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
MA.17 was a randomized, parallel-group phase 3 trial evaluating letrozole versus placebo in breast cancer after 5 years of aromatase inhibitor therapy. The registered primary endpoint was disease-free survival (DFS), a time-to-event outcome analyzed using a stratified log-rank test with a hazard ratio as the effect measure.
| Feature | MA.17 |
|---|---|
| Phase | Phase 3 |
| Condition | Breast Cancer |
| Brief title | Letrozole in Breast Cancer Who Have Received 5 Years of Aromatase Inhibitor Therapy |
| Design | Randomized, parallel-group |
| Masking | Triple |
| Primary purpose | Treatment |
| Allocation | Randomized |
| Enrollment | 1,918 |
| Arms | 2 |
| Interventions | Letrozole; placebo |
| Primary endpoint | Disease-free Survival (DFS) |
| Primary endpoint type | Time-to-event |
| Hypothesis type | Superiority |
| Results posted | Yes |
| Lead sponsor | Canadian Cancer Trials Group |
| Sponsor type | Network |
| ClinicalTrials.gov | NCT00754845 |
2. Clinical Question
The central statistical question was whether treatment with letrozole, compared with placebo, changed disease-free survival among women with breast cancer who had received 5 years of aromatase inhibitor therapy.
Population
Women with breast cancer who had received 5 years of aromatase inhibitor therapy.
Intervention
Letrozole.
Comparator
Placebo.
Primary question
Does letrozole produce a different disease-free survival experience from placebo under a superiority hypothesis?
3. Trial Design
The trial started on November 23, 2004 and had a primary completion date of December 21, 2015. The registry reports an enrollment of 1,918 and two treatment arms.
Letrozole
- Intervention type: drug
- Compared with placebo
- Included in the primary DFS comparison
Placebo
- Intervention type: other
- Comparator for letrozole
- Included in the primary DFS comparison
4. Endpoints
| Endpoint | Role | Time frame | Type | Reported analysis |
|---|---|---|---|---|
| Disease-free Survival (DFS) | Primary | Unitil the end of study with a median follow up of 75 months | Time-to-event | Stratified log-rank test; hazard ratio |
| Overall Survival (OS) | Secondary | Until the end of study with a median follow-up of 75 months | Time-to-event | Log-rank test; hazard ratio |
| Incidence of Contralateral Breast Cancer | Secondary | 10 years | Time-to-event | Log-rank test |
| Change From Baseline in Role Function- Physical Scale on SF(Short Form)-36 Health Survey | Secondary | 8 years | Continuous | Mixed-effects model |
Primary endpoint: Disease-free Survival
The registry defines Disease-free Survival (DFS) as the months from the day of randomization to the earliest date when a recurrence of the primary disease was observed, including recurrence in the breast, chest wall and nodal sites or development of metastatic disease, or when a contralateral breast cancer was observed. Subjects who died without recurrence of the primary disease or development of the contralateral breast cancer were censored.
The registered time frame is "Unitil the end of study with a median follow up of 75 months". The reported outcome unit is the probability of DFS at 5 years.
5. Statistical Methodology
Primary DFS analysis
The primary DFS analysis used a stratified log-rank test. The reported effect measure was a hazard ratio, with a two-sided 95% confidence interval and a superiority hypothesis.
The analysis population included all women randomized, analyzed according to the treatment arm to which they were randomized.
Stratification
The registry's analysis notes state that the primary DFS analysis was stratified by the stratification factors at randomization. Stratification preserves the role of prespecified randomization factors when comparing time-to-event outcomes.
A stratified log-rank test does not simply compare two unadjusted event-time distributions. Instead, it incorporates the prespecified strata into the comparison, allowing the treatment contrast to be evaluated while respecting the trial's stratified randomization structure.
Analysis population
For the primary DFS analysis, all women randomized were included in the analysis based on treatment arm they were randomized. This is an intention-to-treat-style analysis principle: the efficacy comparison remains tied to randomized assignment rather than being redefined according to treatment actually received or later treatment changes.
Secondary analyses
Overall survival and incidence of contralateral breast cancer were also analyzed with the log-rank test. The OS analysis reported a hazard ratio, while the contralateral breast cancer analysis reported a P-value without a hazard-ratio estimate in the ClinicalTrials.gov record.
The longitudinal SF-36 physical role-function endpoint was analyzed with a mixed-effects model, reflecting a fundamentally different statistical structure from the time-to-event endpoints.
6. Results
Primary endpoint: Disease-free Survival
Hazard ratio for disease-free survival
95% CI: 0.48–0.91 · P = 0.01 · Two-sided
Comparison: Letrozole vs Placebo
| Primary DFS result | Reported value |
|---|---|
| Outcome unit | Probability of DFS at 5 years |
| Analysis population | All women randomized, analyzed according to randomized treatment arm |
| Groups compared | Letrozole vs Placebo |
| Method | Stratified log-rank test |
| Effect measure | Hazard ratio |
| Estimate | 0.66 |
| 95% CI | 0.48–0.91 |
| P-value | 0.01 |
| Hypothesis | Superiority |
| Stratification | Stratified by the stratification factors at randomization |
The estimated hazard ratio of 0.66 means that, under the time-to-event comparison represented by the reported hazard ratio, the estimated instantaneous rate of a DFS event in the letrozole group was approximately 66% of that in the placebo group. Expressed as a relative complement, this corresponds to an estimated 34% lower hazard for the letrozole group.
The HR does not mean that 34% of patients avoided recurrence, that 34% more patients were disease-free at 5 years, or that every patient experienced the same proportional reduction in event risk. A hazard ratio is a relative time-to-event measure, not an absolute probability.
The 95% confidence interval of 0.48–0.91 describes uncertainty around the estimated hazard ratio under the statistical model and sampling framework. It does not describe the range of effects that individual patients experienced.
The P-value of 0.01 addresses evidence against the null hypothesis in the specified superiority comparison. It does not measure the size of the treatment effect. Effect magnitude and statistical evidence should therefore be read separately: the HR describes the estimated relative effect, the CI describes its precision, and the P-value describes evidence against the null under the specified testing framework.
Because DFS is a censored time-to-event endpoint, the analysis also depends on how follow-up and censoring are handled. The hazard-ratio interpretation additionally relies on the appropriateness of representing the treatment contrast with a proportional-hazards-type summary over the analyzed follow-up. The ClinicalTrials.gov record does not provide a diagnostic assessment of that assumption.
Secondary endpoint: Overall Survival
Hazard ratio for overall survival
95% CI: 0.73–1.28 · P = 0.83 · Two-sided
Comparison: Arm I vs Arm II
| OS result | Reported value |
|---|---|
| Time frame | Until the end of study with a median follow-up of 75 months |
| Outcome unit | Probability of OS at 5 years |
| Analysis population | All women randomized |
| Groups compared | Arm I vs Arm II |
| Method | Log-rank test |
| Effect measure | Hazard ratio |
| Estimate | 0.97 |
| 95% CI | 0.73–1.28 |
| P-value | 0.83 |
| Hypothesis | Superiority |
The OS hazard ratio of 0.97 is close to 1. Under the reported model-based time-to-event comparison, the estimated instantaneous rate of death in Arm I was approximately 97% of that in Arm II.
This does not mean that overall survival was exactly the same in the two groups. The estimate is subject to sampling uncertainty, as reflected by the 95% confidence interval of 0.73–1.28.
The confidence interval spans 1.00, so the data are compatible with a range of relative hazard differences in either direction under the specified analysis. The P-value of 0.83 indicates little evidence against the null hypothesis in this superiority test; it is not a measure of how large or small the observed HR is.
The registry reports the analysis as a log-rank comparison with a hazard ratio. As with the primary DFS analysis, interpretation of a single HR requires attention to censoring and the appropriateness of the proportional-hazards summary over follow-up.
Secondary endpoint: Incidence of Contralateral Breast Cancer
| Result | Reported value |
|---|---|
| Time frame | 10 years |
| Outcome unit | Number of new case per 1000 person years |
| Analysis population | All women randomized |
| Groups compared | Letrozole vs Placebo |
| Method | Log-rank test |
| P-value | 0.007 |
| Hypothesis | Superiority |
The registry reports a P-value of 0.007 for the superiority comparison of letrozole versus placebo over 10 years. The reported outcome unit is the number of new cases per 1000 person-years.
No hazard-ratio estimate or confidence interval is included in the registry-reported statistical analysis for this endpoint. Consequently, the result should not be converted into a hazard ratio or an estimated relative reduction without additional reported data.
The P-value indicates the statistical evidence reported for the comparison; it does not quantify the magnitude of the difference. For magnitude and precision, an effect estimate and confidence interval would provide additional information, but those values are not included in the registry analysis.
Secondary endpoint: SF-36 Role Function—Physical Scale
| Result | Reported value |
|---|---|
| Endpoint | Change From Baseline in Role Function- Physical Scale on SF(Short Form)-36 Health Survey |
| Time frame | 8 years |
| Outcome unit | Score on a scale |
| Analysis population | All randomized patients |
| Groups compared | Letrozole vs Placebo |
| Method | Mixed Models Analysis / mixed-effects model |
| P-value | <0.01 |
| Hypothesis | Superiority |
The SF-36 physical role-function endpoint was analyzed with a mixed-effects model, rather than a survival-analysis method. The registry reports a superiority-test P-value of <0.01 for the comparison of letrozole versus placebo.
Because the registry analysis does not report an estimated between-group difference or confidence interval for this endpoint, the P-value alone does not establish the magnitude or precision of the difference. A mixed-effects model is designed to account for the correlation among repeated observations from the same participant, but the exact model specification is not provided in the ClinicalTrials.gov record.
7. Statistical Methods Explained
Why was a log-rank test used for DFS?
DFS is a time-to-event endpoint. Participants can experience an event at different times, while others may remain event-free at the end of available follow-up and therefore contribute censored observations. A log-rank test compares the event-time experience of randomized groups while incorporating the timing of events and censoring rather than reducing the outcome to a simple yes/no proportion at one arbitrary date.
Why was the DFS analysis stratified?
The registry states that the primary DFS analysis was stratified by the stratification factors used at randomization. Stratification allows the time-to-event comparison to respect the trial's prespecified randomization structure. It is particularly useful when the randomization procedure intentionally balances treatment assignments within clinically or statistically important strata.
What does an HR of 0.66 mean?
An HR of 0.66 is a relative time-to-event estimate. It indicates an estimated instantaneous event rate in the letrozole group that is 66% of the corresponding rate in the placebo group under the fitted analysis. The complementary interpretation is an estimated 34% lower hazard.
That is different from saying that 34% of participants benefited or that the probability of an event was reduced by exactly 34% at every time point. Absolute event probabilities require separate estimates such as Kaplan-Meier survival probabilities.
Why is the confidence interval important?
The DFS 95% CI of 0.48–0.91 communicates the uncertainty surrounding the estimated HR of 0.66. The interval is more informative than the point estimate alone because it shows how precisely the treatment effect was estimated under the specified statistical framework.
A confidence interval is not a range containing the true treatment effect with a fixed probability after the data have been observed. It is a statement about the performance of the interval procedure under repeated sampling.
Why doesn't the P-value measure treatment effect?
The DFS P-value of 0.01 and OS P-value of 0.83 answer questions about evidence against their respective null hypotheses. They do not measure clinical importance, effect magnitude, or probability that the treatment works.
For that reason, a statistically interpretable trial result should be read using the full set of available quantities: the effect estimate, its confidence interval, the P-value, the endpoint definition, and the analysis population.
Why was a mixed-effects model used for the SF-36 endpoint?
The SF-36 endpoint is continuous rather than time-to-event and is measured longitudinally. Repeated measurements from the same participant are correlated, so treating every observation as independent can understate uncertainty. A mixed-effects model can represent this within-participant correlation while estimating treatment-related differences over repeated assessments.
The ClinicalTrials.gov record reports only that a mixed-effects model was used and give a P-value of <0.01. They do not provide the model's covariance structure, fixed-effect specification, random-effect structure, or an estimated treatment difference.
8. Kaplan-Meier Estimation and Censoring
Although the registry's normalized methods list identifies the primary method as a log-rank test, DFS and OS are time-to-event outcomes for which Kaplan-Meier estimation is the standard descriptive framework. Kaplan-Meier curves estimate the probability of remaining event-free or alive over time while retaining information from participants who are censored.
Here, di represents events at time ti, while ni represents participants at risk immediately before that event time.
The important statistical distinction is that censoring does not mean that an individual experienced the event at the censoring time. Instead, that participant contributes information through the time at which follow-up ends or the participant otherwise becomes censored under the analysis rules.
9. Hazard Ratios in MA.17
| Endpoint | Comparison | HR | 95% CI | P-value |
|---|---|---|---|---|
| Disease-free Survival | Letrozole vs Placebo | 0.66 | 0.48–0.91 | 0.01 |
| Overall Survival | Arm I vs Arm II | 0.97 | 0.73–1.28 | 0.83 |
The contrast between the two estimates illustrates why a trial should not be summarized by one number alone. The primary DFS analysis reports an HR of 0.66, whereas the secondary OS analysis reports an HR of 0.97. These are estimates for different endpoints and should be interpreted within their respective endpoint definitions and follow-up structures.
A hazard ratio is inherently relative. It does not provide the absolute probability of remaining disease-free or alive at a particular time. The registry identifies the outcome unit for both DFS and OS as the probability at 5 years, but the statistical analyses posted on ClinicalTrials.gov do not provide the corresponding numerical 5-year probabilities. Therefore, the reported HRs should not be substituted for those absolute quantities.
10. Secondary Endpoint Structure
| Endpoint | Statistical family | Reported evidence | Interpretive focus |
|---|---|---|---|
| Disease-free Survival (DFS) | Survival analysis | HR 0.66; 95% CI 0.48–0.91; P = 0.01 | Primary time-to-event treatment comparison |
| Overall Survival (OS) | Survival analysis | HR 0.97; 95% CI 0.73–1.28; P = 0.83 | Secondary time-to-event comparison |
| Incidence of Contralateral Breast Cancer | Survival analysis | P = 0.007 | 10-year incidence comparison |
| SF-36 Role Function—Physical Scale | Longitudinal / mixed models | P < 0.01 | Repeated continuous outcome |
These endpoints require different statistical interpretations. DFS and OS incorporate event timing and censoring. Contralateral breast cancer is also represented as a time-to-event endpoint in the registry. The SF-36 outcome is continuous and longitudinal, so its mixed-effects analysis addresses repeated measurements rather than event-time distributions.
11. Safety Results
The ClinicalTrials.gov record reports serious adverse events by randomized arm using affected participants over participants at risk:
| Arm | Serious adverse events | Affected / at risk |
|---|---|---|
| Arm I | Serious adverse events | 15 / 959 |
| Arm II | Serious adverse events | 19 / 954 |
The registry reports serious adverse events as 15/959 in Arm I and 19/954 in Arm II. These are descriptive safety counts rather than a reported inferential comparison in the statistical analyses posted on ClinicalTrials.gov.
The denominators are the reported numbers at risk for the safety measure. They should not be silently substituted with the overall enrollment of 1,918, because safety summaries can use populations defined by treatment exposure or evaluability.
No additional serious-adverse-event confidence interval, P-value, risk ratio, or hazard ratio is included in the ClinicalTrials.gov record. Accordingly, no formal comparative safety conclusion is added here.
12. Multiplicity and Multiple Endpoints
MA.17 has one registered primary endpoint and three posted secondary outcome analyses. The primary endpoint is DFS, while OS, incidence of contralateral breast cancer, and change from baseline in the SF-36 physical role-function scale are secondary endpoints.
| Endpoint role | Endpoint | Reported statistical result |
|---|---|---|
| Primary | Disease-free Survival (DFS) | HR 0.66; 95% CI 0.48–0.91; P = 0.01 |
| Secondary | Overall Survival (OS) | HR 0.97; 95% CI 0.73–1.28; P = 0.83 |
| Secondary | Incidence of Contralateral Breast Cancer | P = 0.007 |
| Secondary | Change From Baseline in Role Function- Physical Scale on SF(Short Form)-36 Health Survey | P < 0.01 |
The existence of several statistical analyses creates an important interpretive distinction: a nominal P-value for a secondary endpoint does not automatically have the same confirmatory interpretation as the prespecified primary endpoint. Whether and how multiplicity was controlled depends on the trial's prespecified statistical plan. The ClinicalTrials.gov record does not report an alpha-allocation or multiplicity-adjustment procedure, so none is inferred here.
13. Randomization and the Intention-to-Treat Principle
The primary DFS analysis included all women randomized according to the treatment arm to which they were randomized. This is important because the purpose of randomization is to create comparable treatment groups at baseline, subject to chance variation.
Preserves randomized comparison
Analyzing participants according to randomized assignment maintains the treatment comparison generated by the randomization process.
Avoids post-randomization selection
Reassigning participants according to treatment actually received can introduce selection related to adherence, discontinuation, or subsequent clinical events.
Relevant to DFS
The registry explicitly states that all randomized women were included in the primary analysis based on randomized treatment arm.
Different from safety analysis
Safety populations can be defined around treatment exposure. The registry-reported serious-AE results are presented using affected and at-risk counts rather than the overall randomized enrollment.
14. Time-to-Event Analysis: What the Data Actually Tell Us
Time-to-event analysis contains more information than a simple event proportion because it incorporates when events occur. Two participants can both eventually experience a recurrence, yet their contribution to a time-to-event analysis differs if one recurrence occurs much earlier than the other.
MA.17's primary DFS analysis therefore uses a method suited to the structure of the endpoint: the stratified log-rank test. The hazard ratio provides a relative summary of the treatment contrast over follow-up.
For the reported DFS result, HR = 0.66. This is a model-based relative measure and should not be interpreted as an absolute risk ratio.
The ClinicalTrials.gov record does not provide the underlying event counts, individual follow-up times, Kaplan-Meier estimates at multiple time points, or median DFS. Those quantities are therefore not reconstructed on this page.
15. Longitudinal Analysis of SF-36
The SF-36 physical role-function outcome is structurally different from DFS and OS. It is a continuous score measured over time, with the registry defining the outcome as change from baseline over an 8-year time frame.
The registry reports a mixed-effects model for this analysis. Mixed-effects models are useful when repeated observations are obtained from the same participants because those observations are generally correlated.
The fixed component can describe systematic treatment and time effects, while random effects and the covariance structure account for dependence among observations from the same participant. The exact specification used in MA.17 is not provided in the ClinicalTrials.gov record.
16. Clinical Biostats Interpretation of the Primary Result
The primary DFS analysis reported a hazard ratio of 0.66 for letrozole versus placebo, with a two-sided 95% confidence interval of 0.48–0.91 and a P-value of 0.01. The analysis included all randomized women according to randomized treatment arm and used a stratified log-rank test.
The result does not provide a 5-year absolute DFS probability in the ClinicalTrials.gov record. It also does not imply that every participant experienced a 34% reduction in individual risk, nor does it establish the probability that any particular participant will remain disease-free.
The interval from 0.48 to 0.91 indicates uncertainty around the estimated HR. It shows that the point estimate of 0.66 should not be treated as an exact treatment effect. The interval also communicates substantially more information about precision than the P-value alone.
A P-value of 0.01 indicates statistical evidence under the specified superiority test. It does not tell us whether the HR is clinically large, clinically small, or precisely estimated. Those questions are addressed by the HR, confidence interval, and absolute outcome measures.
17. Limitations
- Registry-level detail: this analysis is constrained to the numerical and methodological information from ClinicalTrials.gov. Trial-protocol and statistical-analysis-plan details not included in that data are not inferred.
- Incomplete absolute-effect reporting: the statistical analyses posted on ClinicalTrials.gov identify the DFS and OS outcome unit as probability at 5 years, but numerical 5-year probabilities are not provided.
- No median event times: median DFS and median OS are not included in the ClinicalTrials.gov record and therefore are not reported.
- Hazard-ratio assumptions: a single HR is a relative time-to-event summary and is most straightforward to interpret when its underlying proportional-hazards representation is reasonable. The ClinicalTrials.gov record does not report a formal assessment of that assumption.
- Secondary-endpoint multiplicity: the ClinicalTrials.gov record does not specify an alpha-allocation or multiplicity-adjustment strategy for the secondary analyses. Their nominal P-values should therefore not automatically be interpreted as independently confirmatory.
- Incomplete mixed-model specification: the SF-36 analysis is identified as a mixed-effects model, but the ClinicalTrials.gov record does not provide the detailed model specification, covariance structure, or estimated treatment difference.
- Limited safety inference: serious adverse events are reported as affected/at-risk counts by arm, but the ClinicalTrials.gov record does not provide a formal comparative safety analysis.
- No individual-level data: without participant-level event and censoring times, Kaplan-Meier curves and other distributional summaries cannot be independently reconstructed.
18. Why This Trial Matters Statistically
MA.17 is a useful teaching example because its registry record connects several core clinical-trial methods in a single randomized study: time-to-event endpoints, stratified log-rank testing, hazard ratios, confidence intervals, intention-to-treat analysis, and longitudinal mixed-effects modeling.
| Statistical concept | How it appears in MA.17 |
|---|---|
| Randomization | Randomized allocation to two parallel treatment arms |
| Masking | Triple masking |
| Superiority testing | Registered hypothesis type for the reported analyses |
| Time-to-event endpoint | DFS is the registered primary endpoint |
| Stratified analysis | Primary DFS analysis stratified by the factors used at randomization |
| Log-rank test | Used for DFS, OS, and contralateral breast cancer analyses |
| Hazard ratio | Reported for DFS and OS |
| Confidence interval | 95% two-sided intervals reported for DFS and OS HRs |
| Intention-to-treat principle | All women randomized included in the primary DFS analysis according to randomized arm |
| Mixed-effects model | Used for change from baseline in the SF-36 physical role-function scale |
| Longitudinal outcome | SF-36 endpoint assessed over an 8-year time frame |
| Secondary endpoints | OS, contralateral breast cancer incidence, and SF-36 physical role function |
19. Statistical Methods Explained Through the Primary DFS Result
Randomization
Randomized assignment provides the basis for comparing letrozole and placebo without relying on investigators to choose which participants receive each treatment.
Stratification
The primary DFS analysis respects the stratification factors used at randomization rather than ignoring that design feature.
Log-rank test
The primary comparison evaluates time-to-event experience rather than simply counting whether each participant eventually experienced an event.
Hazard ratio
The HR of 0.66 summarizes the relative instantaneous event rate under the fitted time-to-event comparison.
20. Interpreting DFS and OS Together
The ClinicalTrials.gov record shows two different time-to-event estimates: a DFS HR of 0.66 and an OS HR of 0.97. These should not be treated as contradictory measurements of the same outcome. DFS captures the first occurrence of specified disease-related events or contralateral breast cancer, while OS concerns death from any cause.
Differences between endpoints are expected because they represent different clinical events and because events that occur before death can affect the DFS experience without necessarily producing the same relative difference in overall survival.
| Feature | DFS | OS |
|---|---|---|
| Role | Primary | Secondary |
| Type | Time-to-event | Time-to-event |
| Reported effect | HR 0.66 | HR 0.97 |
| 95% CI | 0.48–0.91 | 0.73–1.28 |
| P-value | 0.01 | 0.83 |
| Analysis | Stratified log-rank | Log-rank |
| Time frame | End of study; median follow-up 75 months | End of study; median follow-up 75 months |
The appropriate interpretation is therefore endpoint-specific: the primary DFS analysis reports an estimated hazard ratio below 1 with its associated confidence interval and P-value, while the secondary OS analysis reports an HR close to 1 with a wider interval spanning 1.00.
21. The Difference Between Statistical Evidence and Effect Size
MA.17 illustrates why the statistical result should be read as a collection of quantities rather than as a single P-value.
The estimate describes the observed relative effect, the confidence interval communicates uncertainty, the P-value evaluates evidence against a null hypothesis, and the endpoint definition establishes what clinical event is actually being analyzed.
For DFS, the four pieces are HR 0.66, 95% CI 0.48–0.91, P = 0.01, and a registered endpoint defined from randomization to recurrence, metastatic disease, or contralateral breast cancer, with specified censoring for participants who died without those events.
For OS, the corresponding values are HR 0.97, 95% CI 0.73–1.28, and P = 0.83, for the endpoint defined as overall survival in the registry analysis.
22. Important Statistical Interpretation Issues
- Do not equate HR with risk ratio: a hazard ratio summarizes relative event rates over time; it is not automatically the ratio of cumulative probabilities.
- Do not equate HR with absolute benefit: an HR below 1 does not specify the absolute difference in 5-year DFS probability.
- Do not equate P-value with effect size: P = 0.01 does not mean the treatment effect is 1% or 99% likely to have any particular magnitude.
- Respect the analysis population: the primary DFS result uses all randomized women according to randomized treatment arm.
- Respect the stratification: the primary analysis was explicitly stratified by the factors used at randomization.
- Separate endpoint families: DFS, OS, contralateral breast cancer incidence, and SF-36 physical role function require different statistical interpretations.
- Do not infer missing estimates: the registry supplies P-values for contralateral breast cancer and SF-36 without corresponding effect estimates in the ClinicalTrials.gov record.
- Do not infer unreported multiplicity procedures: no alpha-allocation or adjustment method is included in the ClinicalTrials.gov record.
23. Trial Timeline
Trial start
The registered MA.17 trial began.
Randomized comparison
The study used randomized allocation in a parallel design with triple masking and two treatment arms: letrozole and placebo.
Disease-free survival
The primary DFS endpoint was analyzed using a stratified log-rank test with a hazard ratio of 0.66, 95% CI 0.48–0.91, and P = 0.01.
Primary completion
The registered primary completion date was December 21, 2015.
24. Related Tutorials
Learn more about the methods used in this trial:
25. Related Calculators
26. Sources
- ClinicalTrials.gov: NCT00754845 — MA.17.
- PubMed: PMID 27264120.
- PubMed: PMID 34825307.
- PubMed: PMID 33853037.
- PubMed: PMID 29328860.
Continue through Clinical Biostats
Explore the statistical methods behind randomized clinical trials, survival analysis, longitudinal models, confidence intervals, and related clinical-trial calculations.
27. Record Summary
MA.17 provides a compact example of several central principles in clinical-trial statistics. The study is a randomized phase 3, parallel-group trial with triple masking and two interventions, letrozole and placebo. Its registered primary endpoint is disease-free survival, a time-to-event outcome analyzed with a stratified log-rank test and summarized using a hazard ratio.
The primary DFS result was HR 0.66, with a two-sided 95% confidence interval of 0.48–0.91 and P = 0.01. The analysis included all randomized women according to their randomized treatment arm and was stratified by the factors used at randomization.
The secondary analyses demonstrate why endpoint-specific interpretation matters. Overall survival produced an HR of 0.97 with a 95% CI of 0.73–1.28 and P = 0.83. The incidence of contralateral breast cancer was analyzed with a log-rank test and reported P = 0.007, while the longitudinal SF-36 physical role-function endpoint was analyzed using a mixed-effects model with P < 0.01.
The statistical lesson is broader than any single result. A rigorous interpretation combines the endpoint definition, randomized analysis population, statistical method, effect estimate, confidence interval, and P-value. It also distinguishes time-to-event methods from longitudinal continuous-outcome models and avoids converting unreported quantities into estimates that the registry does not provide.