Breast Cancer Risk Reduction: A Patient Doctor Intervention: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Breast Cancer Risk Reduction: A Patient Doctor Intervention (NCT01830933), a randomized na study. The primary outcome is Knowledge of Breast Cancer Risk Factors.

2. Clinical Question

3. Trial Design

This was a randomized, single-masked, parallel-group study of BreastCARE compared with usual care. The registry lists the study as completed, with enrollment of 1235. The recorded study start was 2011-06 and primary completion was 2012-08. The phase is listed as not applicable. The sponsor was the University of California, San Francisco.

Participants were assigned to an intervention or comparison group at recruitment. The registry description says block randomization was used. The block size, sequence-generation method, allocation-concealment procedures, and the identity of the person or people who were masked are not reported in the registry record. The record therefore identifies the broad design but does not establish the operational details of randomization or masking.

The BreastCARE intervention was described as a tablet-PC-based education approach in the primary care setting. The research goal was to estimate individual breast cancer risk, give the participant and physician personalized risk information and recommendations, and support discussion of risk reduction practices. The available intervention-arm description begins to describe a research assistant welcoming the patient and demonstrating tablet use, but the full procedure is not reported in the registry record. The comparator was usual care; its complete care description is also not reported.

The posted primary outcome is continuous: knowledge of breast cancer risk factors, summarized as a mean and standard deviation. It was measured by post-survey approximately one week after the initial visit. The registry reports one primary outcome and 4 outcome measures in total, but no secondary results are posted. The registry lists 0 analyses. A detailed statistical analysis plan and the original sample-size justification are not reported in the registry record.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

Population: Number of participants who completed follow-up.

6. Primary Endpoint

The registry lists the primary outcome as Knowledge of Breast Cancer Risk Factors, measured over one week post-initial visit (approximately one week).

The primary endpoint is knowledge of breast cancer risk factors, measured approximately one week after the initial visit. The registry describes a post-survey based on a series of eight questions. Participants could score from 0-100, where 0 means no correct answers and 100 means all answers are correct. The outcome is reported as a mean with standard deviation, making it a continuous measure rather than a count of events or a time-to-event outcome.

A knowledge score is used to describe what participants know about breast cancer risk factors at the time of the survey. Comparing group means provides a concise summary of the average scores in the two randomized groups. In general, a score-based endpoint can capture differences in measured knowledge without itself demonstrating changes in decisions, health practices, or later health outcomes. Those outcomes are distinct from the questionnaire score.

The registry’s primary endpoint description ends before the full account of the measure is available. Additional information about the exact survey items, scoring rules beyond the stated range, validation, and treatment of incomplete responses is not reported in the registry record. The posted means therefore describe the recorded score, but the available registry detail does not permit a more complete assessment of how each question contributed to that score.

7. Results Posted in the Registry

• BreastCARE Intervention: mean 56.40 versus 48.90 on control; difference 7.50 (95% CI 4.78 to 10.22), standardized effect d = 0.31; z-test p = <0.001.

8. Statistical Interpretation

9. Statistical Methods Explained

What does a mean difference describe?

The endpoint is a continuous score. For a continuous measure, the mean describes the average observed value within a group. A mean difference expresses the contrast between the group averages in the original score units. Here, the reported difference is 7.5 units on the 0-100 knowledge scale, comparing BreastCARE with usual care. This keeps the result interpretable in the same units as the survey rather than converting it to a different scale.

The reported group means are 56.4 for BreastCARE and 48.9 for usual care. The standard deviation is 24.3 in each group. In general, a standard deviation describes how spread out individual scores are around a group mean. It is not the uncertainty of the mean difference. Uncertainty in the comparison is expressed by the confidence interval.

What does the confidence interval express?

The 95% confidence interval for the mean difference runs from 4.784 to 10.22 units on the scale. In general, a confidence interval gives a range of estimates compatible with the observed data under the statistical method and its assumptions. It conveys both the estimated direction and the precision of the comparison. An interval that does not include zero is consistent with a nonzero difference under that method, but the interval does not identify a single exact effect or establish practical importance.

The interval is attached to the group contrast, not to individual scores. Its width reflects uncertainty in the estimated average difference, while the standard deviations describe variation among participants. These quantities answer different questions and should not be substituted for one another.

How should the p-value be read?

The unadjusted comparison reports p < 0.001. In general, a p-value is calculated under a specified null hypothesis and statistical model. It describes how unusual data at least as incompatible with that null hypothesis would be if the null and the model assumptions held. It is not the probability that the null hypothesis is true, nor does it quantify the probability that the finding is due to chance in an everyday sense. It also does not measure the magnitude of the group difference.

The registry record does not report a detailed analysis plan or a list of covariates for an adjusted analysis. The result is therefore best described as an unadjusted comparison, without attributing it to a model or adjustment procedure that is not reported. The record lists 0 analyses; the comparison statistics do not supply a fuller account of model diagnostics or analytic choices.

Why can score variability matter?

In general, variability affects how precisely a mean and a difference between means can be estimated. When participants’ scores vary widely, the group averages can be less precise for a given amount of information than they would be with less variation. The observed standard deviations are 24.3 in both groups, and the confidence interval provides the direct reported measure of precision for the mean difference.

Some statistical methods also rely on assumptions about the distribution of outcomes or errors. For count outcomes, over-dispersion means that observed variation exceeds what a simple model expects; methods that account for it can be important for appropriate uncertainty estimates. That general issue does not describe the primary endpoint in this trial, which is a continuous survey score. The registry does not report a diagnostic assessment of the score distribution or any special variance adjustment, so none should be inferred.

What is the role of randomization?

In general, random assignment is intended to make treatment groups comparable in expectation, so that an outcome contrast can be interpreted as a comparison of assigned groups rather than a comparison chosen by participants or investigators. The registry says participants were randomized at recruitment using block randomization. It does not report the block size, allocation concealment, or whether the posted results follow an intention-to-treat approach. Randomization is an important design feature, but it does not by itself resolve uncertainty about missing outcome data, adherence, or the exact analysis population.

The design is parallel-group: participants were assigned to one of the groups, rather than each participant serving as their own comparison at different treatment periods. The registry labels the study single-masked, but who was masked and how masking was maintained are not reported in the registry record. No additional claims about masking can be made from that label alone.

What does the planning calculation represent?

The planning figures are illustrations based on the observed difference and stated assumptions. They are not evidence about the trial’s original design justification. In general, a power calculation asks how many participants would be needed under a specified effect size, variability, significance level, and allocation plan to have a stated chance of detecting an effect using the chosen test. Such calculations depend on the assumptions used and are not guarantees about what a future study will observe.

The registry record does not report the original sample-size justification, the trial’s prespecified analysis plan, or whether there were interim analyses. The displayed planning assumptions should therefore be understood only as the assumptions attached to the retrospective illustration, not attributed to the investigators’ original protocol.

10. Confidence Intervals and Precision

The mean difference is 7.5 units on the 0-100 scale, and the 95% confidence interval extends from 4.784 to 10.22. This interval communicates the uncertainty around the estimated average contrast. Its endpoints are both on the positive side of zero, so the interval supports a positive mean difference under the calculation method used. The interval does not mean that 95% of individual participants’ scores fall within those bounds; it concerns the estimated difference between group means.

Precision is distinct from the size of the estimated difference. The interval gives a range of values that remain compatible with the data and method, rather than proving the true difference is any one value in that range. The endpoint’s standard deviation is 24.3 in each group, describing score variation among participants; it should not be read as the confidence interval for the mean difference.

The reported p-value is p < 0.001. It is consistent with the interval’s exclusion of zero, but the p-value does not make the estimate more precise and does not describe its practical importance. The registry does not report a threshold for a meaningful knowledge-score difference, so the interval cannot be classified against such a threshold using the record alone.

The comparison is unadjusted, and further details about missing responses and analysis populations are not reported in the registry record. Those omissions limit assessment of whether the interval captures all relevant uncertainty. It remains a measure of precision for the posted statistical comparison, not a guarantee that the same estimate would be obtained in another setting or over a longer follow-up period.

11. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning figures are participants per arm, not total event counts. They illustrate sample sizes for a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The assumed effect to detect is expressed as a fraction of the observed effect. These are planning assumptions for an illustration; the original trial design assumptions and sample-size justification are not reported in the registry record. This is not observed power.

For planning for 100% of the observed effect, the figures are 165 participants per arm for 80% power and 221 participants per arm for 90% power. For planning for 75% of the observed effect, they are 293 participants per arm for 80% power and 393 participants per arm for 90% power. For planning for 50% of the observed effect, they are 660 participants per arm for 80% power and 883 participants per arm for 90% power.

In general, power is the probability that a study will detect an effect of a specified size under the calculation’s assumptions if that effect is present. The 80% column means the planning calculation targets an 80% chance of detecting the assumed effect; the 90% column targets a 90% chance. Higher targeted power requires more participants under otherwise fixed assumptions. The figures also show the general pattern that smaller effects need more participants: detecting a smaller fraction of the observed difference requires larger group sizes in these calculations.

These values should not be read as the number enrolled in the original study, a prediction of future results, or proof that the trial had a particular probability of success. They are conditional planning illustrations based on the observed effect and stated method assumptions. The registry record does not report whether the original study used these assumptions or any of these target sample sizes.

12. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = 7.500; pooled standard deviation σ = 24.300.
2. n = 2 × (1.96 + 0.842)² × 24.300² / 7.500² = 164.8, rounded up to 165 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
delta <- 7.5                      # observed difference in means
sigma <- 24.3                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(1830933)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 165 (80% power), 221 (90% power)
 75% of observed effect: n per arm = 293 (80% power), 393 (90% power)
 50% of observed effect: n per arm = 660 (80% power), 883 (90% power)
power.t.test: 165.8 
Simulated power at n = 165 per arm: 0.802 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

13. Multiplicity, Missing Data and Analysis Populations

The registry lists 4 outcome measures, identifies knowledge of breast cancer risk factors as the primary outcome, and reports no posted secondary outcome results. It also lists 0 analyses. The number of outcomes alone does not establish how many statistical tests were planned or performed, and the registry does not report a multiplicity strategy. Whether outcomes were prespecified in a protocol or analysis plan, and whether any adjustment for multiple comparisons was used, are not reported in the registry record.

In general, multiplicity arises when several outcomes, time points, or comparisons are tested. If many tests are conducted, the chance of at least one apparently notable result can increase unless the analysis plan addresses that issue. This is a general statistical consideration, not a claim about what happened in this study. With no posted secondary results and no detailed analysis plan, the primary comparison should be interpreted on its own terms, while recognizing that the full testing context is not available.

Missing-data handling is not reported in the registry record. The posted outcome counts are 655 for usual care and 580 for BreastCARE, but the registry does not explain whether these are all randomized participants, all participants with a completed survey, or another analysis population. It does not describe response rates, reasons for missing scores, imputation, or sensitivity analyses. These details matter because a comparison based only on observed scores can be affected if outcome availability differs systematically between groups.

The record does not report whether the analysis followed an intention-to-treat principle, whether participants were analyzed according to assignment, or how protocol deviations and intervention exposure were handled. It also does not report an adjusted model or covariate-selection plan. As a result, the posted group comparison cannot be assumed to include any particular population definition or missing-data procedure beyond what is explicitly described.

14. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 0% reporting threshold.

The registry reports 0 serious adverse events in usual care among 655 participants at risk and 0 in BreastCARE among 580 participants at risk. It also reports 0 other adverse events in usual care among 655 at risk and 0 in BreastCARE among 580 at risk. These are the adverse-event counts recorded in the registry, not proof that no events occurred outside the record’s ascertainment or reporting process.

The number of deaths is not reported in the registry record. The record does not provide serious-event terms, and no event descriptions are listed. Further details about how adverse events were defined, collected, monitored, or timed are not reported in the registry record. Without that context, the zero counts cannot characterize the completeness of safety monitoring or rule out unrecorded events.

These figures describe reported counts within the stated groups and at-risk populations. They do not provide a detailed comparison of event types, severity, timing, or relatedness. The safety information should be read as registry reporting, rather than as a comprehensive account of all possible harms.

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

The posted result indicates that the BreastCARE group had a higher mean breast cancer risk-factor knowledge score than the usual-care group at the survey conducted approximately one week after the initial visit. The estimated mean difference was 7.5 units on the 0-100 scale, with a 95% confidence interval from 4.784 to 10.22 and p < 0.001. This is evidence about the measured short-term survey outcome in the randomized comparison.

The result does not mean that every participant’s knowledge increased, that every participant benefited equally, or that the intervention changed behavior. Group averages conceal individual variation, and the registry does not report individual change scores. It also does not establish whether participants retained knowledge beyond the stated assessment time.

The intervention’s stated aims included personalized breast cancer risk information, education, and discussion of risk reduction practices. The primary outcome is knowledge, not adoption of a risk-reduction practice, a change in a clinical decision, or a breast cancer diagnosis. The posted result cannot answer whether the intervention changed those outcomes. Results for secondary outcomes are not posted in the registry record.

Statistical evidence of a nonzero difference is not the same as evidence that the difference is practically important. The registry does not report a threshold for a meaningful change in score. Nor does the p-value describe the probability that the intervention caused a meaningful improvement. The result should be interpreted in the scale units and at the assessment time actually reported.

The record describes a randomized design, but does not report all details needed to assess missing outcome data, analysis populations, or the analysis plan. Those limits do not alter the numerical comparison, but they constrain how comprehensively it can be evaluated. The most direct conclusion is that the posted groups had different average knowledge scores at the reported short-term survey assessment; broader claims are not established by this endpoint.

16. Why This Trial Matters Statistically

This study illustrates a common distinction in clinical research: an intervention may be designed to influence several steps in a pathway, while its primary endpoint measures only one of them. BreastCARE was intended to combine risk assessment, personalized information, and clinician-patient discussion. The reported endpoint captures breast cancer risk-factor knowledge on a survey. It does not directly measure changes in practice or later health outcomes.

The continuous score and mean difference make the comparison interpretable in units familiar to the endpoint. The confidence interval shows the precision of that estimated contrast, while the standard deviations describe participant-level spread. Keeping these concepts separate helps avoid treating a statistically significant comparison as if it automatically represented a large or important change for every participant.

The registry also highlights the value of detailed reporting. Information about the original sample-size justification, analysis populations, missing data, masking roles, multiplicity, and secondary results is not reported in the registry record. These details help readers understand how a result was planned and analyzed, and what conclusions can reasonably extend beyond the primary comparison.

Finally, the planning illustrations show how target sample size depends on the effect size a study aims to detect. In general, planning around a smaller effect requires more participants than planning around a larger one, given the same other assumptions. Such illustrations are useful for understanding design tradeoffs, but they do not substitute for the original protocol or establish the design choices made for this trial.

17. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

The registry contains limited detail about the intervention and comparator procedures. The BreastCARE arm description ends before the full procedure is available, and the comparison description is also incomplete. Although the intervention’s aims are described, the record does not permit a complete reconstruction of what participants and clinicians experienced or how consistently the intervention was delivered.

The primary outcome is described as an eight-question survey on a 0-100 scale, but the complete endpoint description is not reported in the registry record. Further detail on the items, scoring, validation, and handling of incomplete questionnaires is unavailable. The outcome was assessed approximately one week after the initial visit; longer-term knowledge results are not reported.

The record reports 0 analyses and no secondary results. A detailed statistical analysis plan, original sample-size justification, missing-data methods, analysis population, and multiplicity procedures are not reported in the registry record. The role and identity of those masked are also not specified. These omissions limit evaluation of the full analytic and operational context.

The registry reports zero serious and zero other adverse events in both groups, but does not describe the ascertainment procedures or provide event terms. Deaths are not reported in the registry record. The safety counts therefore offer limited detail about how events were captured and should not be interpreted as a complete safety profile.

Participant characteristics and more detailed eligibility criteria are not reported in the registry record. The posted findings consequently cannot establish how well the study population represents other settings or groups. These limitations concern the available record and do not change the reported score means or comparison; they narrow the interpretation that can be supported.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Breast Cancer Risk Reduction: A Patient Doctor Intervention — NCT01830933.
• Registry record last updated 2014-08-19; status last verified 2014-08.
• Results first posted 2013-05-16.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

21. Record Summary

NCT01830933 is a completed randomized, single-masked, parallel-group study sponsored by the University of California, San Francisco. The record reports enrollment of 1235, a study start of 2011-06, and primary completion in 2012-08. The intervention was BreastCARE, a tablet-PC-based breast cancer risk education approach; usual care was the comparator.

The primary outcome was knowledge of breast cancer risk factors, measured by post-survey approximately one week after the initial visit on a 0-100 scale. The posted means were 56.4 for BreastCARE and 48.9 for usual care. The unadjusted mean difference was 7.5 units, with a 95% confidence interval from 4.784 to 10.22 and p < 0.001. No secondary results are posted. The registry reports 0 serious and 0 other adverse events in each group; deaths are not reported in the registry record.