IPF Italian Observational Study (FIBRONET) in Idiopathic Pulmonary Fibrosis: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for IPF Italian Observational Study (FIBRONET) in Idiopathic Pulmonary Fibrosis (NCT02803580), a registered phase not stated study. The primary outcome is Percentage of Participants With IPF Symptoms.

2. Clinical Question

FIBRONET was intended to describe the characteristics, management and clinical course of participants with IPF as treated in Italian pulmonary centres. The primary outcome focused on symptoms, while the study’s broader purpose also included lung function and exercise tolerance during 12 months of observation. The record identifies the symptom measure as a percentage of participants, rather than a score measuring symptom intensity or a comparison of treatment effects.

The symptom definition included cough, fatigue, dizziness and chest pain, as well as other symptoms reported at specific visits. The listed examples in the “other” category were dyspnea, hemoptysis, post-nasal drip, sputum, weight loss, worsening of fatigue and lack of appetite. These examples indicate the breadth of symptoms captured; they do not establish how common each symptom was.

Because the study was observational and no comparator is specified, its central question is descriptive: how symptoms were reported over the observation period in the enrolled population. The record does not report a causal question comparing alternative treatments, nor does it identify an assigned treatment whose effect is being tested.

3. Trial Design

FIBRONET, titled “IPF Italian Observational Study,” was a completed observational study of idiopathic pulmonary fibrosis. The sponsor was Boehringer Ingelheim. The record lists enrollment of 209 and gives a study start date of 2015-11-17 and a primary completion date of 2018-05-15. Its stated purpose was to evaluate participant characteristics, management and clinical course under real-world care in Italian pulmonary centres.

The primary symptom outcome was scheduled at baseline, 3 months, 6 months, 9 months and 12 months. The outcome description also specifies that participants with values available at baseline and follow-up visits were considered. It identifies an enrolment window for this population from 30th November 2015 to 6th April 2017. The record does not explain how many participants contributed data at each visit, whether every participant was expected to attend each visit, or how incomplete follow-up was handled.

This design differs from a randomized treatment trial. The record does not describe random assignment, an allocation procedure, or a control group, so it does not establish a like-for-like comparison between treatment arms. The fields describing allocation do not state an allocation scheme. The study instead describes people with IPF in routine Italian pulmonary-centre care.

The record lists 36 outcome measures and no analyses. It names several secondary outcomes about participant characteristics at enrollment, including age, gender, race, education level, employment status, body mass index, housing situation and marital status. The registry record does not report a statistical analysis plan, a sample-size justification for the observational study, or interim analyses. Those omissions limit what can be concluded about how the study was planned to summarize or compare data.

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.

Before assignment: Data source for this study were medical records usually collected during routine clinical practice other than study-specific questionnaires.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: All participants who enrolled in the Italian Pulmonary Centers from 30th November 2015 to 6th April 2017 were included. Participants with values available at baseline and at follow up visits were considered.

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: All patients who enrolled in the Italian Pulmonary Centers from 30th November 2015 to 6th April 2017 were included.

6. Primary Endpoint

The registry lists the primary outcome as Percentage of Participants With IPF Symptoms, measured over Baseline, 3 months, 6 months, 9 months and 12 months.

The primary endpoint is the percentage of participants with IPF symptoms. The named examples include cough, fatigue, dizziness and chest pain, while the “other” category includes dyspnea, hemoptysis, post-nasal drip, sputum, weight loss, worsening of fatigue and lack of appetite. The endpoint description refers to symptoms at the 12-month follow-up and also specifies assessments at baseline, 3 months, 6 months, 9 months and 12 months.

A percentage is a way to express how frequent a defined event or characteristic is in the group being assessed. In this case, the event is reporting an IPF symptom, not the severity of that symptom. A percentage can help describe the symptom burden in the observed population at each scheduled visit. Repeated assessments can also describe whether the reported proportion changes over the observation period, provided the data and denominators at each visit are available.

This outcome is relevant to the study’s stated aim of characterizing symptoms and clinical course in real-world care. It does not by itself measure lung function or exercise tolerance, which are also named in the study purpose. Nor does a symptom percentage determine why symptoms occurred or whether management caused a change.

The registry record does not report the primary endpoint percentages, participant counts with symptoms at each visit, or confidence intervals for those estimates. Consequently, the intended measure and assessment schedule can be described, but the magnitude and precision of the observed symptom proportions cannot be evaluated from the recorded information.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

Statistical methods determine how observations are converted into estimates and how uncertainty around those estimates is evaluated. For FIBRONET, the primary endpoint is a binary percentage: a participant either meets the definition of reporting an IPF symptom at a visit or does not. The percentage describes the proportion of the assessed group with that characteristic. It is not a measure of symptom intensity, and it does not indicate how many different symptoms an individual reported.

What does a percentage estimate?

In general, a percentage is calculated by dividing the number of participants meeting the outcome definition by the number assessed for that outcome, then expressing the result as a percentage. For a repeated outcome, each visit may have its own assessed group and estimate. If the denominator changes across visits because follow-up is incomplete, percentages can reflect both changes in symptoms and changes in who contributed data. The registry record does not report the visit-specific counts or denominators, so the actual estimates and their comparability cannot be examined.

The specified assessment times are baseline, 3 months, 6 months, 9 months and 12 months. Repeated measurements can describe a pattern over time, but observations from the same participant are related rather than independent. Methods that formally compare visits should account for that within-participant relationship. The registry record does not report whether such a model or any other repeated-measures method was used; it lists no analyses.

Why do uncertainty intervals matter?

In general, a confidence interval gives a range of values compatible with the observed data under the assumptions of the method. It communicates the precision of an estimate: a narrower interval generally indicates greater precision, while a wider interval indicates more uncertainty. An interval does not eliminate possible bias from missing data, measurement choices or the way participants entered the study. The registry record does not report confidence intervals for the symptom percentages, so their statistical precision is not stated.

A test of a difference between visits or groups, if planned, would address a question different from describing each percentage. A p-value is a measure of how compatible the data are with a specified null hypothesis under a statistical model; it does not measure the size or clinical importance of an effect. No p-values or hypothesis tests are reported in the registry record, and no statistical analysis plan is described. It would therefore be inappropriate to infer that a particular test was performed or that the outcome changed significantly.

How should over-dispersion be understood?

In general, over-dispersion occurs when the variability in outcome data is greater than a statistical model expects. For binary observations, this can occur when participants differ in their underlying likelihood of reporting the outcome, or when observations are correlated in ways not captured by the model. If a model assumes less variability than is actually present, its uncertainty estimates can be too small. Appropriate methods may account for additional variation or clustering when the design and data justify doing so. The registry record does not report an over-dispersion assessment or a method addressing it, so none should be attributed to this study.

For a repeated symptom measure, the definition and collection process are also part of the method. A broad “any symptom” endpoint can combine different experiences. Consistent questioning and coding across visits help make comparisons meaningful. The record lists symptom examples, but does not detail the measurement instrument, interviewer procedures, coding rules or validation process. The available description therefore supports explanation of the intended outcome, not an assessment of its measurement reliability.

What do sample-size illustrations mean?

General sample-size calculations estimate how many participants a hypothetical study might need under stated assumptions. The registry record describes planning illustrations based on an observed effect, a two-sided significance level of 0.05, equal allocation between two arms and a normal approximation. It says that the effect to detect is a stated fraction of the observed effect, and that non-time-to-event illustrations are expressed as participants per arm. These assumptions describe hypothetical planning calculations, not FIBRONET’s observational design or a randomized allocation.

Such illustrations are not observed power and do not establish that this study was planned with those assumptions. They cannot substitute for a prospective sample-size justification, which is not reported in the registry record. The record also does not describe how an effect was selected for these illustrations in relation to a clinical objective. Since the study is not described as having two allocated arms, an equal-allocation calculation should not be interpreted as evidence that the enrolled participants were divided into treatment groups.

The record lists 36 outcome measures and no analyses. It does not say which outcomes were prioritized in the analysis, how multiple statistical tests might have been handled, or which adjustments, if any, were planned. General statistical methods can clarify what would be needed to interpret percentages and comparisons, but they do not fill in missing study-specific methods. Without the actual estimates, analysis population details and uncertainty measures, no numerical inference about the primary endpoint can be made.

10. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when many outcomes, time points or statistical tests are examined. In general, the more separate tests conducted, the greater the chance that at least one result may appear noteworthy by chance alone. Researchers may address this through a prespecified hierarchy of outcomes, adjusted testing, or a clear distinction between confirmatory and exploratory analyses. The registry record lists 36 outcome measures, including the primary symptom outcome and secondary participant characteristics, but does not report a multiplicity strategy or statistical analysis plan. It is not reported in the registry record whether the outcomes were assigned a hierarchy or analyzed with adjustment for multiple testing.

The registry record lists no analyses. It therefore does not provide reported tests, estimates, or a description of which outcomes were analyzed. The absence of recorded analyses should not be read as evidence for or against a symptom change; it means that no inferential results are available in this record for interpretation.

Missing data are particularly relevant because the primary population description includes participants with values available at baseline and follow-up visits. The record does not report the number of participants with data at each visit, reasons for missing observations, or whether the analysis used complete cases, imputation or another method. It also does not state how participants with some, but not all, follow-up visits were treated.

In general, missingness can affect both the denominator and the representativeness of a percentage. If participants with missing follow-up differ from those observed, the available-data estimate may not describe the full enrolled population. The direction and size of any such effect cannot be established without information about missingness and its handling.

The record does not specify an analysis population beyond the availability criterion in the endpoint description. It is not reported in the registry record whether all enrolled participants, an eligible subset, or another defined group was used for each analysis. These gaps constrain interpretation of both repeated symptom estimates and comparisons across visits.

11. Safety Results

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

Deaths

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: cardiac arrest (1.4%), death (1.4%), idiopathic pulmonary fibrosis (1.0%), respiratory failure (1.0%), angina pectoris (0.5%).

The registry record lists 16 participants with serious adverse events among 209 at risk, and 38 with other adverse events among 209 at risk. It also lists 13 deaths. These are descriptive safety counts in the record; they do not establish that an event was caused by a treatment or by study participation. The record does not report event timing, exposure duration, attribution, or a comparative group for interpreting these counts.

The listed serious adverse-event terms and percentages include cardiac arrest, 1.4%; death, 1.4%; idiopathic pulmonary fibrosis, 1.0%; respiratory failure, 1.0%; angina pectoris, 0.5%; and cardiac failure, 0.5%. These are registry-listed term percentages and should be read as event-category reporting, not as evidence of causation. The record does not explain the relationship between the listed “Death” term and the separate count of deaths, or provide enough detail to reconcile those entries. Event terms can also describe categories rather than unique participants, so they should not be added together to create a total.

Safety counts in an observational study need context about follow-up, ascertainment and the population at risk. Those details are not reported in the registry record. With no randomized comparator or treatment-attribution information specified, the counts cannot show whether a particular management approach changed the risk of an adverse event.

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

The record establishes that FIBRONET was a completed observational study of IPF in Italian pulmonary centres, with enrollment of 209. It describes a primary endpoint based on the percentage of participants reporting symptoms and scheduled assessments at baseline, 3 months, 6 months, 9 months and 12 months. This defines what the study intended to measure and the context in which it was collected.

The recorded information does not include the actual primary outcome percentages, symptom counts at each visit, confidence intervals or statistical tests. Consequently, it does not show whether symptom reporting changed during follow-up, how large any change was, or how precisely an estimate was measured. A schedule of assessments alone is not a result, and enrollment does not determine the outcome values.

Even if a change in symptom percentage were reported, an observational design without a stated comparator would not by itself establish that a particular treatment or management decision caused the change. Participants were observed in real-world care, and the record does not describe a randomized treatment contrast or an adjustment strategy that could isolate treatment effects. Clinical course and management can be described, but causal attribution requires evidence and assumptions beyond the endpoint schedule.

The endpoint also answers a limited question. A percentage reporting any symptom does not describe symptom severity, duration or impact, and the varied symptoms grouped under “other” are not interchangeable experiences. The record’s broader study purpose mentions lung function and exercise tolerance, but those outcomes cannot be inferred from the symptom endpoint.

The serious adverse-event counts and listed terms provide descriptive safety information, but without timing, attribution and an appropriate comparator they do not establish treatment-related harm. Overall, the record supports an account of the study’s observational purpose, population and planned symptom measure. It does not provide reported primary outcome results sufficient to judge symptom frequency or change.

13. Why This Trial Matters Statistically

Observational studies address questions that differ from those answered by randomized comparisons. FIBRONET was designed to characterize IPF participants and their management and clinical course in Italian pulmonary centres under real-world care. That perspective can be useful for describing the population and the outcomes the study set out to monitor, while requiring care about selection, measurement and causal interpretation.

The primary endpoint illustrates why a clear estimand matters. The study asks for a percentage of participants reporting symptoms, but that quantity depends on the symptom definition, who was assessed at each visit and the denominator used. The record names several symptoms and a sequence of scheduled assessments. It also says that participants with available baseline and follow-up values were considered. Without visit-specific counts, methods and results, a reader cannot tell whether percentages are directly comparable over time or how much uncertainty surrounds them.

The record also distinguishes a descriptive clinical course from an intervention effect. There is no randomized comparison or stated allocation scheme. An observed pattern, if reported, would need to be interpreted in the context of participant characteristics, care decisions and follow-up completeness; it could not automatically be assigned to treatment. This distinction is central to sound statistical communication in clinical research.

Safety reporting reinforces the same point. Counts and adverse-event terms can describe what was recorded, but event attribution and comparative risk require additional context. The registry record lists serious events, other adverse events and deaths, but does not report the details needed to connect them to a specific treatment or exposure.

FIBRONET therefore matters statistically as an example of why registry descriptions, outcome definitions and results must be read separately. It provides a defined observational purpose and schedule, but the recorded information does not include primary symptom estimates or analysis results. Clear reporting of denominators, missing-data handling, uncertainty and analytic choices would be needed for a fuller interpretation.

14. 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 limitations specific to FIBRONET follow from the information recorded. First, the primary symptom outcome is described, but its actual percentages and participant counts are not reported in the registry record. This prevents evaluation of symptom frequency at any scheduled visit or comparison over time. Precision measures, such as confidence intervals, are also not reported.

Second, the outcome definition includes several named symptoms and a broad “other” category. The registry record does not describe the instrument or method used to elicit symptoms, how “any symptom” was coded, or whether severity was captured. The listed examples clarify the intended scope, but not how consistently the measure was applied across visits.

Third, the record describes the population as participants with available values at baseline and follow-up visits, without reporting the number contributing at each assessment or the handling of missing observations. The reasons for missing data and any imputation or sensitivity analysis are not reported in the registry record. Thus, the representativeness of visit-specific percentages cannot be assessed.

Fourth, the observational design has no stated randomized allocation or comparator. The record does not provide details of treatment patterns or analytic adjustment that would support causal interpretation. Any association between management and clinical course would remain subject to potential differences between participants and other factors not described in the record.

Finally, the registry record lists 36 outcome measures but no analyses. It does not describe a statistical analysis plan, multiplicity handling, or a sample-size justification for the observational study. The planning assumptions described for sample-size illustrations do not establish the design or power of FIBRONET. These omissions limit assessment of prespecification and statistical rigor as well as interpretation of the outcome findings.

15. Related Tutorials

16. Related Statistical Calculators

17. Sources

• ClinicalTrials.gov: IPF Italian Observational Study (FIBRONET) in Idiopathic Pulmonary Fibrosis — NCT02803580.
• Registry record last updated 2019-09-13; status last verified 2019-08.
• Results first posted 2019-09-13.
• 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.

18. Record Summary

FIBRONET (NCT02803580), titled “IPF Italian Observational Study,” was a completed observational study sponsored by Boehringer Ingelheim. It enrolled 209 participants with idiopathic pulmonary fibrosis. The recorded study start was 2015-11-17, and primary completion was 2018-05-15.

The study aimed to describe participant characteristics, management and clinical course in real-world Italian pulmonary centres during 12 months of observation. Its primary endpoint was the percentage of participants with IPF symptoms at baseline, 3 months, 6 months, 9 months and 12 months. The record lists 36 outcome measures and no analyses.

The registry record does not report primary symptom percentages, visit-specific counts, confidence intervals, or a statistical analysis plan. It does not state an allocation scheme or describe a randomized comparator. Safety entries include serious adverse events, other adverse events and deaths, but the record does not provide enough context to attribute those events to a treatment.