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Advanced Breast Cancer Phase 3 Randomized NCT01958021

MONALEESA-2: Complete Statistical Analysis of Ribociclib in Advanced Breast Cancer

An independent statistical analysis of the randomized phase 3 MONALEESA-2 trial evaluating ribociclib plus letrozole versus placebo plus letrozole in postmenopausal women with advanced or metastatic breast cancer.

Trial status: Completed  ·  Enrollment: 668  ·  Primary completion: January 29, 2016
Scope of this record

This page provides an independent statistical analysis and educational interpretation of publicly reported results. ClinicalTrials.gov provides the official trial registry record. Numerical trial results on this page are restricted to the ClinicalTrials.gov record.

1. Trial at a Glance

MONALEESA-2 was a randomized, quadruple-masked, parallel-group phase 3 study of ribociclib plus letrozole versus placebo plus letrozole in postmenopausal women with advanced or metastatic breast cancer. The trial enrolled 668 participants and posted four statistical analyses, including a formal analysis of the primary progression-free survival endpoint.

668
Enrollment
2 treatment arms
3
Phase
Phase 3
0.556
Primary PFS HR
95% CI 0.429–0.720
0.00000329
Primary PFS P-value
Two-sided
FeatureMONALEESA-2
Trial nameMONALEESA-2
NCT identifierNCT01958021
Brief titleStudy of Efficacy and Safety of LEE011 in Postmenopausal Women With Advanced Breast Cancer
PhasePhase 3
StatusCompleted
Enrollment668
AllocationRandomized
Design modelParallel
MaskingQuadruple
Primary purposeTreatment
Lead sponsorNovartis Pharmaceuticals
Sponsor typeIndustry
ConditionsAdvanced, Metastatic Breast Cancer
StartDecember 17, 2013
Primary completionJanuary 29, 2016

2. Clinical Question

The trial addresses whether adding ribociclib to letrozole improves clinical outcomes compared with letrozole plus placebo in postmenopausal women with advanced or metastatic breast cancer. The registered primary endpoint was progression-free survival by investigator assessment.

Population

Postmenopausal women with advanced or metastatic breast cancer, as specified by the trial's brief title and condition description.

Intervention

Ribociclib plus letrozole.

Comparator

Placebo plus letrozole.

Primary question

Does ribociclib plus letrozole improve progression-free survival compared with placebo plus letrozole?

3. Trial Design

01
Randomize668 participants
02
Parallel arms2 groups
03
Quadruple maskingMasked trial
04
Assess PFSInvestigator assessment
05
AnalyzeTime-to-event comparison
INTERVENTION ARM

Ribociclib + Letrozole

  • Ribociclib
  • Letrozole
  • Serious adverse events affected 108 of 334 participants in the registry-reported arm-level safety data.
CONTROL ARM

Placebo + Letrozole

  • Placebo
  • Letrozole
  • Serious adverse events affected 62 of 330 participants in the registry-reported arm-level safety data.
Design interpretation. Randomization creates the basis for comparing outcomes between the two treatment assignments. The parallel design means participants are assigned to one of the two study groups rather than sequentially receiving both randomized regimens. Quadruple masking indicates that the registry classifies the study as masked at four levels, but the ClinicalTrials.gov record does not specify the individual roles included in that classification.

4. Analysis Population and Statistical Framework

The posted statistical analyses specify the Full Analysis Set (FAS), including all randomized participants, for the primary progression-free survival analysis and the three secondary analyses reported in the ClinicalTrials.gov record.

EndpointAnalysis populationComparisonMethod
Progression-free survivalFAS including all randomized participantsRibociclib + letrozole vs placebo + letrozoleLog-rank test
Overall survivalFAS including all randomized participantsRibociclib + letrozole vs placebo + letrozoleLog-rank test
Overall response rateFAS including all randomized participantsRibociclib + letrozole vs placebo + letrozoleCochran-Mantel-Haenszel test
Clinical benefit rateFAS including all randomized participantsRibociclib + letrozole vs placebo + letrozoleCochran-Mantel-Haenszel test

The registry data identifies two principal statistical method families: the log-rank test for time-to-event outcomes and the Cochran-Mantel-Haenszel test for binary outcomes. The primary hypothesis type and the secondary analyses are described as superiority comparisons.

5. Endpoints

EndpointRegistry definition / descriptionTime frameType
Progression Free Survival (PFS) by Investigator Assessment PFS was defined as the period starting from the date of randomization to the date of the first documented progression or death caused by any reason. In cases where patients did not experience an event, PFS was censored at the date of the last adequate tumor assessment. Clinical deterioration without objective radiological evidence was not considered as documented disease progression. Up to 23 months Time-to-event
Overall Survival (OS) Overall survival Up to approximately 87 months Time-to-event
Overall Response Rate (ORR) by Investigator Assessment Overall response rate by investigator assessment Up to 23 months Binary
Clinical Benefit Rate (CBR) by Investigator Assessment Clinical benefit rate by investigator assessment Up to 23 months Binary

The registry lists one primary endpoint: progression-free survival by investigator assessment. The other three statistical analyses reported in the ClinicalTrials.gov record are secondary endpoints.

6. Statistical Methodology

Time-to-event analysis

Progression-free survival and overall survival are time-to-event endpoints. Unlike a simple binary outcome, these endpoints retain information about when an event occurred and can also accommodate participants whose event status is not observed by the end of follow-up.

For PFS in MONALEESA-2, the registry definition begins at randomization and ends at the first documented progression or death from any reason. Participants without an event were censored at the date of their last adequate tumor assessment. This makes censoring part of the statistical definition of the endpoint rather than merely an administrative detail.

Conceptual survival function
S(t) = P(T > t)

A survival function represents the probability that the event time exceeds a specified time. In a clinical trial, Kaplan-Meier estimation is a standard way to estimate this function in the presence of right-censored observations.

Log-rank test

The registry reports the log-rank test for both PFS and OS. The log-rank procedure compares the observed pattern of events between treatment groups over follow-up rather than comparing only a single time point.

For the primary PFS endpoint, the analysis therefore asks whether the observed time-to-progression-or-death experience differs between the randomized ribociclib-plus-letrozole group and the placebo-plus-letrozole group.

Hazard ratio

The primary and OS analyses use the hazard ratio as their reported effect measure. A hazard ratio compares the estimated instantaneous event rates between the treatment groups over the analyzed follow-up.

Interpretation of the hazard ratio
HR < 1  →  lower estimated event hazard in the ribociclib + letrozole group

A hazard ratio is a relative time-to-event measure. It is not a probability, not a median survival time, and not the percentage of patients who benefit.

Cochran-Mantel-Haenszel test

The registry reports the Cochran-Mantel-Haenszel test for overall response rate and clinical benefit rate. This is a categorical-data method that can compare binary outcomes while accounting for stratification variables when such strata are part of the analysis specification.

The ClinicalTrials.gov record does not identify the specific stratification variables used for these analyses, so no particular stratification scheme is inferred here.

Full Analysis Set

All four posted analyses identify the Full Analysis Set as including all randomized participants. This is important because analyzing participants according to randomized assignment preserves the treatment comparison established by randomization rather than restricting the primary efficacy comparison only to participants who completed treatment.

7. Primary Result: Progression-Free Survival

The primary endpoint was progression-free survival by investigator assessment, measured for up to 23 months. The analysis used a log-rank test in the Full Analysis Set, including all randomized participants. The comparison was ribociclib plus letrozole versus placebo plus letrozole.

Hazard ratio for progression or death

0.556

95% CI: 0.429–0.720   ·   P = 0.00000329

Two-sided confidence interval · Superiority hypothesis

Primary endpointResult
EndpointProgression Free Survival (PFS) by Investigator Assessment
Time frameUp to 23 months
Analysis populationFull Analysis Set, including all randomized participants
MethodLog-rank test
Effect measureHazard ratio
Hazard ratio0.556
95% CI0.429–0.720
P-value0.00000329
HypothesisSuperiority
Clinical Biostats interpretation

The hazard ratio of 0.556 means that, within the statistical framework represented by the reported time-to-event analysis, the estimated instantaneous hazard of progression or death was approximately 55.6% as high with ribociclib plus letrozole as with placebo plus letrozole. Expressed as a relative reduction in estimated hazard, this corresponds to approximately a 44.4% lower estimated hazard.

That interpretation does not mean that 44.4% of participants avoided progression, that 44.4% of participants benefited, or that each participant had exactly a 44.4% reduction in risk. A hazard ratio is a relative time-to-event effect measure, not an individual probability.

The 95% confidence interval of 0.429–0.720 describes statistical uncertainty around the estimated hazard ratio. It indicates that the estimate is not being presented as an exact fixed quantity; the interval represents the uncertainty associated with the estimate under the relevant statistical framework.

The P-value of 0.00000329 addresses evidence against the null hypothesis in the reported statistical test. It does not measure the size or clinical importance of the treatment effect. Effect magnitude is conveyed by the hazard ratio and its confidence interval.

Because PFS includes censoring, interpretation also depends on the endpoint's censoring rules. The registry specifically states that participants without an event were censored at the date of the last adequate tumor assessment. The ClinicalTrials.gov record does not report a separate assessment of the proportional-hazards assumption, so no such assumption check is attributed to this trial record.

8. Secondary Result: Overall Survival

Overall survival was a secondary time-to-event endpoint with a time frame of up to approximately 87 months. The Full Analysis Set was compared using a log-rank test, with hazard ratio as the effect measure.

Hazard ratio for overall survival

0.765

95% CI: 0.628–0.932   ·   P = 0.004

Two-sided confidence interval · Superiority hypothesis

Secondary endpointResult
EndpointOverall Survival (OS)
Time frameUp to approximately 87 months
Analysis populationFull Analysis Set, including all randomized participants
MethodLog-rank test
Effect measureHazard ratio
Hazard ratio0.765
95% CI0.628–0.932
P-value0.004
HypothesisSuperiority
Clinical Biostats interpretation

The OS hazard ratio of 0.765 corresponds to an estimated instantaneous hazard of death approximately 76.5% as high in the ribociclib-plus-letrozole group as in the placebo-plus-letrozole group, or approximately a 23.5% lower estimated hazard under the reported analysis.

This does not mean that 23.5% of participants were prevented from dying, nor does it describe an absolute difference in survival probability. A hazard ratio summarizes a relative time-to-event comparison.

The 95% confidence interval of 0.628–0.932 expresses uncertainty around the estimated hazard ratio. It is not an interval containing the outcomes of individual participants and does not state that individual treatment effects must fall between those two numbers.

The P-value of 0.004 measures the statistical evidence against the null hypothesis under the reported test. It should not be interpreted as a 0.4% probability that the treatment effect is real, nor as a measure of effect magnitude.

OS is less directly tied to tumor-assessment censoring than PFS because death is the event itself, but time-to-event interpretation still depends on follow-up, censoring, and the analysis framework. The ClinicalTrials.gov record does not provide additional information about proportional-hazards diagnostics or alternative survival models.

9. Secondary Result: Overall Response Rate

Overall response rate by investigator assessment was a secondary binary endpoint with a time frame of up to 23 months. The analysis used the Full Analysis Set and a Cochran-Mantel-Haenszel test.

Statistical comparison

P = 0.000155

Cochran-Mantel-Haenszel test · Superiority hypothesis

The registry analysis does not provide an effect estimate or confidence interval for this endpoint.

EndpointResult
OutcomeOverall Response Rate (ORR) by Investigator Assessment
Time frameUp to 23 months
Endpoint typeBinary
Analysis populationFull Analysis Set, including all randomized participants
MethodCochran-Mantel-Haenszel test
P-value0.000155
HypothesisSuperiority
Effect estimate / CINot included in the ClinicalTrials.gov record
Clinical Biostats interpretation

The reported P-value of 0.000155 indicates strong statistical evidence against the null hypothesis under the reported Cochran-Mantel-Haenszel test. However, the ClinicalTrials.gov record does not provide the actual response rates, an absolute difference, a risk ratio, an odds ratio, or a confidence interval.

Consequently, the P-value alone cannot tell us how large the difference in response was. Two trials can have similarly small P-values with very different effect sizes, depending on sample size and outcome variability.

The binary nature of ORR also makes it conceptually different from PFS and OS. ORR reduces the response experience to whether a participant meets the prespecified response classification, whereas time-to-event endpoints incorporate the timing of events.

10. Secondary Result: Clinical Benefit Rate

Clinical benefit rate by investigator assessment was another secondary binary endpoint, evaluated for up to 23 months. The analysis used the Full Analysis Set and the Cochran-Mantel-Haenszel test.

Statistical comparison

P = 0.018

Cochran-Mantel-Haenszel test · Superiority hypothesis

The registry analysis does not provide an effect estimate or confidence interval for this endpoint.

EndpointResult
OutcomeClinical Benefit Rate (CBR) by Investigator Assessment
Time frameUp to 23 months
Endpoint typeBinary
Analysis populationFull Analysis Set, including all randomized participants
MethodCochran-Mantel-Haenszel test
P-value0.018
HypothesisSuperiority
Effect estimate / CINot included in the ClinicalTrials.gov record
Clinical Biostats interpretation

The CBR comparison has a reported P-value of 0.018. Under the registry-reported statistical framework, this provides evidence against the null hypothesis of the reported comparison.

Again, the P-value does not quantify the magnitude of the treatment difference. Because the registry analysis does not include the underlying CBR percentages or a confidence interval, the statistical record cannot support a numerical statement about the absolute size of the difference.

The distinction between statistical evidence and effect magnitude is important: an inferential test answers whether the observed data are inconsistent with the null model, while an effect estimate describes the size and direction of the observed difference.

11. Safety Results

The ClinicalTrials.gov record reports serious adverse events by arm as affected participants divided by the number at risk. These data should be interpreted separately from the efficacy analyses because safety is concerned with adverse-event occurrence rather than time to progression or death.

GroupSerious adverse events affectedAt risk
Ribociclib + Letrozole108334
Placebo + Letrozole62330
Crossover to Ribociclib + Letrozole14

The ClinicalTrials.gov record therefore identifies 108/334 participants with serious adverse events in the ribociclib-plus-letrozole group and 62/330 in the placebo-plus-letrozole group. It separately identifies a crossover group of 1/4. The ClinicalTrials.gov record does not provide a formal statistical comparison, confidence interval, or P-value for these serious-adverse-event counts.

Safety interpretation: The serious-adverse-event counts should not be treated as an efficacy measure or combined mechanically with the PFS and OS hazard ratios. They describe affected participants among those at risk and are reported here as a separate safety outcome. The ClinicalTrials.gov record does not establish that the crossover group should be pooled with either randomized arm for an efficacy analysis.

12. What the Primary Hazard Ratio Means

Relative treatment effect

The primary PFS hazard ratio of 0.556 indicates a lower estimated instantaneous hazard of progression or death in the ribociclib-plus-letrozole group relative to the placebo-plus-letrozole group under the reported analysis. The corresponding relative reduction in estimated hazard is approximately 44.4%.

This is a relative measure. It does not say that 44.4% of participants were progression-free, that 44.4% of participants were cured, or that every patient experienced the same proportional reduction.

Confidence interval

The 95% confidence interval of 0.429–0.720 communicates uncertainty around the PFS hazard-ratio estimate. The interval is relatively narrower than an extremely imprecise estimate would be, but its width should still be considered when describing the precision of the treatment effect.

A confidence interval is not a prediction interval for individual patients. It also does not mean that 95% of future individual hazard ratios will fall between 0.429 and 0.720.

P-value

The primary P-value of 0.00000329 measures evidence against the null hypothesis for the reported superiority comparison. It is not an effect-size measure. The hazard ratio and its confidence interval are needed to describe the magnitude and precision of the treatment comparison.

13. Why Time-to-Event Endpoints Require Special Interpretation

PFS and OS are not ordinary binary outcomes because participants can enter the analysis at different times and may be followed for different lengths of time. A participant who has not experienced the event by the end of observation is not necessarily equivalent to a participant who was never at risk; instead, the observed follow-up contributes information up to the censoring point.

Timing matters

A time-to-event analysis incorporates when events occur, rather than simply counting how many participants experienced an event by a fixed date.

Censoring matters

For PFS, the registry specifically states that participants without an event were censored at their last adequate tumor assessment.

Hazard is not risk

A hazard ratio compares event hazards. It should not be described as though it were a simple ratio of cumulative probabilities.

Follow-up matters

The registry gives different follow-up windows for PFS, ORR and CBR versus OS, so their results should not be treated as though they came from identical observation periods.

14. Statistical Methods Explained

Why was a log-rank test used for PFS?

PFS is a time-to-event endpoint, so a method designed for time-to-event data is appropriate. The log-rank test compares the survival experience between treatment groups over the period of observation rather than reducing the endpoint to a single binary outcome. In MONALEESA-2, the registry explicitly reports the log-rank test for PFS.

What does a hazard ratio of 0.556 mean?

A hazard ratio of 0.556 means that the estimated instantaneous hazard in the ribociclib-plus-letrozole group was approximately 55.6% of that in the placebo-plus-letrozole group under the reported analysis. Equivalently, the estimated hazard was approximately 44.4% lower. It does not mean that 44.4% of patients benefited or that the probability of progression was reduced by exactly 44.4% at every time point.

Why is the confidence interval important?

The estimate 0.556 is only one estimate of the treatment effect. The 95% confidence interval of 0.429–0.720 describes uncertainty around that estimate. Reporting the interval prevents the point estimate from being interpreted as though it were known without statistical uncertainty.

Why does the P-value not measure effect size?

The primary P-value of 0.00000329 describes the evidence against the null hypothesis in the specified statistical test. It does not tell us whether the effect is large or small in clinical terms. The hazard ratio provides the relative effect estimate, while the confidence interval provides information about its precision.

Why was the Cochran-Mantel-Haenszel test used for ORR and CBR?

ORR and CBR are binary outcomes in the registry classification. The Cochran-Mantel-Haenszel test is a categorical-data procedure that can compare treatment groups while accounting for strata when a stratified analysis is specified. The registry explicitly reports this method for both secondary endpoints.

Why does the Full Analysis Set matter?

The posted analyses identify the Full Analysis Set as including all randomized participants. Analyzing randomized participants according to treatment assignment maintains the treatment comparison generated by randomization and avoids redefining the efficacy population based solely on subsequent treatment exposure or completion.

15. Primary and Secondary Statistical Evidence

EndpointRoleTypeMethodEffect measureResult
Progression Free Survival by Investigator Assessment Primary Time-to-event Log-rank HR 0.556 (95% CI 0.429–0.720) P = 0.00000329
Overall Survival Secondary Time-to-event Log-rank HR 0.765 (95% CI 0.628–0.932) P = 0.004
Overall Response Rate by Investigator Assessment Secondary Binary Cochran-Mantel-Haenszel Not reported in registry-reported analysis P = 0.000155
Clinical Benefit Rate by Investigator Assessment Secondary Binary Cochran-Mantel-Haenszel Not reported in registry-reported analysis P = 0.018

This table illustrates an important distinction in clinical-trial reporting: a formal hypothesis test may be available without a corresponding effect estimate in the registry's statistical-analysis record. For ORR and CBR, the ClinicalTrials.gov record supports reporting the P-values and methods, but not inventing response percentages or confidence intervals that are not present.

16. Multiplicity, Interim Analysis, and Other Design Issues

The registry-reported MONALEESA-2 data identifies the primary endpoint, three secondary statistical analyses, and superiority hypotheses. It does not provide information about a non-inferiority margin, a prespecified interim-analysis boundary, an alpha-spending procedure, a multiplicity-adjustment strategy, or a detailed endpoint hierarchy.

Design topicWhat the ClinicalTrials.gov record supports
SuperiorityReported for the primary PFS analysis and all three registry-reported secondary analyses.
Non-inferiority marginNot applicable to the reported superiority analyses; no non-inferiority margin is reported.
Interim analysisNo interim-analysis method or boundary is reported.
MultiplicityNo multiplicity-adjustment procedure is reported.
StratificationNo specific stratification factors are reported in the ClinicalTrials.gov record.
Bayesian methodsNo Bayesian analysis is reported.
Missing-data imputationNo imputation method is posted on ClinicalTrials.gov for the posted analyses.
CrossoverThe ClinicalTrials.gov record identifies 1/4 participants in a group labeled crossover to ribociclib + letrozole; the ClinicalTrials.gov record does not provide a detailed crossover-analysis methodology.
Why this restraint matters: Statistical trial pages should distinguish between what a registry actually reports and what might ordinarily be included in a full statistical analysis plan. A familiar clinical-trial design should not be used as a reason to infer unreported alpha spending, stratification factors, imputation rules, or interim boundaries.

17. Crossover and Interpretation of the Randomized Comparison

The ClinicalTrials.gov record identifies a group labeled Crossover to Ribociclib + Letrozole, with serious adverse events affecting 1 of 4 participants. This establishes that a crossover category is represented in the ClinicalTrials.gov record.

However, the available data does not provide enough information to determine how crossover was incorporated into the primary efficacy analysis, whether crossover occurred before or after a particular endpoint event, or whether a sensitivity analysis adjusted for crossover. Therefore, the primary PFS and OS results should be interpreted using the reported randomized Full Analysis Set comparison rather than constructing an unreported crossover-adjusted effect.

Statistical caution: Crossover can complicate interpretation of intention-to-treat treatment effects when participants assigned to one group subsequently receive treatment associated with the other group. The existence of a crossover category alone, however, is not enough to quantify its effect on the reported hazard ratios.

18. Understanding the Four Posted Statistical Analyses

AnalysisQuestion addressedWhy the method fits
PFS Do the randomized groups differ in time to first documented progression or death? PFS is a time-to-event endpoint; the registry reports a log-rank comparison and hazard ratio.
OS Do the randomized groups differ in overall survival? OS is a time-to-event endpoint; the registry reports a log-rank comparison and hazard ratio.
ORR Do the randomized groups differ in the binary response outcome? ORR is classified as binary; the registry reports a Cochran-Mantel-Haenszel comparison.
CBR Do the randomized groups differ in the binary clinical-benefit outcome? CBR is classified as binary; the registry reports a Cochran-Mantel-Haenszel comparison.

This is a useful example of matching the statistical method to the structure of the endpoint. The same randomized trial can require different inferential methods because PFS and OS contain timing and censoring information, while ORR and CBR are classified as binary outcomes.

19. Important Limitations and Interpretation Issues

20. Why This Trial Matters Statistically

MONALEESA-2 is a useful teaching example because the ClinicalTrials.gov record brings together two major classes of clinical-trial endpoints and two corresponding statistical approaches. The primary endpoint is a time-to-event outcome analyzed with a log-rank test and summarized with a hazard ratio, while ORR and CBR are binary outcomes analyzed with the Cochran-Mantel-Haenszel test.

ConceptHow it appears in MONALEESA-2
RandomizationThe trial uses randomized allocation with 668 enrolled participants.
Parallel designThe trial is classified as a parallel-group study with 2 arms.
Quadruple maskingThe registry classifies the trial as quadruple masked.
Full Analysis SetThe posted analyses include all randomized participants in the FAS.
Time-to-event endpointPFS is the registered primary endpoint; OS is a secondary endpoint.
Log-rank testUsed for the PFS and OS statistical analyses.
Hazard ratioReported for both PFS and OS.
Confidence intervalReported for the primary PFS HR and secondary OS HR.
Binary endpointORR and CBR are classified as binary outcomes.
Cochran-Mantel-Haenszel testUsed for ORR and CBR.
Superiority testingReported hypothesis type for all four registry-reported statistical analyses.
CensoringSpecified for participants without a PFS event at their last adequate tumor assessment.

21. Reading the Results as a Statistical Story

The primary PFS analysis gives the clearest numerical picture in the ClinicalTrials.gov record. The hazard ratio of 0.556, together with its 95% confidence interval of 0.429–0.720 and P-value of 0.00000329, provides three complementary pieces of information: the estimated direction and magnitude of the relative treatment effect, the uncertainty around that estimate, and the strength of evidence against the null hypothesis under the specified test.

The OS analysis uses the same general time-to-event framework but is a secondary endpoint and has a different reported effect estimate: HR 0.765, with a 95% CI of 0.628–0.932 and P = 0.004. The two hazard ratios therefore should not be collapsed into a single overall treatment-effect number.

ORR and CBR add binary-outcome evidence. Their P-values, 0.000155 and 0.018, respectively, provide inferential information, but the registry analysis does not provide the underlying percentages or effect estimates. A statistically careful summary therefore reports those P-values without inventing a numerical treatment difference.

22. Results Summary

EndpointEffect95% CIP-valueInterpretive role
Primary PFSHR 0.5560.429–0.7200.00000329Primary time-to-event evidence
Secondary OSHR 0.7650.628–0.9320.004Secondary time-to-event evidence
Secondary ORRNot reportedNot reported0.000155Binary-outcome evidence
Secondary CBRNot reportedNot reported0.018Binary-outcome evidence
Statistical reading: The ClinicalTrials.gov record supports a complete numerical interpretation of the PFS and OS hazard-ratio analyses, while the ORR and CBR records support interpretation of their hypothesis tests but not reconstruction of their effect sizes. Keeping those distinctions visible is essential to an accurate trial-results page.

23. Related Tutorials

Learn more about the methods used in this trial:

24. Related Calculators

25. Sources

Continue with the statistical methods

Explore the underlying survival-analysis, categorical-data, clinical-trial, and statistical-inference concepts used to interpret randomized trial evidence.

26. Record Summary

MONALEESA-2 provides a useful example of how a randomized phase 3 clinical trial can combine different statistical methods according to endpoint structure. Its registered primary endpoint, progression-free survival by investigator assessment, is a time-to-event outcome analyzed with a log-rank test and reported as a hazard ratio of 0.556 with a 95% confidence interval of 0.429–0.720 and P = 0.00000329. Overall survival was analyzed similarly, with HR 0.765, 95% CI 0.628–0.932, and P = 0.004. Overall response rate and clinical benefit rate were analyzed as binary endpoints using the Cochran-Mantel-Haenszel test, with reported P-values of 0.000155 and 0.018, respectively.

The most important statistical lesson is that these numbers answer different questions. Hazard ratios quantify relative time-to-event effects; confidence intervals describe uncertainty around those estimates; P-values quantify evidence against a null hypothesis under a specified test; and binary-outcome analyses require their own effect measures for understanding the magnitude of a difference. A careful interpretation therefore preserves the distinction between statistical evidence, effect size, uncertainty, endpoint definition, and analysis population.

Clinical Biostats methodology: This page intentionally reports only the trial facts and numerical results contained in the registry-reported MONALEESA-2 data. Where the registry analysis provides a method and P-value but no effect estimate or confidence interval, the page does not reconstruct or infer the missing quantity.