DUS on the Prescribing Indications for CPA/EE in 5 European Countries: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for DUS on the Prescribing Indications for CPA/EE in 5 European Countries (NCT02494297), a registered phase not stated study. The primary outcome is Drug Utilization Pattern of Cyproterone Acetate and Ethinyl Estradiol.

2. Clinical Question

3. Trial Design

This is a completed drug utilization study focused on why health care providers prescribe cyproterone acetate and ethinyl estradiol. Its stated purpose is to characterize prescribing behavior in Austria, Czech Republic, France, the Netherlands, and Spain. The study is not described as a randomized treatment comparison. The registry states that allocation is not given and cautions that the study groups are not a like-for-like control comparison.

The listed group is users of Diane 35, identified as EE/CPA and BAY86-5264 in the group description. The registry records enrollment of 1597 participants. It does not explain whether that enrollment is the number with complete outcome information, how participants were recruited, or how many were included in each country. Those details are not reported in the registry record.

The study start date is 2015-03-06, and the primary completion date is 2016-10-31. Its status is completed. The primary outcome timeframe is described as within 18 months. Information was obtained from doctors prescribing CPA/EE, and the outcome categories are said to be based on current disease status. The record does not provide further detail about the timing or method of data collection.

The registry lists one outcome measure and no analyses. It does not describe a comparator treatment, a randomization method, masking, or a planned statistical analysis. These details are not reported in the registry record, so the design should be interpreted as a descriptive account of prescribing patterns rather than as evidence from a controlled treatment-effect comparison. The sponsor is the Center for Epidemiology and Health Research, Germany.

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 Drug Utilization Pattern of Cyproterone Acetate and Ethinyl Estradiol, measured over within 18 months.

The primary outcome is titled Drug Utilization Pattern of Cyproterone Acetate and Ethinyl Estradiol. Its unit is participants, and its measurement is a count of participants. The registry says doctors prescribing CPA/EE provided information and that the outcome categories are based on current disease status. The stated timeframe is within 18 months.

A participant count can describe how prescribing indications or disease-status categories are represented in the study population. In a drug utilization study, such a description is useful for understanding the reasons recorded by prescribers and whether use is reported in relation to the updated label, concomitant use with combined hormonal contraceptives, and second-line treatment for acne. These are the study’s stated areas of interest, not treatment-effect comparisons.

The registry does not provide the category definitions, counts, or other outcome values. It therefore does not permit a reader to determine which indications were most frequent or how participants were distributed across categories. Although enrollment is recorded as 1597, the outcome results needed to interpret category counts are not reported in the registry record. The endpoint is descriptive as registered; it is not an estimate of the effect of CPA/EE compared with a control treatment.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

Statistical methods determine how collected observations are summarized and what kinds of conclusions those summaries can support. In this study, the registered primary measure is a count of participants, and the stated objective is to describe prescribing behavior. That makes descriptive summaries a natural way to present the outcome: each category would be characterized by the number of participants assigned to it, provided the categories and analysis population are defined. The registry record does not report those counts or a fuller statistical analysis plan.

What does a participant count describe?

A count records how many participants meet a stated category definition. It is not automatically a percentage, a rate, or a comparison of treatment effects. Interpreting a count requires knowing what the category means and who was eligible to be counted. Here, the registry says categories are based on current disease status, but does not list their definitions or report their values. The enrollment figure of 1597 describes study enrollment; it does not establish how many participants had usable information for a particular category.

Counts can be presented without statistical modeling. If uncertainty is quantified, a confidence interval is one general way to show the range of values compatible with the observed data under a specified statistical procedure. A confidence interval is not a guarantee that the true value lies within its limits, and its interpretation depends on the sampling and analysis assumptions. No confidence intervals are reported in the registry record. Without category results, no precision assessment can be made for the primary outcome.

Why does the study design matter?

A randomized comparison assigns participants to treatment groups using a random process. That design can support a causal comparison when it is properly conducted and analyzed. This study is described as not being a randomized comparison, and allocation is not stated. Its listed group is users of CPA/EE; the record does not identify a comparable control group. Therefore, the registered objective is descriptive, not an estimate of how outcomes differ because of treatment assignment.

In general, an observational comparison can be affected by differences in the characteristics of people who receive different treatments or have different indications. Statistical adjustment may address measured differences under specific assumptions, but it cannot guarantee removal of unmeasured confounding. The registry lists no analyses, so it does not report whether any adjustment was planned or performed. It would be inappropriate to infer an adjustment strategy or a causal estimand from the study objective alone.

What is the role of the planning illustration?

A sample-size planning illustration asks how many participants might be needed under specified assumptions to detect a chosen effect with a stated statistical power. The registry’s planning description specifies a two-sided significance level of 0.05, equal allocation between two arms, a normal approximation, and an effect expressed as a fraction of the observed effect. It says that participant counts are used per arm for non-time-to-event outcomes, while time-to-event illustrations use total events. These are planning assumptions, not evidence that the study used that design or achieved a particular power.

In general, a planning calculation depends on assumptions about the effect to detect, variability, allocation, and statistical procedure. A calculation based on an observed effect is especially dependent on that effect estimate: if the estimate is imprecise, the planning result inherits that uncertainty. A planning illustration is not observed power and cannot show that a completed study had adequate power. In this case, the registry record does not provide the observed outcome values needed to interpret an effect-based illustration, nor does it establish the study’s own sample-size justification. The study’s enrollment of 1597 is not, by itself, evidence of a particular power or design target.

What can be said about hypothesis tests?

A p-value, when reported, measures how compatible data are with a specified statistical model and null hypothesis; it is not the probability that the null hypothesis is true. A significance threshold is a decision convention, not a measure of clinical importance. The planning description mentions a two-sided significance level, but the registry lists no analyses and reports no p-values. That planning convention should not be mistaken for evidence that hypothesis tests were performed or that a particular statistical plan was prespecified.

Multiplicity arises when several hypotheses or outcome comparisons are evaluated. Testing many questions can increase the chance of at least one apparently noteworthy result if no strategy addresses that issue. The study has several stated descriptive objectives, but the record does not report a testing hierarchy, multiplicity adjustment, or inferential analysis. Since no analysis results are listed, the statistical consequences of multiple comparisons cannot be assessed.

Why does over-dispersion matter in general?

Over-dispersion is a general concern for count models when observed counts vary more than the model’s assumptions allow. It can lead to uncertainty estimates that are too small if a model assumes less variation than the data contain. This is relevant when counts are analyzed using a statistical model, but the registry identifies a count outcome without reporting a count model, dispersion estimate, or model-based analysis. It is therefore not possible to say whether over-dispersion was assessed or whether it affected any reported result.

For this study, the central statistical limitation is not a known modeling failure but the absence of reported outcome values and analyses. The registry supports understanding the intended descriptive question and the broad measurement approach. It does not support reconstructing the analysis, evaluating precision, or inferring a treatment effect.

10. Multiplicity, Missing Data and Analysis Populations

The registry lists one primary outcome measure and no analyses. The study objective includes several related topics: prescribing indications, use in accordance with the updated label, concomitant use with combined hormonal contraceptives, and second-line treatment with CPA/EE for acne. The record does not explain whether these topics were treated as separate outcomes, descriptive subgroups, or components of a prespecified analysis plan. It also does not report a testing hierarchy or a procedure for handling multiplicity. Because no analyses or results are listed, it is not possible to assess how multiple questions were handled.

Missing-data methods and analysis populations are not reported in the registry record. The record does not say how many participants had complete information for the primary outcome, whether participants with missing information were excluded, or how missing values were handled. Enrollment of 1597 should not be assumed to equal the number included in every outcome category. The information source is doctors prescribing CPA/EE, but the registry does not describe data completeness or validation procedures.

The registry also does not identify a detailed analysis population, such as a population defined by eligibility, exposure, or availability of outcome information. It does not report sensitivity analyses or specify how country-level data were combined. These omissions limit the ability to assess selection into the analysis, representativeness of the recorded data, and robustness of any results. They do not establish that missing data or multiplicity problems occurred; they mean that these issues cannot be evaluated from the registry record.

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

The record describes a completed study designed to characterize prescribing of CPA/EE in five European countries. It identifies doctors as the source of prescribing information and states that the primary outcome is a count of participants classified by current disease status within 18 months. The study’s stated scope includes prescribing indications, use in accordance with the updated label, concomitant use with combined hormonal contraceptives, and second-line use for acne. Those details explain what the study set out to describe.

The record does not report the outcome counts, category-specific results, estimates of uncertainty, or analyses. It therefore does not establish how common any indication was, whether prescribing differed across countries, or how frequently the other stated prescribing circumstances occurred. The listed conditions are not accompanied by participant counts, and they should not be treated as findings about the frequency of diagnoses in the study.

The study is not a randomized comparison, and the record does not identify a like-for-like control group. Its objective is to describe use and prescribing, not to determine a comparative treatment effect. It cannot, on the information reported, establish that CPA/EE caused an outcome, that it was more or less effective than another option, or that a particular prescribing pattern led to a particular clinical result.

The adverse-event fields list zeros for serious and other events at risk and affected, while deaths are not reported. Those entries are not enough to establish the absence of adverse events, because the record does not provide the collection methods, definitions, or analysis context. The main defensible conclusion is about study intent and measurement: the registry describes a physician-informed drug utilization study, but does not include the results needed to quantify its findings.

12. Why This Trial Matters Statistically

Drug utilization studies address a different statistical question from randomized treatment trials. Rather than estimating a treatment contrast, they can describe how medicines are prescribed and which indications are recorded in routine practice. That distinction matters because a descriptive count can inform understanding of prescribing patterns without establishing that a treatment caused a clinical outcome. The registered objective for this study is explicitly centered on prescribing behavior for CPA/EE.

The study spans Austria, Czech Republic, France, the Netherlands, and Spain, and its stated objectives include several aspects of use beyond the broad indication for prescribing. This makes clear reporting important: readers need category definitions, country-specific or combined counts, and a description of who contributed outcome data to understand how representative the summary is. The registry gives the general outcome approach but does not report those details or results.

The example also illustrates why enrollment alone does not convey statistical precision. The registry records 1597 participants, but without the outcome counts and analysis population, readers cannot assess the precision of any specific prescribing category. Nor can an effect-based planning illustration be interpreted as proof of observed power. The relevant information is the observed result and its uncertainty, alongside the design and analysis methods.

Finally, registration can clarify a study’s intended questions, but it is not a substitute for a complete results report. Here, the record documents a completed study and its primary outcome description while listing no analyses. That gap prevents a statistical assessment of what prescribing patterns were actually observed. Recognizing that boundary helps keep conclusions aligned with the evidence available.

13. 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 principal limitation for interpreting this study from the registry record is that it does not report the primary outcome results. No counts by prescribing indication or current disease-status category are given, and no estimates of uncertainty are reported. Consequently, the stated descriptive objective cannot be assessed quantitatively from the registry information.

The record does not define the outcome categories in detail, describe the eligibility criteria, or explain how doctors and participants were selected. Information was obtained from doctors prescribing CPA/EE, but the method of collection, verification, and handling of incomplete reports is not reported. The recorded enrollment of 1597 does not establish the number with data available for each outcome.

The study is not a randomized comparison, and allocation is not stated. No like-for-like control comparison is described, so the record does not support a comparative treatment-effect interpretation. It also does not report whether results were adjusted for participant or country differences. The five-country scope is stated, but the record does not provide country-level enrollment or results, limiting assessment of how patterns varied across settings.

The registry lists no analyses and does not describe missing-data methods, analysis populations, or a multiplicity strategy. It also does not provide enough information to evaluate the adverse-event fields, which list zeros for the reported event-count fields while deaths are not reported. These limitations concern what can be established from the registry record; they do not prove that the study lacked additional methods or findings outside it.

14. Related Tutorials

15. Related Statistical Calculators

16. Sources

• ClinicalTrials.gov: DUS on the Prescribing Indications for CPA/EE in 5 European Countries — NCT02494297.
• Registry record last updated 2021-08-27; status last verified 2021-08.
• Results first posted 2021-08-27.
• 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.

17. Record Summary

NCT02494297 is a completed drug utilization study titled DUS on the Prescribing Indications for CPA/EE in 5 European Countries. The official title describes a study of prescribing indications for cyproterone acetate and ethinyl estradiol in Austria, Czech Republic, France, the Netherlands, and Spain. The sponsor is the Center for Epidemiology and Health Research, Germany. The registry records enrollment of 1597, a start date of 2015-03-06, and a primary completion date of 2016-10-31.

The primary objective was to characterize prescribing behavior. The primary outcome is a count of participants categorized by current disease status, within 18 months, using information obtained from prescribing doctors. The registry lists one outcome measure and no analyses. It does not report category counts, analysis results, or detailed methods for missing data and analysis populations. The record identifies no randomized comparison and no like-for-like control group.