Observational Non-interventional Study (Anwendungsbeobachtung) With Aptivus® (Tipranavir) in HIV-infected Patients.: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Observational Non-interventional Study (Anwendungsbeobachtung) With Aptivus® (Tipranavir) in HIV-infected Patients. (NCT00531206), a registered phase not stated study. The primary outcome is Adverse Events.

2. Clinical Question

3. Trial Design

This was an observational, non-interventional study of antiretroviral combination treatment in clinical practice. The registry gives the study title as an observational study with Aptivus® (tipranavir) in HIV-infected patients and describes the combination of Aptivus with low-dose Norvir® (ritonavir). Its stated aim was to assess treatment experience in daily routine, including whether viral load would be durably suppressed. Because treatment was observed rather than assigned through a randomized comparison, the record describes patients receiving care rather than a controlled experiment with treatment allocation.

The registry lists enrollment of 65, study start in 2006-08, primary completion in 2009-01, and status as completed. The arm description names all participants and does not give a further description. The adverse-event summary identifies 65 patients at risk for serious events and 65 at risk for other events in the combination-treatment group. These figures describe the posted safety summaries; they do not establish that every enrolled patient contributed complete follow-up for every outcome.

The primary outcome was adverse events over 52 weeks, with the population specified as the Full Analysis Set, all patients entered and treated. Secondary outcomes include change in viral load, CD4+ cell count, subjective well-being, serious adverse events, deaths, discontinuations due to an adverse event, investigator-assessed events related to tipranavir/ritonavir, and the number of antiretroviral medicines taken in combination. The registry lists 21 outcome measures, but the available analysis count is 0. Details of visit schedules, follow-up completeness, outcome ascertainment procedures beyond case report forms, and the statistical analysis plan 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

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Full Analysis Set (FAS), all patients entered and treated

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 Adverse Events, measured over 52 weeks.

The primary endpoint is the number of patients with adverse events during a 52-week timeframe. The registry says safety and tolerability were based on adverse events and serious adverse events reported in case report forms. This kind of endpoint records whether an event was reported for a patient, rather than measuring the severity of a symptom on a continuous scale or the time until an event.

In general, counting patients with at least one event can give a straightforward summary of how many participants experienced an event during observation. It is distinct from counting every event: a patient with multiple events may still be counted once in a patient-based endpoint, depending on the endpoint definition. The registry does not give a more detailed definition of whether the primary count includes any adverse event, how repeated events were handled, or how events were attributed to treatment. Those details are not reported in the registry record.

Safety endpoints are used to describe adverse experiences observed while people receive treatment. In an observational study, the endpoint describes events in the treated group under the recorded practice conditions; it does not by itself establish that the treatment caused an event or that the event rate differs from what would occur under another regimen. The full primary adverse-event count is not reported in the registry record.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

In general, an observational study records outcomes among people receiving care without randomly assigning treatments. This design can describe what happened in the enrolled group under the observed practice conditions. It does not ensure that groups receiving different treatments are comparable, and it may not include a separate comparison group at all. In this study, the registry describes one treatment group and states that the study was non-interventional. A randomized treatment contrast is therefore not available in the record.

What does a patient count represent?

The primary endpoint is expressed as the number of patients with adverse events. A patient-based count differs from an event count: when an endpoint counts patients, repeated events in one person need not increase the patient count. The registry's broad endpoint description does not specify how repeated events, events that began before observation, or events with uncertain timing were handled. Those definitions are not reported in the registry record. The posted serious and other adverse-event summaries should be read according to their stated categories rather than assumed to be a complete breakdown of every event.

In general, a count is descriptive. A proportion can also describe the share of an analysis group with an event, but it requires a clearly defined numerator and denominator, and the follow-up and analysis population must be understood. No new proportion or rate is calculated. The at-risk counts in the registry are 65 for serious events and 65 for other events; the corresponding recorded counts are 3 and 4. The record does not explain whether the at-risk population changes over follow-up or how incomplete observation is handled.

Why does the lack of a comparator matter?

A treatment comparison requires interpretable groups and a defined contrast. Randomization is one method for balancing known and unknown prognostic factors on average, while observational comparisons may require design and analytic methods to address differences between groups. This record describes no alternative-treatment group and identifies no like-for-like control comparison. Accordingly, there is no between-group effect estimate to interpret. A single-group event count cannot distinguish events associated with treatment from events related to the underlying condition, concurrent medicines, or other aspects of care.

What do uncertainty estimates add?

In general, a confidence interval describes the range of values reasonably compatible with the data under a specified statistical model and its assumptions. A narrow interval indicates greater statistical precision than a wide interval, but neither precision nor statistical significance resolves bias from confounding or incomplete outcome recording. The registry does not report a confidence interval or inferential test for the adverse-event summaries. No uncertainty interval or test should be inferred from the counts alone.

For a binary endpoint, statistical methods may model whether each patient did or did not experience the event. Such methods rely on a defined outcome, an eligible analysis population, and adequate information about follow-up. If event probabilities differ across patients or observation time varies, a simple count may not capture those differences. The registry does not report a model, adjustment variables, or a detailed plan for analyzing the primary endpoint. A particular statistical model cannot therefore be attributed to this study from the registry record.

How should planning illustrations be understood?

In general, a sample-size calculation asks how many participants a future study might need under chosen assumptions about the event rate, effect to detect, significance level, power, allocation, and statistical method. Such a calculation is a planning exercise; it is not evidence that a completed study had a particular probability of detecting an effect. The stated illustration assumptions use a two-sided significance level of 0.05, equal allocation between two arms, a normal approximation, and an effect defined as a stated fraction of the observed effect. The stated guidance distinguishes participants per arm for non-time-to-event outcomes from a total event count for time-to-event outcomes, using the Schoenfeld method for the latter.

Those assumptions describe hypothetical planning and do not describe the observed study design. The registry describes one observational treatment group rather than equal allocation to two arms. Moreover, the record does not report a primary comparative effect estimate from which a defensible study-specific planning interpretation could be made. A planning illustration should not be called observed power, and it cannot compensate for the absence of a comparator or missing outcome analyses.

Finally, analysis populations matter. The primary outcome specifies the Full Analysis Set as all patients entered and treated. This definition gives a stated population, but the record does not report how many were included in each outcome analysis, how exclusions were handled, whether follow-up was complete, or how missing observations were treated. Without those details, the reported counts cannot be independently interpreted as a complete analysis of every enrolled participant.

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("Aptivus® in Combination With Low-dose Norvir®")
n      <- c(65)
events <- c(23)
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  Aptivus® in Combination With Low-dose Norvir®  65  23  35.4  23.9  48.2  24.9  47.5  24.9  47.6

11. Multiplicity, Missing Data and Analysis Populations

The registry lists 21 outcome measures, including the adverse-event primary endpoint and secondary measures covering viral load, CD4+ cell count, subjective well-being, serious adverse events, deaths, discontinuations, investigator-assessed treatment-related events, and concomitant antiretroviral medicines. Examining many outcomes creates a multiplicity issue: in general, the more statistical tests conducted, the more likely it becomes that at least one result appears notable by chance when no true effect is present. Planned outcome hierarchies or adjustments can help address this, but the registry does not report a multiplicity strategy. The number of analyses listed is 0, so inferential results across outcomes are not available in the registry record.

The record names the Full Analysis Set as all patients entered and treated for the primary endpoint. It does not report detailed inclusion or exclusion rules for secondary outcomes, analysis-specific denominators, or whether every participant had each assessment. The registry also does not report how missing outcome data were handled, whether follow-up ended early for some patients, or whether sensitivity analyses were used. These details matter because observed counts can depend on who contributed data and how incomplete observation was treated.

In general, missingness is not automatically harmless: if participants with missing observations differ in their outcomes or event risk from those observed, a complete-case summary may not represent the whole analysis population. This is a general methodological concern, not evidence that a particular missing-data pattern occurred in this study. The registry does not report enough information to assess that possibility. It also does not report interim analyses, stopping rules, or a prespecified statistical analysis plan; none should be assumed.

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 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: death (1.5%), transaminases increased (1.5%), pulmonary embolism (1.5%).

The serious adverse-event summary reports 3 patients with an event among 65 at risk in the combination-treatment group. The separate summary for other adverse events reports 4 patients with an event among 65 at risk. These are patient counts, not a count of every event, and the registry does not explain whether the categories overlap. They should not be added or treated as mutually exclusive categories.

The leading serious-event terms are Death, Transaminases increased, and Pulmonary embolism, each reported at 1.5%. These term frequencies do not provide a full account of event timing, duration, severity beyond the serious-event classification, or investigator attribution. The record separately lists deaths as a secondary outcome, but a dedicated deaths count is not reported in the registry record.

In general, safety summaries describe what was recorded during observation; they do not by themselves establish causation. The available registry information does not include a control group, an adjusted comparison, or detailed case-level context. It also does not give the full primary adverse-event count. The counts and listed terms therefore support a narrow description of recorded events, not a comparative estimate of risk.

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

The registry record documents an observational study of tipranavir with low-dose ritonavir in routine clinical practice and identifies adverse events over 52 weeks as the primary endpoint. Its posted safety information includes patient counts for serious and other adverse events, along with several serious-event terms and their reported frequencies. These entries provide a descriptive account of selected safety information recorded for the treated group.

They do not establish that the regimen caused any listed event. In an observational setting, events can have multiple explanations, and the record does not provide a comparison group that could help distinguish treatment-associated risk from background illness or other care. Nor does the record provide a comparative effect estimate, confidence interval, or statistical test for the safety counts. The absence of those statistics does not mean there was no risk or no difference; it means the registry entry does not report an analysis that would answer such questions.

The study summary refers to viral-load suppression as an intended assessment, but viral-load outcomes are secondary in the registry listing and their numerical results are not reported in the registry record. The record also lists other secondary outcomes, while outcome-specific estimates are not available. Consequently, the posted safety information cannot answer the broader questions of viral-load response, comparative effectiveness, or overall treatment benefit.

In general, conclusions from an observational safety study depend on clear outcome definitions, complete follow-up, and an appropriate account of who contributed data. The record states the primary population and timeframe but leaves important analytic details unspecified. Its findings should therefore be understood as registry-reported observations in one treatment group, with the stated limitations, rather than as a controlled causal estimate or a comprehensive evaluation of all outcomes.

14. Why This Trial Matters Statistically

This study is statistically informative as an example of the difference between describing outcomes and estimating a treatment effect. The registry identifies a treatment group and reports selected adverse-event counts, but it does not describe a randomized comparator. The counts can tell readers what was recorded among patients receiving the regimen; they cannot show how those outcomes would differ under another treatment.

That distinction is important in clinical research. A treatment effect is inherently comparative: it concerns outcomes under one treatment relative to outcomes under a defined alternative. A single-group description does not supply that contrast. Even a precisely recorded count cannot by itself resolve confounding, background event risk, or differences in patient characteristics that might matter in a non-randomized comparison.

The entry also illustrates why endpoint definitions and analysis details matter. The primary outcome is described as patients with adverse events, but the full primary count and detailed counting rules are not reported in the registry record. Serious and other event counts are available, yet their relation to the broader endpoint is not fully specified. A reader therefore needs to distinguish what is directly reported from what might be inferred, and to avoid treating a limited safety summary as a complete outcome analysis.

Finally, the registry lists multiple outcomes but provides no analysis count. Without reported estimates, uncertainty measures, or a multiplicity approach, the outcome list does not establish which findings were statistically assessed or how they should be interpreted. The case underscores the value of transparent reporting of analysis populations, missing data, outcome definitions, and the planned statistical approach alongside descriptive results.

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.

Several trial-specific limitations constrain interpretation. The study is observational and non-interventional, and the registry does not describe a control group. It explicitly notes that this is not a randomized comparison and that allocation is not stated. The recorded outcomes therefore cannot support a direct comparison with another regimen or a causal estimate of treatment effect.

The primary endpoint is adverse events over 52 weeks, but the complete patient count for that endpoint is not reported in the registry record. The posted safety summary instead gives separate serious and other adverse-event counts. The record does not define how those categories relate to the primary endpoint, whether they overlap, or how repeated events were counted. It also does not report the dedicated deaths result, despite listing Death among the leading serious-event terms.

Although the registry specifies the Full Analysis Set as all patients entered and treated, it does not give outcome-specific analysis populations, follow-up completeness, or missing-data methods. The entry lists 21 outcome measures but reports 0 analyses. No confidence intervals, statistical tests, adjustment methods, interim analyses, or multiplicity strategy are reported in the registry record. The detailed statistical analysis plan is not reported in the registry record.

Other relevant study details, including eligibility criteria, dosage and treatment-selection procedures, event attribution rules, and clinical context for serious events, are not reported in the registry record. The listed term frequencies do not substitute for case-level information. These limitations make the available findings useful as a restricted descriptive record, but insufficient for a broad comparative or causal interpretation.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: Observational Non-interventional Study (Anwendungsbeobachtung) With Aptivus® (Tipranavir) in HIV-infected Patients. — NCT00531206.
• Registry record last updated 2014-04-07; status last verified 2014-02.
• Results first posted 2010-05-12.
• 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

The registry entry describes a completed observational, non-interventional study of tipranavir with low-dose ritonavir in HIV type 1-infected patients. Enrollment was 65; the recorded study start was 2006-08 and primary completion was 2009-01. The stated primary endpoint was the number of patients with adverse events over 52 weeks, with the Full Analysis Set defined as all patients entered and treated.

The safety summary reports 3 patients with serious adverse events and 4 with other adverse events, each category listing 65 at risk. Death, Transaminases increased, and Pulmonary embolism are each listed at 1.5% among the leading serious-event terms. The registry lists 21 outcome measures and 0 analyses. A comparator, full primary adverse-event count, detailed missing-data handling, and outcome-specific analyses are not reported in the registry record. The record supports a descriptive account, not a randomized or causal treatment comparison.