Decision-aid on Breast Cancer Screening: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Decision-aid on Breast Cancer Screening (NCT03097653), a randomized na study. The primary outcome is Number of Participants With Adequate Knowledge.

2. Clinical Question

The study focuses on informed choice rather than a clinical treatment outcome. Knowledge was one component of the intended assessment; attitudes and intentions were also identified in the study aim, but the posted primary endpoint is the number of participants with adequate knowledge. The registry record lists other outcomes concerning screening participation, satisfaction, web-platform activity and decisional conflict.

The central comparison is between randomized groups, with the decision-aid group compared against the standard-information group. The question is therefore whether the posted knowledge results differ between those assigned to the two ways of receiving information. The registry record does not report a more detailed target population description, such as participant age or screening history, so the interpretation should remain tied to the population described in the record rather than extended to a more specific group.

3. Trial Design

The registry record describes a randomized, parallel-group study with no masking. Participants were assigned to a web decision aid or to standard web information. The sponsor was the Mario Negri Institute for Pharmacological Research. The study is marked completed, with enrollment of 1001.

The registry lists the study start as 2017-09-01 and primary completion as 2019-04-20. The primary outcome was assessed at 7-10 days. The study title describes it as multi-centre, longitudinal and controlled; the record does not give further details on the centres, allocation procedure, concealment, or follow-up procedures. It also does not report a phase beyond NA.

For the primary outcome, the registry reports 472 participants in the decision-aid group and 529 in the standard-information group. The outcome counts were 236 and 218, respectively. The reported endpoint is a count of participants meeting the adequate-knowledge threshold, rather than a mean questionnaire score. The record does not report whether every randomized participant contributed to this outcome or how any unavailable outcome data were handled.

Secondary outcomes included the breast cancer screening programme participation rate, satisfaction with information, homepage clicks, visits to the web platforms, pages visited and decisional conflict measured with the Decisional Conflict Scale-SURE Version. Posted results are available for screening participation and number of web-platform accesses. Although the registry lists additional secondary outcomes, results for every listed outcome are not reported in the registry record.

The design description establishes a randomized comparison, but does not establish the details of the statistical plan. The original sample-size justification, planned analysis population, procedures for missing data, and any planned interim analyses are not reported in the registry record. These details matter when assessing how closely posted comparisons reflect the intended analysis.

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.

6. Primary Endpoint

The registry lists the primary outcome as Number of Participants With Adequate Knowledge, measured over 7-10 days.

The primary endpoint counts participants classified as having adequate knowledge about breast cancer screening. Knowledge was assessed with a questionnaire containing 13 multiple-choice questions, with 2 to 4 answer options. Ten questions were qualitative and 3 were numerical. A score of 8 out of 13, described in the record as about 60%, or higher was considered adequate knowledge.

This threshold turns the questionnaire result into a binary outcome: each participant is counted as either meeting the definition or not meeting it. A binary endpoint can make the result easier to interpret as a count or proportion of participants reaching a prespecified level, rather than as a change in average score. However, the registry record does not report the full questionnaire, scoring details beyond the threshold, or whether the threshold was established before the study began.

The endpoint is relevant to the stated aim because the decision aid was intended to support informed choice, and knowledge was one of the stated dimensions of informed choice. It does not, by itself, measure all components of informed choice: the study aim also mentions attitudes and intentions, and the registry lists decisional conflict as a secondary outcome. Nor does the endpoint establish whether an individual made a choice aligned with their values. It reports how many participants met the knowledge criterion at the stated assessment time of 7-10 days.

7. Results Posted in the Registry

• Decision-aid: 50.0% (236/472) versus 41.2% (218/529) on control; risk difference 8.8 percentage points (95% CI 2.6 to 14.9), risk ratio 1.21 (1.06–1.39); unadjusted two-proportion z-test p = 0.005.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Participation Rate to the Breast Cancer Screening Programme

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Decision-aid: 84.1% (376/447) versus 83.0% (416/501) on control; risk difference 1.1 percentage points (95% CI -3.6 to 5.8), risk ratio 1.01 (0.96–1.07); unadjusted two-proportion z-test p = 0.654.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Decision-aid and the control. The interval gives the range of effects that remain compatible with the data.

Number of Times Web Platforms Were Accessed

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Decision-aid: mean 1.10 versus 1.00 on control; difference 0.10 (95% CI 0.07 to 0.13), standardized effect d = 0.46; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Decision-aid than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The posted secondary outcomes give a mixed picture across behavior and engagement. Screening participation was similar in the two groups in the observed results, while the mean number of web-platform accesses was higher in the decision-aid group. These outcomes are related to the study's overall aim but measure different things. Platform access captures interaction with the information environment; screening participation captures a subsequent behavior. Neither is equivalent to the primary measure of adequate knowledge.

This pattern does not establish whether greater engagement led to greater knowledge, or whether knowledge influenced participation. The registry does not report individual-level associations among these outcomes, mediation analyses, or a sequence of measurements that could answer such questions. Nor does it report results for all the secondary outcomes listed, including satisfaction, homepage clicks, pages visited and decisional conflict. The overall secondary evidence is therefore incomplete.

Unadjusted secondary comparisons carry less weight when several outcomes are examined because the chance of at least one apparently unusual result can increase across multiple tests. In general, multiplicity procedures can address this issue, but the registry record does not report a prespecified strategy or adjusted results. An unadjusted finding should be viewed as a result for that endpoint, with due attention to uncertainty, rather than as confirmation of a broad claim about all aspects of informed choice.

The primary outcome remains the clearest direct test of the registered focus on knowledge. The secondary outcomes provide context about screening behavior and web engagement, but they do not independently confirm or overturn the primary comparison. Since several listed secondary measures have no posted results, the available outcomes should not be treated as a complete account of every intended dimension of the intervention.

Secondary outcomes registered for this trial, for reference (only those above were recalculated):

• Participation Rate to the Breast Cancer Screening Programme
• Satisfaction With the Information Measured Using 8 Items With Three Points Scale
• Number of Click on the Homepage
• Number of Times Web Platforms Were Accessed
• Number of Pages Visited on the Web Platforms
• Number of Participants With Decisional Conflict Using Decisional Conflict Scale-SURE Version

9. Statistical Interpretation

10. Statistical Methods Explained

What does a binary outcome represent?

The primary endpoint is a count of participants who met the adequate-knowledge definition. In general, a binary outcome sorts each participant into one of two categories, such as meeting or not meeting a criterion. The risk, or proportion, is the number meeting the criterion relative to the number assessed. A risk difference compares the two group proportions by subtraction. A positive difference in this comparison means that the observed proportion was higher in the decision-aid group than in the standard-information group.

The registry also posts a risk ratio and an odds ratio for the primary comparison. In general, a risk ratio compares the two group proportions as a ratio, while an odds ratio compares the odds of the outcome between groups. Values of 1 indicate no relative difference for these ratio measures; values above 1 indicate a higher outcome frequency in the decision-aid group in this comparison. These measures answer related, but not identical, questions. The absolute risk difference is often useful for describing how far apart the groups are on the outcome's original proportion scale.

What does randomization contribute?

Random assignment is intended to make the comparison between groups less vulnerable to systematic differences at the start of a study. In general, randomization supports a causal interpretation when assignment is implemented as planned, outcomes are measured comparably, and the analysis preserves the randomized comparison. The registry identifies the study as randomized, but does not report the allocation sequence, concealment procedures, or analysis population. Those unreported details limit assessment of how the randomized design was carried through the analysis.

The study was unmasked. In general, when participants know which information option they receive, their expectations or behavior may differ by group. This can matter for outcomes involving self-reported knowledge, satisfaction or platform use. The registry record does not give enough detail to determine how outcome assessment was conducted or whether the assessors knew assignment. The primary outcome's questionnaire-based definition is described, but its full administration and scoring procedures are not reported.

How should the p-values be read?

A p-value measures how incompatible the observed data are with a specified no-difference model, under the assumptions of the statistical test. A small p-value is not the probability that the null hypothesis is true, and it does not measure the size or practical importance of a difference. The primary comparison has an unadjusted p-value of 0.005. The screening participation comparison has an unadjusted p-value of 0.654, and the web-platform access comparison has an unadjusted p-value of <0.001.

The record calls these comparisons unadjusted and lists no reported analyses. It does not identify the tests used for the comparisons or state whether an adjustment was planned. The p-values should therefore be read alongside the estimated contrasts and their confidence intervals, not as stand-alone verdicts.

Why does dispersion matter for a mean?

The web-platform access result is reported as a mean with a standard deviation. In general, a mean describes the average value, while the standard deviation describes the spread of individual observations around that average. The uncertainty around a group mean depends on both the observed spread and the amount of information available. The registry reports a standard deviation of 0.3 in the decision-aid group and 0.1 in the standard-information group. A comparison of means should account for uncertainty in both groups, rather than treating their estimates as error-free.

Over-dispersion is a general concern when count data vary more than an assumed model allows. If a count analysis assumes less variability than is present, its uncertainty may be understated. The posted access outcome is reported as a mean and standard deviation, and the registry does not describe a count model or report a dispersion parameter. It is therefore not possible to determine from the record whether a model accounting for over-dispersion was used.

What can be concluded from the posted analysis details?

The registry provides group counts and summary statistics, along with unadjusted comparisons for the posted results. It does not report covariate-adjusted estimates, sensitivity analyses, subgroup analyses, or a statistical analysis plan. This does not establish that such analyses were or were not conducted outside the registry; their status is not reported in the registry record. The estimated comparisons should be understood as the posted group-level results, not as evidence about unreported adjusted analyses.

The endpoint's threshold is central to interpretation. A participant just below the threshold and a participant with a much lower score are both counted outside the adequate-knowledge category. Conversely, participants at or above the threshold are grouped together. In general, dichotomizing a score can simplify communication, but it discards information about the score's distribution. The record does not post the full score distribution, so the group counts cannot reveal how far participants were from the cutoff.

The trial's planning assumptions are also distinct from the posted comparison method. The registry does not report the original sample-size justification or the detailed analysis plan. Planning figures based on observed effects are illustrations rather than evidence that the trial had a particular probability of detecting the observed result. The interpretation of the estimate rests primarily on the posted outcomes, their uncertainty, and the limitations in the analysis information recorded.

11. Confidence Intervals and Precision

A confidence interval describes a range of effect estimates compatible with the observed data under the model and method used. It communicates uncertainty in the estimated contrast; it is not a range containing every participant's outcome, nor does it assign a probability to a particular effect after the data have been observed. In general, narrower intervals indicate greater precision, while wider intervals indicate less precision.

For the primary risk difference, the posted interval lies above no difference. This is consistent with the point estimate favoring a higher proportion meeting the adequate-knowledge threshold in the decision-aid group. The posted risk-ratio interval also lies above 1. These interval patterns align with the unadjusted p-value of 0.005. They describe statistical uncertainty in the group contrast, not certainty about the cause of every participant's outcome or the importance of the difference to individuals.

The screening participation interval includes no difference. This means the posted data are compatible with a range that includes little or no group separation, as well as values on either side of no difference. The corresponding unadjusted p-value is 0.654. The access outcome interval lies above no mean difference, in line with its unadjusted p-value of <0.001. These contrasts concern distinct outcomes and should not be interpreted as a single combined effect.

Confidence intervals do not account for every limitation. The record does not report how missing outcome data were handled, whether estimates were adjusted, or how multiplicity was addressed. If such analytic choices affect the estimate or its uncertainty, that information is not available in the registry record. Precision should therefore be read as conditional on the reported comparison, not as a complete description of all uncertainty in the study.

12. 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 illustrations based on the observed effect, not the trial's original design justification. The registry record does not report the original design assumptions. The figures use a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each planning scenario uses the stated fraction of the observed effect as the effect to detect.

For the binary outcomes, the figures are participants per arm. They are not total participants across both arms and are not total events. For time-to-event outcomes, the stated convention would instead be total events, but no time-to-event outcome is posted in these results. In reading a planning row, the 80% power column gives the estimated participants per arm under which the design would have an 80% chance of detecting the specified effect, if the listed assumptions and model were appropriate. The 90% power column describes the corresponding planning target for a 90% chance.

The rows that plan for 100%, 75% or 50% of the observed effect represent different assumed effect sizes. Smaller effects require more participants per arm to detect under the same planning assumptions. The resulting figures can vary substantially by endpoint because observed effects and outcome variability differ. For example, the primary knowledge contrast and the screening participation contrast have different observed effects, and their planning requirements are correspondingly different. These illustrations are not observed power: observed power is not a useful substitute for reading the estimated effect and its confidence interval after a study is complete.

These figures do not show whether the enrolled trial was adequately planned, because the original sample-size assumptions and justification are not reported in the registry record. They also do not establish that the chosen planning model matches every feature of the trial. Their purpose is to illustrate how the required group size changes when the assumed effect to detect changes, not to replace interpretation of the posted outcomes.

13. 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, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.412; treatment proportion p₁ = 0.500; average p̄ = 0.456.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.7044 = 1.3805.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.7016 = 0.5905.
4. n = (1.3805 + 0.5905)² / (0.0879)² = 502.8, rounded up to 503 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
p0 <- 0.412098298676749                          # control proportion
p1 <- 0.5                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^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 (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(3097653)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 503 (80% power), 673 (90% power)
 75% of observed effect: n per arm = 891 (80% power), 1,193 (90% power)
 50% of observed effect: n per arm = 1,996 (80% power), 2,671 (90% power)
power.prop.test: 502.8 
Simulated power at n = 503 per arm: 0.805 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-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.

14. Multiplicity, Missing Data and Analysis Populations

The registry lists a primary outcome and multiple secondary outcomes. When many endpoints are tested, some comparisons can appear notable by chance even if there is no underlying difference. In general, a multiplicity plan may define which outcomes are confirmatory and how the overall error rate is controlled. The registry record does not report whether such a plan existed, whether the listed secondary outcomes were ranked, or whether any correction was applied. The posted p-values are unadjusted.

The record reports no analyses for the primary outcome and no reported analyses for the posted secondary outcomes. It gives group summaries and unadjusted comparisons, but does not describe the analysis population, model specification, or handling of missing results. The number of randomized participants differs from the outcome-specific denominators for screening participation. The registry does not explain the reasons for those denominators or describe whether unavailable observations were excluded, imputed, or handled in another way. A difference in denominators alone does not establish why observations are absent.

It is also not reported whether the analysis followed an intention-to-treat principle, whether participants were analyzed according to assignment, or whether a per-protocol population was used. The record does not report missingness by group, reasons for missingness, or sensitivity analyses assessing the effect of missing data. These omissions limit evaluation of possible bias, especially for outcomes with outcome-specific participant counts.

The registry record does not report interim analyses, stopping rules, subgroup plans or a statistical analysis plan. It is not possible to infer these procedures from the posted estimates. The same applies to baseline adjustment and any prespecified handling of multiple outcomes. Without these details, the reported comparisons should be read as the registry's posted summaries and not as a complete account of all analytic decisions.

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

The primary result describes a higher observed proportion of participants meeting the adequate-knowledge threshold in the decision-aid group than in the standard-information group. The estimate and its confidence interval indicate a difference in this trial's randomized groups at the stated assessment period. This is evidence about the defined questionnaire outcome, not a direct measure of every aspect of informed choice.

The result does not establish that the decision aid changed screening participation. The posted participation comparison is compatible with no group difference, and the registry lists further secondary outcomes without posting their results. Nor does the primary outcome establish that participants made choices consistent with their values, that they retained information over a longer period, or that screening decisions improved. Those questions require outcomes and analyses not reported in the registry record.

In general, randomization supports comparisons between assigned groups, but interpretation still depends on follow-up, measurement and analysis. The registry does not describe missing-data procedures, a detailed analysis plan, or the population included in each analysis. The primary outcome denominators are reported, but the record does not explain how participants without an observed outcome were handled. The unmasked design may also be relevant to outcomes that depend on participant responses or engagement.

The study is about a decision aid and standard web information in women newly invited to breast cancer screening, as described in the title. The registry does not provide enough population details to assume that the findings apply identically to other groups, information systems or screening settings. The posted comparisons do not establish broader clinical benefits or harms. No adverse-event counts are recorded for either arm, but the registry's zero entries do not provide enough detail to conclude that no adverse experiences occurred.

The most defensible reading is narrow: the posted trial results show a group difference in the binary knowledge outcome, a less clear separation in screening participation, and a difference in web-platform access. The estimates describe the outcomes as registered and posted; they do not answer questions that were not measured or reported.

16. Why This Trial Matters Statistically

This trial is statistically interesting because its central outcome converts a knowledge questionnaire into a threshold-based binary measure. That choice makes the comparison straightforward to express as the number of participants meeting a defined standard, but it also discards distinctions among scores within each category. A reader should therefore distinguish evidence about crossing the threshold from evidence about the full distribution of knowledge.

The study also places several kinds of outcomes side by side: knowledge, screening participation and use of web platforms. Those measures represent different points in a possible decision process and should not be treated as substitutes. The posted pattern illustrates why a difference in information engagement or knowledge need not appear as an equally clear difference in subsequent behavior. The registry does not report analyses that would explain connections among these outcomes.

From a biostatistical perspective, the record illustrates the importance of reading estimates with their uncertainty, while also recognizing what registry reporting leaves unresolved. Unadjusted p-values, multiple listed endpoints, outcome-specific denominators and absent details about missing-data handling all affect how confidently the findings can be characterized. The observed-effect planning illustrations also underscore that sample-size requirements depend on the effect a future study aims to detect, rather than being a fixed property of the endpoint.

The study's value for statistical interpretation lies in the contrast between a defined primary endpoint and a broader set of registered secondary questions. The primary outcome has a posted comparison, while several listed secondary outcomes do not. Keeping those distinctions clear prevents a single result from being expanded into a claim about every intended aspect of informed choice.

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 record does not provide detailed participant eligibility criteria, recruitment methods, participant characteristics, or the screening context beyond the study title and condition. This restricts assessment of how representative the analyzed participants may be and how widely the findings apply. It also does not describe the content of the decision aid or standard information sufficiently to assess their substantive differences.

The primary endpoint uses a cutoff of 8 out of 13 questionnaire answers, but the full questionnaire, validation information and rationale for the threshold are not reported in the registry record. The binary result does not show the distribution of scores or how close participants were to the cutoff. The timeframe is 7-10 days, so the posted primary endpoint does not describe longer-term knowledge.

The study is unmasked, and the registry does not report how outcomes were administered or whether assessment was independent of group assignment. This matters particularly for self-reported or engagement-related measures. The record does not report missing-data methods, reasons for outcome-specific denominators, an analysis population, or sensitivity analyses. Details of allocation concealment and the randomization procedure are also not reported.

Several secondary outcomes are registered, but results for all of them are not reported in the registry record. Multiplicity handling and the statistical analysis plan are not reported. The adverse-event entries show zeros for the listed categories, while details about adverse-event collection and definitions are not reported. These limitations concern what can be established from the registry record; they do not establish that the unreported procedures or information were absent from the conduct of the study.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Decision-aid on Breast Cancer Screening — NCT03097653.
• Registry record last updated 2021-03-24; status last verified 2021-03.
• Results first posted 2021-03-24.
• 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

NCT03097653, titled “Decision-aid on Breast Cancer Screening,” is a completed randomized, parallel-group, unmasked study. The registry describes enrollment of 1001 and compares an interactive web decision aid with standard web information for women newly invited to breast cancer screening. The sponsor is the Mario Negri Institute for Pharmacological Research.

The primary outcome was the number of participants with adequate knowledge at 7-10 days, defined as a score of at least 8 out of 13 questionnaire questions. The posted counts were 236 of 472 in the decision-aid group and 218 of 529 in the standard-information group. The estimated primary comparison favors a higher proportion meeting the threshold in the decision-aid group, with an unadjusted p-value of 0.005.

Posted secondary results include screening participation and web-platform access. The registry lists additional secondary outcomes, but results for all listed outcomes, analysis-plan details, missing-data procedures and multiplicity handling are not reported in the registry record.