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
MONARCH E was a randomized, parallel-group, phase 3 trial in breast cancer evaluating abemaciclib given with standard adjuvant endocrine therapy against standard adjuvant endocrine therapy alone. The registry identifies invasive disease-free survival (IDFS) as the single registered primary endpoint and reports a formal hazard-ratio analysis using a log-rank test.
| Feature | MONARCH E |
|---|---|
| Trial name | MONARCH E |
| NCT identifier | NCT03155997 |
| Phase | Phase 3 |
| Condition | Breast Cancer |
| Brief title | Endocrine Therapy With or Without Abemaciclib (LY2835219) Following Surgery in Participants With Breast Cancer |
| Allocation | Randomized |
| Design model | Parallel |
| Masking | None |
| Primary purpose | Treatment |
| Enrollment | 5637 |
| Interventions | Abemaciclib; Standard Adjuvant Endocrine Therapy |
| Trial status | Active, not recruiting |
| Lead sponsor | Eli Lilly and Company |
| Sponsor type | Industry |
| Start date | 2017-07-12 |
| Primary completion | 2020-03-16 |
2. Clinical Question
The central statistical question was whether adding abemaciclib to standard adjuvant endocrine therapy changes the time from randomization to invasive disease-free survival events compared with standard adjuvant endocrine therapy alone.
Population
Participants with breast cancer enrolled in the MONARCH E phase 3 randomized trial following surgery.
Intervention
150 mg Abemaciclib plus Endocrine Therapy.
Comparator
Endocrine Therapy.
Primary question
Does the addition of abemaciclib improve invasive disease-free survival relative to endocrine therapy alone?
3. Trial Design
150 mg Abemaciclib + Endocrine Therapy
- Abemaciclib
- Standard adjuvant endocrine therapy
- Serious adverse events: 344/2791 affected/at risk
Endocrine Therapy
- Standard adjuvant endocrine therapy
- No masking
- Serious adverse events: 202/2800 affected/at risk
The available registry data establish a randomized, parallel, unmasked phase 3 comparison. They do not provide a factorial component, crossover procedure, non-inferiority margin, Bayesian analysis, or an interim-analysis rule. Those design features therefore are not part of this statistical reconstruction.
4. Randomization, Stratification, and Analysis Populations
Randomization is the key design feature that creates the basis for comparing outcomes between the two treatment strategies. In a randomized trial, treatment assignment is determined before the outcome is observed, which helps separate treatment assignment from prognostic characteristics on average across the randomized population.
The primary IDFS analysis is explicitly described as a stratified analysis. The registry analysis notes identify stratification by Interactive Web Response Systems (IWRS) Geographical Region, IWRS Prior Treatment, and IWRS Menopausal Status. These factors therefore form part of the reported statistical comparison.
| Analysis population | Registry description |
|---|---|
| Primary IDFS population | All randomized participants, including censored participants. |
| Abemaciclib + endocrine therapy censored | 2672 participants were censored. |
| Endocrine therapy censored | 2642 participants were censored. |
| DRFS population | All randomized participants, including censored participants. |
| DRFS censored in abemaciclib group | 2702 participants were censored. |
| DRFS censored in endocrine-therapy group | 2677 participants were censored. |
The use of censored participants is important in time-to-event analysis. A participant who has not experienced the specified event by the available follow-up can still contribute information up to the point of censoring. Excluding all such participants would discard information that survival methods are specifically designed to use.
5. Primary Endpoint
| Endpoint | Registry definition | Time frame |
|---|---|---|
| Invasive Disease Free Survival (IDFS) | IDFS, as defined by the STEEP System, was measured from the date of randomization to the date of first occurrence of one of the following events: ipsilateral invasive breast tumor recurrence, regional invasive breast cancer recurrence, distant recurrence, contralateral invasive breast cancer, second primary non-breast invasive cancer, death attributable to any cause. | Baseline to Recurrence or Death from Any Cause (Up to 32 Months) |
Statistically, IDFS is a composite time-to-event endpoint. The event is not limited to recurrence in the originally treated breast. The registry definition includes several types of invasive recurrence, contralateral invasive breast cancer, a second primary non-breast invasive cancer, and death from any cause.
6. Secondary Endpoint
| Endpoint | Definition / time frame | Reported estimate |
|---|---|---|
| Distant Relapse-Free Survival (DRFS) | Baseline to Distant Recurrence or Death from Any Cause (Up to 32 Months) | HR 0.717; 95% CI 0.559–0.920 |
The registry reports a hazard ratio and a two-sided 95% confidence interval for DRFS, with the comparison stratified by IWRS Geographical Region, IWRS Prior Treatment, and IWRS Menopausal Status. The ClinicalTrials.gov record does not identify a formal statistical method for this secondary endpoint.
7. Statistical Methodology
Time-to-event analysis
Both IDFS and DRFS are time-to-event endpoints. Rather than asking only whether an event occurred, these analyses incorporate when the event occurred and allow participants without an observed event during follow-up to contribute censored information.
For IDFS, the event definition is the first occurrence of any event specified by the registered STEEP-based definition. For DRFS, the registered event is distant recurrence or death from any cause.
Kaplan-Meier estimation
Kaplan-Meier estimation is the standard descriptive framework for displaying time-to-event distributions. It estimates the probability of remaining event-free over time while accounting for censoring. The MONARCH E registry analysis identifies the endpoints as time-to-event and reports a hazard ratio analysis; it does not separately list Kaplan-Meier estimation as a method.
Here, di represents the number of events at event time ti, while ni represents the number at risk immediately before that time.
Log-rank test
The reported primary IDFS comparison used a log-rank test. The log-rank test compares the observed and expected numbers of events between treatment groups over follow-up, taking account of the ordering of event times.
Because the analysis was stratified, the comparison was not simply an unstratified test pooling every participant together. Stratification allows the treatment comparison to account for the prespecified IWRS factors recorded in the analysis.
Hazard ratio
The reported treatment effect is a hazard ratio (HR). An HR below 1 indicates a lower estimated instantaneous event rate in the abemaciclib-plus-endocrine-therapy group relative to endocrine therapy alone, within the time-to-event model underlying the reported estimate.
For MONARCH E, the primary IDFS estimate of 0.747 corresponds to an estimated hazard that is 74.7% of the comparator hazard under the reported analysis. The complementary interpretation is approximately a 25.3% lower estimated hazard, calculated directly as 1 − 0.747.
Stratified analysis
The primary analysis was stratified by IWRS Geographical Region, IWRS Prior Treatment, and IWRS Menopausal Status. In a stratified survival comparison, information within the defined strata contributes to the overall treatment comparison while allowing baseline event patterns to differ across strata.
This is different from adjusting for a continuous covariate in a conventional regression model. Stratification preserves separate baseline risk structures for the specified strata rather than forcing a single baseline hazard across them.
Superiority hypothesis
The registered hypothesis type for the primary analysis is superiority. This is conceptually different from non-inferiority testing. A superiority analysis asks whether the evidence supports a difference in favor of the intervention, whereas non-inferiority requires comparison with a prespecified clinically acceptable margin. No non-inferiority margin is reported in the registry-reported MONARCH E data.
8. Results: Invasive Disease-Free Survival
The primary endpoint analysis compared 150 mg Abemaciclib plus Endocrine Therapy with Endocrine Therapy among all randomized participants, including censored participants. The registry reports a stratified log-rank analysis with a hazard ratio as the effect measure.
Primary IDFS treatment effect
95% CI: 0.598–0.932 · P = 0.00957
Comparison: 150 mg Abemaciclib + Endocrine Therapy vs Endocrine Therapy
| Primary endpoint | Abemaciclib + Endocrine Therapy | Endocrine Therapy | Reported analysis |
|---|---|---|---|
| Invasive Disease Free Survival (IDFS) | 2672 censored participants | 2642 censored participants | Stratified Log Rank; HR 0.747 (95% CI 0.598–0.932); P = 0.00957 |
The hazard ratio of 0.747 means that, under the reported time-to-event analysis, the estimated instantaneous rate of an IDFS event in the abemaciclib-plus-endocrine-therapy group was about 74.7% of the corresponding rate in the endocrine-therapy group. Expressed as the complementary relative reduction in estimated hazard, this is approximately 25.3%.
The HR does not mean that 25.3% of participants avoided an event, that every participant experienced a 25.3% reduction, or that the absolute probability of an IDFS event was reduced by 25.3 percentage points. A hazard ratio is a relative time-to-event measure, not an absolute risk difference.
The 95% confidence interval of 0.598–0.932 describes statistical uncertainty around the estimated hazard ratio under the analysis framework. It does not describe the range of individual patient responses. Because the interval remains below 1, the reported estimate is consistent with a lower event hazard for the intervention group across the confidence interval.
The P = 0.00957 value addresses evidence against the null hypothesis in the reported statistical testing framework. It is not a measure of the size or clinical importance of the treatment effect. Effect size is conveyed by the hazard ratio and its confidence interval, while the p-value describes evidence against the null under the specified testing framework.
The analysis is based on time-to-event data and includes censored participants. Interpretation of a hazard ratio also depends on the survival-analysis model and, where a proportional-hazards interpretation is invoked, on the adequacy of the proportional-hazards assumption. The ClinicalTrials.gov record does not provide enough information to independently assess that assumption.
9. Results: Distant Relapse-Free Survival
DRFS was reported as a secondary time-to-event endpoint. The registry compared 150 mg Abemaciclib plus Endocrine Therapy with Endocrine Therapy and reports a hazard ratio with a two-sided 95% confidence interval.
Secondary DRFS treatment effect
95% CI: 0.559–0.920
Time frame: Baseline to Distant Recurrence or Death from Any Cause (Up to 32 Months)
| Secondary endpoint | Estimate | 95% CI | Analysis population |
|---|---|---|---|
| Distant Relapse-Free Survival (DRFS) | HR 0.717 | 0.559–0.920 | All randomized participants, including censored participants |
The ClinicalTrials.gov record does not report a p-value or a formal statistical method for the DRFS comparison. It does identify stratification by IWRS Geographical Region, IWRS Prior Treatment, and IWRS Menopausal Status.
An HR of 0.717 corresponds to approximately a 28.3% lower estimated hazard, calculated as 1 − 0.717. This is an interpretation of the reported relative effect and should not be converted into an absolute reduction in distant recurrence or death.
10. Understanding the Censoring in MONARCH E
Censoring is central to interpreting both reported survival analyses. In the primary IDFS analysis, 2672 participants in the abemaciclib-plus-endocrine-therapy group and 2642 participants in the endocrine-therapy group were censored. In the DRFS analysis, the corresponding numbers were 2702 and 2677.
What censoring means
A censored participant contributes information up to the point at which their event-free follow-up is no longer observed for the analysis.
What censoring does not mean
A censored participant should not automatically be interpreted as having remained event-free indefinitely.
Why survival methods use it
Time-to-event methods are specifically constructed to use partial follow-up rather than discarding participants whose complete event history is unavailable.
Interpretive caution
The validity of survival estimates depends on the assumptions governing censoring and follow-up. The ClinicalTrials.gov record does not provide enough detail to evaluate those assumptions directly.
11. Statistical Methods Explained
Why was a log-rank test used for IDFS?
IDFS is a time-to-event endpoint, so a simple comparison of proportions at a single time point would discard much of the available follow-up information. The log-rank test instead compares the event experience of the randomized groups across the observed follow-up period while accommodating censoring.
What does an HR of 0.747 mean?
An HR of 0.747 means that the estimated instantaneous rate of an IDFS event in the abemaciclib-plus-endocrine-therapy group was 0.747 times that of the endocrine-therapy group under the reported analysis. The complementary calculation, 1 − 0.747, gives approximately a 25.3% lower estimated hazard.
That statement is about the hazard, not an absolute event probability. It does not say that 25.3% fewer participants experienced an event.
Why is the confidence interval important?
The 95% confidence interval of 0.598–0.932 shows the statistical uncertainty around the primary HR estimate. A narrower interval would indicate greater precision; a wider interval would indicate less precision. The interval should not be interpreted as a range containing the treatment effect for 95% of individual patients.
Why does the p-value not measure effect size?
The p-value of 0.00957 describes the evidence against the null hypothesis in the reported primary testing framework. It is affected by both the observed data and the amount of information available. It does not tell us whether the treatment effect is large or small. The HR and confidence interval provide the more direct description of the relative effect and its precision.
Why does stratification matter?
The primary IDFS analysis was stratified by IWRS Geographical Region, IWRS Prior Treatment, and IWRS Menopausal Status. Stratification allows the comparison to account for differences in the underlying event experience associated with these predefined strata rather than treating the entire randomized population as one homogeneous risk set.
Does an HR automatically mean proportional hazards?
Not necessarily. A hazard ratio is a relative comparison of event rates under a time-to-event model, but the familiar interpretation of one constant HR over time relies on a proportional-hazards framework. The registry-reported MONARCH E registry data identify the hazard ratio but do not provide sufficient model diagnostics to determine whether proportional hazards hold throughout follow-up.
Why is the secondary DRFS p-value not reported here?
The registry statistical-analysis record reports an HR of 0.717 and a two-sided 95% confidence interval of 0.559–0.920 for DRFS, but it does not report a p-value or a formal statistical method for that analysis. A statistical analysis page should not manufacture a p-value from the confidence interval when the registry does not report one.
12. Primary Endpoint vs Secondary Endpoint
| Endpoint | Role | Effect measure | Formal method reported | P-value reported |
|---|---|---|---|---|
| Invasive Disease Free Survival (IDFS) | Primary | HR 0.747; 95% CI 0.598–0.932 | Stratified Log Rank | 0.00957 |
| Distant Relapse-Free Survival (DRFS) | Secondary | HR 0.717; 95% CI 0.559–0.920 | Not reported in registry-reported registry analysis | Not reported in registry-reported registry analysis |
This distinction matters statistically. A primary endpoint is the principal outcome specified for the trial's confirmatory question. A secondary endpoint can provide additional evidence about the treatment effect, but its interpretation depends on the prespecified statistical hierarchy and multiplicity procedures.
The registry-reported MONARCH E data identify the primary hypothesis as superiority, but they do not provide an alpha-allocation scheme, multiplicity adjustment procedure, or endpoint hierarchy beyond identifying IDFS as the registered primary endpoint. Those details should therefore not be inferred.
13. Safety Results
The registry provides serious adverse event counts by treatment arm. These are presented as affected participants over participants at risk.
| Safety measure | 150 mg Abemaciclib + Endocrine Therapy | Endocrine Therapy |
|---|---|---|
| Serious adverse events | 344/2791 | 202/2800 |
The reported serious-adverse-event figures are descriptive safety results. They should not be treated as directly interchangeable with the efficacy hazard ratios because they represent a different outcome domain and are expressed as affected participants over participants at risk rather than as a time-to-event treatment effect.
14. What the Hazard Ratio Does — and Does Not — Mean
The primary IDFS HR of 0.747 indicates a lower estimated instantaneous rate of the registered IDFS event in the abemaciclib-plus-endocrine-therapy group than in the endocrine-therapy group. The complementary relative-hazard interpretation is approximately 25.3% lower estimated hazard.
An HR of 0.747 does not mean that the absolute probability of an IDFS event decreased by 25.3 percentage points. Absolute risk depends on the baseline event rate and follow-up time. The ClinicalTrials.gov record does not provide time-specific IDFS probabilities, so an absolute risk reduction should not be calculated here.
The HR is a population-level comparative measure. It does not imply that every participant receiving abemaciclib experienced the same proportional reduction in event hazard.
The 95% CI of 0.598–0.932 quantifies uncertainty around the primary estimate. It does not provide a distribution of individual treatment effects and should not be interpreted as the range of outcomes that patients can expect individually.
The p-value of 0.00957 addresses evidence against the null hypothesis in the reported superiority analysis. It does not measure clinical magnitude, probability of treatment benefit, or the probability that the null hypothesis is true.
15. Statistical Interpretation of the Secondary DRFS Result
The DRFS hazard ratio of 0.717 is directionally consistent with the primary IDFS hazard ratio because both estimates are below 1. The DRFS 95% confidence interval of 0.559–0.920 also lies below 1.
However, statistical interpretation should distinguish this descriptive consistency from a formal claim about multiplicity-adjusted confirmation. The ClinicalTrials.gov record does not provide a p-value, formal DRFS method, or multiplicity procedure. Consequently, the most precise statement is that the registry reports a hazard-ratio estimate and confidence interval favoring the abemaciclib-plus-endocrine-therapy comparison for this secondary endpoint.
IDFS
Primary endpoint; HR 0.747; 95% CI 0.598–0.932; P = 0.00957; stratified log-rank analysis.
DRFS
Secondary endpoint; HR 0.717; 95% CI 0.559–0.920; no formal method or p-value reported in the ClinicalTrials.gov record.
16. Design Features That Are Not Reported
The available MONARCH E data are sufficiently detailed to reconstruct the primary time-to-event comparison, but several statistical-design topics requested for some trial records are not present in the ClinicalTrials.gov record.
| Design topic | Available information |
|---|---|
| Non-inferiority margin | Not reported; the registered hypothesis is superiority. |
| Crossover | Not reported in the ClinicalTrials.gov record. |
| Factorial design | Not reported; the design model is parallel. |
| Multiplicity adjustment | Not reported in the ClinicalTrials.gov record. |
| Interim analysis | Not reported in the ClinicalTrials.gov record. |
| Missing-data or imputation method | Not reported in the ClinicalTrials.gov record. |
| Bayesian methods | Not reported in the ClinicalTrials.gov record. |
| Primary statistical method | Log-rank test, with stratified analysis and hazard ratio as the effect measure. |
These omissions are methodological boundaries rather than evidence that the corresponding procedures were absent from the underlying protocol or statistical analysis plan. The ClinicalTrials.gov record simply do not provide those details, so this page does not infer them.
17. Why the Primary Analysis Population Matters
The registry specifies that the IDFS analysis used all randomized participants, including the censored participants. This is important because randomization establishes the treatment comparison before outcomes are observed.
Using the randomized population helps preserve the comparability created by random assignment. In contrast, restricting the analysis only to participants who remained on treatment could introduce selection because continued treatment can itself be related to tolerability, disease status, adherence, or other post-randomization factors.
For the primary IDFS result, the registry explicitly anchors the analysis to all randomized participants and accounts for censored participants within the survival analysis.
18. Reading the Primary Result in Context
There are three separate statistical questions embedded in the reported IDFS result.
1. Direction
Is the estimated relative event hazard above or below 1? The reported HR of 0.747 is below 1.
2. Precision
How uncertain is the estimate? The 95% CI is 0.598–0.932.
3. Statistical evidence
How much evidence is reported against the null? The reported two-sided p-value is 0.00957.
4. Clinical meaning
What does the effect mean for patients? That requires absolute event probabilities, follow-up-specific estimates, adverse-event context, and other clinical information not contained in the ClinicalTrials.gov record.
Keeping these questions separate prevents a common statistical error: treating a small p-value as though it were itself a measure of treatment magnitude. The p-value and the effect estimate serve different purposes.
19. Primary vs Secondary Endpoint Interpretation
IDFS and DRFS are both time-to-event outcomes, but they answer somewhat different questions because their event definitions differ. IDFS includes several invasive recurrence and death components, whereas DRFS focuses on distant recurrence or death from any cause.
| Feature | IDFS | DRFS |
|---|---|---|
| Role | Primary | Secondary |
| Time frame | Baseline to Recurrence or Death from Any Cause (Up to 32 Months) | Baseline to Distant Recurrence or Death from Any Cause (Up to 32 Months) |
| Effect measure | HR 0.747 | HR 0.717 |
| 95% CI | 0.598–0.932 | 0.559–0.920 |
| P-value | 0.00957 | Not reported |
| Formal method reported | Log Rank | Not reported |
| Stratification | IWRS Geographical Region, IWRS Prior Treatment, IWRS Menopausal Status | IWRS Geographical Region, IWRS Prior Treatment, IWRS Menopausal Status |
The two estimates should not be treated as interchangeable endpoints. Their definitions differ, and the primary endpoint carries a different confirmatory role from the secondary endpoint.
20. Limitations
- Limited reported statistical detail: the ClinicalTrials.gov record identifies the primary log-rank method and hazard ratio but does not provide the full statistical analysis plan.
- Secondary-method uncertainty: the DRFS result has an HR and confidence interval, but the ClinicalTrials.gov record does not identify the formal statistical method or p-value.
- No absolute time-specific estimates: the ClinicalTrials.gov record does not provide Kaplan-Meier survival probabilities at specific time points, medians, or absolute risk differences.
- No event counts by treatment arm: the ClinicalTrials.gov record provides censoring counts but not the corresponding IDFS or DRFS event counts by arm.
- Composite primary endpoint: IDFS combines multiple clinically different event types, so the overall HR should not be interpreted as an effect estimate for any single component.
- Censoring assumptions: survival-analysis validity depends on assumptions concerning censoring and follow-up. The ClinicalTrials.gov record does not provide enough information to evaluate these assumptions.
- Hazard-ratio interpretation: a single HR is most straightforward when the relative hazards are reasonably stable over time. The ClinicalTrials.gov record does not provide proportional-hazards diagnostics.
- Multiplicity information: the ClinicalTrials.gov record identifies a primary and a secondary endpoint but do not provide the multiplicity-control procedure, so the secondary result should not be assigned an unreported confirmatory error-control interpretation.
- Safety comparison: serious adverse events are reported as affected/at-risk counts, but no formal statistical comparison is provided in the ClinicalTrials.gov record.
- Generalizability: the available registry information does not provide the detailed baseline characteristics needed to assess how closely the randomized population represents other breast-cancer populations.
21. Why This Trial Matters Statistically
MONARCH E is a useful statistical teaching case because the registry data bring together randomization, stratification, censoring, a composite time-to-event primary endpoint, a stratified log-rank test, and hazard-ratio interpretation in a single phase 3 comparison.
| Concept | How it appears in MONARCH E |
|---|---|
| Randomization | The allocation is randomized across two parallel treatment groups. |
| Time-to-event analysis | IDFS is measured from randomization to the first qualifying event; DRFS is measured from randomization to distant recurrence or death. |
| Censoring | The primary analysis includes censored participants; 2672 and 2642 participants were censored in the two IDFS groups. |
| Stratified analysis | The primary analysis is stratified by IWRS Geographical Region, IWRS Prior Treatment, and IWRS Menopausal Status. |
| Log-rank test | The reported formal method for the primary IDFS comparison. |
| Hazard ratio | HR 0.747 for IDFS and HR 0.717 for DRFS. |
| Confidence interval | The primary IDFS 95% CI is 0.598–0.932; the DRFS 95% CI is 0.559–0.920. |
| Superiority testing | The primary hypothesis type is reported as superiority. |
| Composite endpoint | IDFS includes multiple invasive recurrence, second-primary-cancer, and death events. |
| Safety analysis | Serious adverse events are reported separately by treatment arm. |
22. A Practical Workflow for Analyzing MONARCH E
This workflow illustrates why clinical-trial statistics should not begin with the p-value. First define exactly what counts as an event, establish the randomized comparison, account for censoring, specify the comparison method, and then interpret the effect estimate together with its uncertainty.
23. What the Registry Data Support — and What They Do Not
| Question | Supported by the ClinicalTrials.gov record? |
|---|---|
| Was the trial randomized? | Yes. |
| Was the design parallel? | Yes. |
| Was the trial masked? | No; masking is reported as none. |
| What was the primary endpoint? | IDFS. |
| What was the primary statistical method? | Stratified log-rank analysis. |
| What was the primary HR? | 0.747. |
| What was the primary 95% CI? | 0.598–0.932. |
| What was the primary p-value? | 0.00957. |
| Was DRFS reported? | Yes. |
| Was a DRFS HR reported? | Yes, 0.717. |
| Was a DRFS p-value reported? | No, not in the ClinicalTrials.gov record. |
| Were serious adverse events reported by arm? | Yes. |
| Were median survival times provided? | No. |
| Were subgroup results provided? | No. |
| Was a non-inferiority margin provided? | No. |
| Was a Bayesian analysis provided? | No. |
| Was an interim-analysis procedure provided? | No. |
This distinction is important for reproducible statistical reporting. A complete analysis should be detailed where the registry supplies evidence and deliberately restrained where the registry does not provide the necessary information.
24. Related Tutorials
Learn more about the methods used in this trial:
25. Related Statistical Calculators
26. Sources
- ClinicalTrials.gov: MONARCH E — NCT03155997.
- PubMed: Publication associated with MONARCH E.
- PubMed: Publication associated with MONARCH E.
- PubMed: Publication associated with MONARCH E.
- PubMed: Publication associated with MONARCH E.
- PubMed: Publication associated with MONARCH E.
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27. Record Summary
MONARCH E provides a clear example of randomized time-to-event analysis in a phase 3 oncology trial. The primary endpoint, invasive disease-free survival, was defined from randomization to the first occurrence of a broad set of invasive recurrence, second-primary-cancer, or death events. The primary comparison used a stratified log-rank test and reported a hazard ratio of 0.747 with a 95% confidence interval of 0.598–0.932 and a p-value of 0.00957.
The secondary distant relapse-free survival analysis reported an HR of 0.717 with a 95% confidence interval of 0.559–0.920, although the ClinicalTrials.gov record does not identify a formal statistical method or p-value for that analysis. Serious adverse events were reported as 344/2791 in the abemaciclib-plus-endocrine-therapy group and 202/2800 in the endocrine-therapy group.
The most useful statistical interpretation therefore combines the hazard ratio, confidence interval, reported p-value, endpoint definition, randomized analysis population, censoring, and stratified analysis structure. Just as importantly, the interpretation should stop where the ClinicalTrials.gov record stop: no unreported subgroup estimates, median event times, interim rules, multiplicity procedures, or model specifications are added.