value of 0.0006 provides evidence against the null hypothesis under the reported test. It does not tell us whether the HR is closer to 2, 6, or 20. The confidence interval supplies that information about statistical precision.
21. From AF Detection to Clinical Outcomes
One of the most important statistical distinctions in CRYSTAL-AF is the difference between a diagnostic endpoint and downstream clinical outcomes. The primary endpoint asks whether AF is detected. Recurrent stroke or TIA asks a different question about subsequent clinical events.
Diagnostic endpoint
AF detection within 6 months directly evaluates the study's diagnostic purpose and produced a hazard ratio of 6.4.
Longer diagnostic follow-up
AF detection within 12 months produced a hazard ratio of 7.3, using the same broad ITT time-to-event framework.
Clinical event endpoint
Recurrent stroke or TIA produced an HR of 0.68 with a 95% CI of 0.35–1.32 and P = 0.25.
Patient-reported outcome
EQ-5D at 12 months was compared using a two-sided t-test, with P = 0.11 and no effect estimate reported in the posted analysis.
These outcomes should not be treated as interchangeable. A large effect on detection does not mathematically imply a corresponding effect on recurrent stroke or TIA. Each endpoint represents a different stage of the clinical pathway and requires its own statistical interpretation.
22. Limitations
- Wide confidence intervals: the primary AF-detection hazard ratio of 6.4 has a 95% CI of 1.9–21.7, indicating substantial uncertainty about the exact magnitude of the relative effect.
- Different endpoint types: AF detection, recurrent stroke or TIA, medication use, clinical disease burden and EQ-5D measure different aspects of the study experience and should not be combined into one overall effect.
- Different analysis populations: several time-to-event analyses use all randomized subjects, whereas OAC use, antiarrhythmic-drug use, and EQ-5D use specified follow-up-based populations.
- Unreported methods: the statistical method for OAC use and antiarrhythmic-drug use is not reported in the ClinicalTrials.gov record.
- Incomplete uncertainty reporting: the EQ-5D analysis reports a P-value but no effect estimate or confidence interval in the ClinicalTrials.gov record.
- Censoring details: the ClinicalTrials.gov record does not specify censoring rules for the time-to-event analyses.
- Missing-data methodology: no imputation method is reported in the ClinicalTrials.gov record.
- Multiplicity: the ClinicalTrials.gov record does not specify a multiplicity-adjustment or alpha-allocation strategy across the primary and secondary endpoints.
- Proportional-hazards assumption: the ClinicalTrials.gov record does not report a formal assessment of this assumption, which is relevant when interpreting a single hazard ratio.
- Secondary endpoint populations: restricting visit-based analyses to subjects with specified follow-up information can affect their interpretation relative to the randomized ITT population.
- Safety inference: serious adverse events are reported as counts by arm, without a formal statistical comparison in the ClinicalTrials.gov record.
23. Why This Trial Matters Statistically
CRYSTAL-AF is a useful statistical teaching case because it connects randomized trial design with diagnostic detection, survival analysis, clinical events, treatment-use outcomes, patient-reported outcomes, and safety reporting. The trial also illustrates why the statistical meaning of an endpoint depends on both the outcome definition and the analysis population.
| Concept | How it appears in CRYSTAL-AF |
|---|---|
| Randomization | Randomized allocation to continuous monitoring or control. |
| Parallel design | Two-arm parallel trial design. |
| Intention-to-treat analysis | Primary AF detection and several secondary time-to-event outcomes use all randomized subjects. |
| Time-to-event endpoint | AF detection and several secondary outcomes incorporate event timing over follow-up. |
| Log-rank test | Reported formal method for the primary endpoint and several secondary time-to-event outcomes. |
| Hazard ratio | Primary and several secondary time-to-event effect measures. |
| Confidence interval | Shows uncertainty around the reported hazard ratios and mean differences. |
| P-value | Quantifies evidence against the null hypothesis under the reported testing framework. |
| Mean difference | Reported for OAC and antiarrhythmic-drug use. |
| t-test | Two-sided t-test reported for the EQ-5D outcome. |
| Different analysis populations | ITT is used for several efficacy endpoints, while visit-based populations are used for other outcomes. |
| Safety by arm | Serious adverse events reported as affected/at-risk counts. |
24. Related Tutorials
Learn more about the methods used in this trial:
25. Related Calculators
26. Sources
- ClinicalTrials.gov: CRYSTAL-AF, NCT00924638.
- PubMed: PMID 33984539.
- PubMed: PMID 33789592.
- PubMed: PMID 30196791.
- PubMed: PMID 26763225.
- PubMed: PMID 26182860.
Continue through the Clinical Biostats statistical pathway
Explore the statistical concepts behind randomized trials, time-to-event endpoints, hazard ratios, confidence intervals, hypothesis tests, and clinical-trial analysis.
27. Record Summary
CRYSTAL-AF provides a clear example of how statistical analysis can distinguish a diagnostic detection endpoint from downstream clinical outcomes. The primary analysis used an intention-to-treat population, a log-rank test, and a hazard ratio of 6.4 with a 95% CI of 1.9–21.7 and P = 0.0006 for AF detection within 6 months. The corresponding 12-month AF analysis reported an HR of 7.3 with a 95% CI of 2.6–20.8 and P < 0.0001.
The other outcomes illustrate why endpoint-specific interpretation is essential. Recurrent stroke or TIA had an HR of 0.68 with a 95% CI of 0.35–1.32 and P = 0.25. OAC use had a reported mean difference of 8.8 with a 95% CI of 2.8–14.8, while antiarrhythmic-drug use had a mean difference of 0.4 with a 95% CI of -2.3–3.1. The EQ-5D analysis used a two-sided t-test and reported P = 0.11 without an effect estimate in the ClinicalTrials.gov record.
The statistical story is therefore not simply that one number was significant and another was not. It involves the distinction between time-to-event and fixed-visit outcomes, hazard ratios and mean differences, ITT and visit-based populations, and effect size, precision, and statistical evidence. Those distinctions are central to interpreting randomized clinical-trial results correctly.