Observational Trial With Enbrel: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Observational Trial With Enbrel (NCT00488475), a registered phase not stated study. The primary outcome is Percentage of Participants Achieving Functional Remission Determined by Hannover Functional Ability Questionnaire (FFbH) at Week 26.

2. Clinical Question

In practical terms, this is a descriptive question about functional ability among people receiving etanercept in routine care. It is not a randomized comparison of etanercept against another treatment or against no treatment. The endpoint definition indicates what would count as remission, but without the observed result and analysis population size, the registry record cannot establish how many participants met that definition or how precisely the percentage was estimated.

3. Trial Design

The registry identifies NCT00488475 as a completed observational study titled “Observational Trial With Enbrel.” Its official title describes a one-year observational study of etanercept in routine German clinical practice for rheumatoid arthritis, with health-economic, safety, and effectiveness evaluation. Enrollment was 4945, and the listed intervention was etanercept. The record identifies rheumatoid arthritis as the condition of interest.

Unlike a randomized controlled trial, this study did not report randomized allocation. The registry record does not state an allocation method, and it does not describe a concurrent control group. The intervention and participant information therefore support a description of etanercept use, not a randomized treatment contrast. The summary explains the rationale for observational assessment in routine practice and mentions comparison with a previous study of similar design as a study aim. Results of a historical comparison are not reported in the registry record.

The primary outcome is the percentage of participants achieving FFbH functional remission at week 26. The record lists additional outcomes covering quality of life, work productivity and activity impairment, health-care resource use, working disability, disease activity, and swollen-joint count. It identifies 23 outcome measures, but the results for those measures are not reported in the registry record. The specific number analyzed for the primary endpoint is also not reported. The effectiveness population is defined as adults with confirmed rheumatoid arthritis, no prior etanercept treatment, and post-baseline documentation.

The record marks the study completed. It lists a start date of 2006-09 and a primary completion date of 2013-04. Those registry dates do not by themselves establish how long each participant was observed; participant-level follow-up duration is not reported in the registry record. The planned one-year duration in the title should therefore not be treated as evidence that every participant contributed a full year of follow-up.

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

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Effectiveness population included all participants \>= 18 years of age, confirmed diagnosis of rheumatoid arthritis, who had not received treatment with etanercept previously and who had post baseline documentations. Here 'N' (number of participants analyzed) signifies those participants who were evaluable for this measure.

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: Safety population included all participants with available documentations.

6. Primary Endpoint

The registry lists the primary outcome as Percentage of Participants Achieving Functional Remission Determined by Hannover Functional Ability Questionnaire (FFbH) at Week 26, measured over Week 26.

The primary endpoint is the percentage of participants achieving functional remission on the Hannover Functional Ability Questionnaire at week 26. The FFbH asks 18 questions about daily activities during the last 7 days. Responses distinguish performing an activity without difficulty, performing it with some difficulty, and being unable to perform it or needing help. Responses are scored, and the functional-capacity score is scaled from 0 to 100, with higher scores indicating better daily activities. Functional remission is defined as a score at least 83%.

This endpoint focuses on a participant’s reported ability to carry out everyday activities, rather than solely on joint counts or a laboratory measure. Converting the score into a remission category creates an outcome that can be expressed as a percentage, but it also means that people just below and just above the cutoff are classified differently even when their underlying scores are close. The continuous score and the remission category answer related but distinct questions.

In general, a confidence interval around a percentage communicates the statistical uncertainty associated with estimating the population percentage from the analyzed participants. The registry record names a 95% confidence interval as the endpoint’s dispersion measure, but the actual percentage, interval limits, and analyzed denominator are not reported in the registry record. Thus, the endpoint definition is available, while its observed magnitude and precision are not.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The statistical information in the registry record is limited. It describes an observational study, defines the primary endpoint, names a confidence-interval measure, and lists safety counts. It does not report the primary outcome estimate, interval limits, analysis denominator, or analysis details. The concepts below explain how such quantities are generally interpreted; they do not describe unreported procedures from this study.

What does a percentage endpoint represent?

For a binary outcome such as achieving or not achieving functional remission, the percentage is the proportion of analyzed participants classified as having the outcome. The denominator matters: it should reflect the participants whose outcome status was included in the analysis, not automatically everyone enrolled. When assessments are missing or participants do not meet the specified effectiveness-population criteria, the analysis denominator may differ from enrollment. The number analyzed for the primary endpoint is not reported in the registry record, so neither the observed percentage nor its denominator can be reconstructed from the posted information.

The FFbH remission category is based on a threshold applied to a functional-capacity score. A threshold makes results easier to express as a remission proportion, but it discards some detail in the original score. Two participants with similar scores near the cutoff can fall into different categories, while participants with quite different scores on the same side of the cutoff share the same binary outcome classification. Reporting the continuous score alongside a remission percentage can, in general, offer complementary information. Whether and how that was done for the primary endpoint is not reported in the registry record.

How should a confidence interval be read?

In general, a confidence interval describes the uncertainty around an estimate under the statistical method used. For a percentage, a narrower interval indicates greater statistical precision than a wider interval, given the analysis and assumptions. It is not a range containing a known, fixed proportion of individual participant outcomes, and it does not account automatically for systematic problems such as selection bias, measurement error, or missing outcome data. The primary endpoint specifies a 95% confidence interval, but neither the estimate nor interval bounds are reported in the registry record. Its precision therefore cannot be assessed.

Why does observational design matter?

In general, random allocation can help balance measured and unmeasured prognostic factors between comparison groups. In an observational study, treatment is used in clinical practice rather than assigned by randomization, so groups or participants may differ in ways that relate to outcomes. This study record does not identify a concurrent comparison group or an allocation method. A descriptive percentage among participants receiving etanercept can characterize that observed group, but a treatment effect requires a defensible comparison and assumptions about differences between groups. The record does not report an adjusted treatment-effect analysis.

The study summary presents routine-care assessment as a way to examine patients and centers beyond those typically involved in randomized trials. Such settings can be informative about practice outside a tightly controlled trial environment. At the same time, routine-care data may reflect variation in participant selection, treatment decisions, follow-up, and recording. Those features affect how broadly results can be applied and whether any observed association can be attributed to treatment.

What do over-dispersion and count outcomes mean?

In general, over-dispersion occurs when outcome variability is greater than a statistical model’s assumptions allow. It can make standard errors too small and confidence intervals too narrow if ignored. It is relevant to some count or rate analyses, particularly when event counts vary more than expected under a simple model. The registry lists health-care resource use and safety outcomes among the areas of interest, but it does not report a model for those outcomes or an assessment of over-dispersion. It would be inappropriate to infer that any particular method was used.

Similarly, time-to-event methods account for both event timing and differing follow-up, but the registry record does not describe a time-to-event analysis. It lists a general sample-size-planning approach in which time-to-event illustrations use total event counts, while other illustrations use participants per arm. That planning description does not establish that a time-to-event analysis was performed for the study’s outcomes.

What can the planning assumptions tell readers?

The registry’s planning assumptions describe illustrations based on an observed effect, using a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. The target effect is described as a stated fraction of the observed effect. These are planning illustrations, not evidence that the observational study used a two-arm randomized design. No resulting planning sample-size values are reported in the registry record for this explanation. Such illustrations are not observed power and should not be interpreted as a measure of whether the study did or did not detect a treatment effect.

In general, power calculations depend on assumptions about an effect size, variability or event frequency, allocation, and statistical method. A calculation based on an observed effect is especially dependent on that estimate and may not represent an independently specified design target. The registry record does not report the study’s own sample-size justification, a protocol-based target, interim analyses, or a statistical analysis plan. Those details cannot be inferred from the planning assumptions alone.

10. Exact Estimates for Each Arm

No two-arm comparison is shown for this trial, but each arm's result can still be summarized with exact interval estimates computed from the posted counts. The Clopper-Pearson interval is exact and conservative; the Wilson interval is a common closer-to-nominal alternative; the Bayesian credible interval uses a uniform Beta(1, 1) prior. For small groups the three can differ noticeably.

R code and output

arm    <- c("Etanercept")
n      <- c(3723)
events <- c(1355)
for (i in seq_along(n)) {
  ci <- binom.test(events[i], n[i])$conf.int          # Clopper-Pearson exact interval
  cr <- qbeta(c(0.025, 0.975), 1 + events[i], 1 + n[i] - events[i])   # Bayesian, uniform Beta(1,1) prior
  wi <- (function(x, n) { p <- x / n; z <- qnorm(0.975); d <- 1 + z^2 / n
    c((p + z^2 / (2 * n) - z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d, (p + z^2 / (2 * n) + z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d) })(events[i], n[i])
  cat(sprintf("ARM|%s|%d|%d|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f\n", arm[i], n[i], events[i], 100 * events[i] / n[i],
              100 * ci[1], 100 * ci[2], 100 * wi[1], 100 * wi[2], 100 * cr[1], 100 * cr[2]))
}

ARM  Etanercept  3723  1355  36.4  34.8  38.0  34.9  38.0  34.9  38.0

11. Multiplicity, Missing Data and Analysis Populations

The registry identifies 23 outcome measures, including the primary functional-remission outcome and secondary measures covering quality of life, work productivity, health-care use, working disability, disease activity, and swollen-joint count. When multiple outcomes or analyses are examined, the chance of at least one apparently unusual result can increase. In general, a prespecified primary endpoint helps focus interpretation, while adjustment procedures or a clear hierarchy can address some multiplicity concerns. The registry record does not report whether multiplicity was addressed, which outcomes were formally tested, or any analysis hierarchy. It also lists zero analyses, so no inferential analysis results are available to evaluate.

Missing data matter because the primary outcome requires an FFbH assessment at week 26. Participants without a usable assessment may not contribute to an outcome estimate, and different approaches to missing observations can lead to different results. The record’s effectiveness-population description requires post-baseline documentation, but the number meeting this definition, the number with week 26 assessments, reasons for missingness, and any missing-data method are not reported in the registry record. No assumption about missing outcomes should be attributed to the study.

The registry describes an effectiveness population of adults with confirmed rheumatoid arthritis who had not previously received etanercept and had post-baseline documentation. It does not report how many were analyzed or whether additional exclusions applied. There is no reported intention-to-treat population, per-protocol population, or safety analysis population definition beyond the safety counts and at-risk denominators. These distinctions are important because an analysis population determines which participants contribute to each estimate and how findings should be interpreted.

In general, analyses of multiple endpoints, missing assessments, and selected analysis populations can affect the meaning and reliability of estimates. Since the relevant decisions and outcome values are not reported in the registry record, these aspects remain unresolved rather than evidence of a particular flaw or method.

12. 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.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: condition aggravated (1.6%), rheumatoid arthritis (1.5%), fall (0.6%), pneumonia (0.5%), osteoarthritis (0.4%).

The posted safety figures list 4871 participants at risk for serious adverse events, with 649 affected. For other adverse events, the listed number at risk is also 4871, with 1921 affected. These are the registry’s recorded counts; no additional percentage has been calculated. The record does not specify whether the affected counts represent participants with at least one event, event episodes, or another counting convention, so they should be read in the form reported rather than reinterpreted.

The registry lists the following serious-event terms and percentages: condition aggravated, 1.6%; rheumatoid arthritis, 1.5%; fall, 0.6%; pneumonia, 0.5%; osteoarthritis, 0.4%; and atrial fibrillation, 0.4%. The record does not report details of event adjudication, causality assessment, or whether these categories overlap for participants with multiple events. The listed terms therefore describe reported safety categories, not proof that etanercept caused them.

The death count is not reported in the registry record. Also not reported are the specific event-collection procedures, the follow-up time contributing to the at-risk denominators, and a detailed breakdown of event timing. As this is an observational study without a listed concurrent control group, the safety counts do not provide a randomized comparison of event frequency between treatments.

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

The study is relevant as an observational examination of etanercept use in routine German clinical practice. Its stated aims include health economics, safety, and effectiveness, and its primary endpoint focuses on daily functioning at week 26. The FFbH definition makes clear how functional remission was classified, and the posted safety information gives counts and selected serious-event categories. These details help identify the questions the registry intended to address.

However, the primary endpoint result is not reported in the registry record. No observed remission percentage, 95% confidence-interval limits, or endpoint analysis denominator is available. The record therefore cannot establish the frequency of functional remission at week 26 or the precision of an estimate. Enrollment of 4945 does not fill this gap, because the registry defines an effectiveness population and does not say how many participants had an evaluable week 26 assessment.

The design also constrains what an observed result could mean. In general, an observational cohort can describe outcomes in the people whose care is recorded, but without random allocation and a suitable concurrent comparator it does not by itself identify a causal treatment effect. The registry record does not describe a like-for-like control group or an adjusted comparison. It therefore does not support attributing a change in functioning, safety outcome, or health-care use to treatment on its own.

The record’s study aims and endpoint definitions should be distinguished from findings. The presence of a predefined endpoint does not reveal its result, and a list of adverse-event counts does not establish causation or comparative safety. Likewise, a planning illustration is not an observed analysis or evidence of adequate power. The most defensible reading is that the registry records a completed observational study with specified objectives and measures, while key outcome estimates and analysis details are not reported in the registry record.

14. Why This Trial Matters Statistically

Statistically, this study illustrates an important distinction between measuring outcomes in routine care and estimating a causal treatment effect. Observational research can describe what was recorded among participants treated in ordinary practice. Such evidence may address settings and patients that are not represented in the same way in randomized trials, a motivation expressed in the study summary. But broader practice relevance does not remove the possibility that treatment selection and outcome patterns are related to participant characteristics or clinical decisions.

The primary measure also highlights how outcome definition shapes interpretation. The FFbH captures reported capacity in daily activities, and its remission classification applies a threshold of at least 83%. A binary endpoint offers a direct proportion, while retaining the underlying score can preserve more gradation. The registry specifies the measure and cutoff but does not report the actual result, underscoring that a clear definition is not a substitute for an estimate and its uncertainty.

The record also demonstrates why enrollment, analysis populations, and outcome denominators must be kept distinct. Although enrollment is 4945, the effectiveness-population criteria require prior-treatment status and post-baseline documentation, and the endpoint is assessed at week 26. Without the number analyzed, the endpoint percentage cannot be reconstructed or its precision judged. This is a basic interpretive issue in studies with eligibility criteria and follow-up assessments.

Finally, the registry states planning assumptions that describe hypothetical two-arm illustrations, while the study is observational and does not list a concurrent control arm. Keeping planning exercises separate from the actual design prevents a hypothetical sample-size calculation from being mistaken for observed evidence or observed power. The record’s limited results also show why conclusions should track what is actually reported: study aims, endpoint definitions, and safety counts are informative, but they do not supply an unposted effectiveness estimate.

15. 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 primary limitation for interpreting effectiveness is that the registry record does not report the week 26 functional-remission percentage, its confidence interval, or the number analyzed. The enrollment figure of 4945 is not a substitute for the endpoint-specific denominator, especially because the stated effectiveness population has eligibility criteria and requires post-baseline documentation. The number of participants with an evaluable FFbH assessment is not reported in the registry record.

The study is observational, and the record does not state an allocation method or identify a concurrent control group. Therefore, any descriptive outcomes among etanercept users would not alone distinguish treatment-related effects from differences in participant characteristics, clinical decisions, or other influences. The study summary mentions historical comparison as an aim, but the comparison results and methods are not reported in the registry record.

Important analytic details are also not reported: the statistical analysis plan, sample-size justification for the study itself, interim analyses, handling of missing outcomes, multiplicity procedures, and adjustment methods. The registry lists 23 outcome measures but does not give their results. These omissions limit assessment of the analysis choices and the consistency of interpretation across outcomes; they do not establish that a particular method was or was not used.

The safety counts lack detail on event definitions and attribution, and the death count is not reported in the registry record. The at-risk denominators and affected counts are posted, but the record does not describe how event episodes, repeated events, or overlapping categories were handled. Finally, the one-year duration appears in the official title, but participant-level follow-up duration is not reported. These limitations constrain interpretation of both effectiveness and safety without changing the fact that the record documents an observational study and its stated objectives.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: Observational Trial With Enbrel — NCT00488475.
• Registry record last updated 2014-08-01; status last verified 2014-07.
• Results first posted 2014-05-15.
• 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.

19. Record Summary

NCT00488475 is a completed observational study of etanercept use in routine German rheumatoid arthritis care. The registry lists enrollment of 4945 and identifies a week 26 primary endpoint: the percentage achieving FFbH functional remission, defined as functional capacity at least 83%. The record names a 95% confidence interval but does not report the primary result, interval, or analysis denominator.

The study’s stated aims cover health economics, safety, and effectiveness. Secondary outcomes include quality of life, work productivity, health-care resource use, working disability, disease activity, and swollen-joint count. The record lists safety counts of 649 affected for serious adverse events and 1921 affected for other adverse events, each among 4871 at risk. A concurrent control group, allocation method, and detailed analysis procedures are not reported in the registry record. Accordingly, the available information supports description of the study design, endpoint definition, and posted safety figures, but not a conclusion about the primary effectiveness result or a causal treatment effect.