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Idiopathic Pulmonary Fibrosis Phase 3 Terminated NCT03711162

ISABELA 1: Complete Statistical Analysis of GLPG1690 in Idiopathic Pulmonary Fibrosis

An independent statistical review of the randomized phase 3 ISABELA 1 trial evaluating GLPG1690 versus placebo in subjects with idiopathic pulmonary fibrosis, with emphasis on annual FVC decline, disease progression, hospitalization, longitudinal outcomes, time-to-event analysis, and safety.

Trial start: November 28, 2018  ·  Primary completion: March 30, 2021  ·  Enrollment: 525
Scope of this record

This page separates reported trial results from statistical interpretation. Numerical results and trial characteristics on this page are restricted to the ClinicalTrials.gov record for NCT03711162 and the linked PubMed records identified in that data.

Registry note: This page provides an independent statistical analysis and educational interpretation of publicly reported results. ClinicalTrials.gov provides the official trial registry record.

1. Trial at a Glance

ISABELA 1 was a randomized, parallel, quadruple-masked, phase 3 treatment study in idiopathic pulmonary fibrosis. The registry reports 525 enrolled participants and three study arms involving GLPG1690 600 mg, GLPG1690 200 mg, and placebo. The study was terminated prematurely based on recommendations of the Independent Data Monitoring Committee.

525
Enrollment
Registry total
3
Study Arms
600 mg · 200 mg · placebo
52
Primary Time Point
Weeks
121
EoS Time Frame
Weeks
FeatureISABELA 1
Trial nameISABELA 1
NCT identifierNCT03711162
PhasePhase 3
ConditionIdiopathic Pulmonary Fibrosis
Therapeutic areaPulmonology
AllocationRandomized
Design modelParallel
MaskingQuadruple
Primary purposeTreatment
Enrollment525
Arms3
InterventionsGLPG1690 and placebo
StatusTerminated
Lead sponsorLakefront Biotherapeutics NV
Sponsor typeIndustry

2. Clinical Question

The registry describes ISABELA 1 as a phase 3 study testing how effective and safe GLPG1690 is for subjects with idiopathic pulmonary fibrosis when used together with standard of care. The primary registered endpoint was the annual rate of decline in forced vital capacity (FVC) up to week 52.

Population

Subjects with idiopathic pulmonary fibrosis enrolled in the phase 3 ISABELA 1 study.

Intervention

GLPG1690, evaluated at 600 mg and 200 mg in the reported comparisons.

Comparator

Placebo.

Primary question

How does GLPG1690 compare with placebo for the annual rate of decline in FVC from baseline through week 52?

3. Trial Design

01
Randomize 525 enrolled
02
Three arms 600 mg · 200 mg · placebo
03
Follow FVC and clinical outcomes
04
Week 52 Primary endpoint
05
EoS Week 121
ACTIVE ARM · 600 MG

GLPG1690 600 mg

  • GLPG1690
  • Reported against placebo for the primary FVC analysis
  • Reported for multiple secondary efficacy endpoints
ACTIVE ARM · 200 MG

GLPG1690 200 mg

  • GLPG1690
  • Reported against placebo for the primary FVC analysis
  • Reported for multiple secondary efficacy endpoints

Comparator arm

The third arm was placebo. The ClinicalTrials.gov record compare each GLPG1690 dose with placebo rather than reporting a direct 600 mg versus 200 mg comparison.

The study was randomized and parallel, with quadruple masking. The registry reports that the study was terminated prematurely based on recommendations of the Independent Data Monitoring Committee. That fact is important when interpreting the maturity and precision of the reported estimates.

4. Trial Timing and Status

November 28, 2018

Study start

The registry lists November 28, 2018 as the study start date.

March 30, 2021

Primary completion

The registry lists March 30, 2021 as the primary completion date.

Study status

Terminated

The study was prematurely terminated based on recommendations of the Independent Data Monitoring Committee.

5. Primary Endpoint

EndpointRegistry definitionTime frame
Annual Rate of Decline in FVC up to Week 52 FVC, in mL, is the maximum amount of air exhaled from the lungs by a participant after taking their deepest possible breath, as measured by spirometry. Baseline up to week 52

The endpoint is continuous and is expressed in the posted statistical analyses as mL/year. Rather than comparing only FVC at a single visit, the reported analysis estimated treatment-specific slopes over time and used the time-by-treatment interaction in a mixed model to determine the treatment effect.

Core statistical idea
Treatment effect = estimated slope for GLPG1690 − estimated slope for placebo

The registry-reported analysis notes state that the treatment effect was determined from estimated slopes for each treatment group on the basis of the time-by-treatment interaction term from the mixed model.

6. Analysis Population

Several secondary analyses were also reported in the Full Analysis Set - Efficacy. For the composite endpoint involving mortality or non-elective lung transplantation, the registry-reported population description was FAS - EF with available data at specified time point.

Why the population matters: The registry describes the FAS-EF as containing randomized participants who received at least one dose, so it is not identical in wording to a pure all-randomized intention-to-treat population. The analysis records nevertheless identify intention-to-treat analysis as an associated concept. Interpretation should therefore follow the registry's stated analysis population rather than silently relabeling it.

7. Statistical Methodology

Mixed-effects modeling for longitudinal FVC

The primary FVC analysis was reported as a coefficient regression model. More importantly for interpretation, the analysis notes state that treatment effect was determined from estimated slopes using a time-by-treatment interaction term from a mixed model.

This structure is appropriate to the longitudinal nature of repeated FVC measurements because the question is fundamentally about how FVC changes over time. The treatment-by-time interaction asks whether the estimated rate of change differs between treatment groups.

Slope-based treatment effect
βtime × treatment = difference in estimated FVC trajectories

A positive or negative mean difference therefore has to be interpreted in the context of the endpoint's definition: annual rate of decline in FVC, measured in mL/year.

Mixed-effects models for SGRQ

The secondary SGRQ analyses used mixed models. For the week 52 analyses, the registry-reported analysis notes specify treatment, categorical time, treatment-by-time interaction, stratum, and baseline SGRQ total score as fixed effects, with participant as a random effect.

This separates two sources of variation: systematic differences associated with treatment and time, and within-participant correlation created because the same participant contributes repeated observations.

Logistic regression

Disease progression was analyzed with logistic regression for the binary outcome "Percentage of Participants With Disease Progression." The reported effect measure was an odds ratio.

Odds ratio
OR = odds of progression in GLPG1690 ÷ odds of progression in placebo

An odds ratio of 1 indicates equal odds under the fitted comparison. Values below 1 indicate lower estimated odds in the numerator group, while values above 1 indicate higher estimated odds. An odds ratio is not itself a risk ratio.

Cox proportional-hazards models

Time-to-event secondary endpoints were analyzed using Cox proportional-hazards models. The registry analysis text explicitly identifies Cox proportional hazards for respiratory-related hospitalization, all-cause hospitalization, acute IPF exacerbation, and several composite time-to-event outcomes.

The hazard ratio summarizes the estimated relative instantaneous event rate between groups under the fitted model. It does not directly report the difference in cumulative event probability at a particular time point.

Intention-to-treat as an associated analysis concept

The ClinicalTrials.gov record identifies intention-to-treat analysis as an associated concept for the primary and several secondary analyses. The actual analysis-population field, however, is the more specific source for determining who was included in each posted analysis.

8. Primary Results: Annual Rate of Decline in FVC Through Week 52

The registry posts two formal primary endpoint analyses: GLPG1690 600 mg versus placebo and GLPG1690 200 mg versus placebo. Both use a two-sided 95% confidence interval and a superiority hypothesis.

GLPG1690 600 mg vs Placebo

LS mean difference in annual FVC decline

22.7 mL/year

95% CI: -52.3 to 97.6 mL/year   ·   P = 0.5525

Estimated from the treatment-by-time interaction using the mixed-model slope approach.

Clinical Biostats interpretation

The reported LS mean difference was 22.7 mL/year for GLPG1690 600 mg versus placebo. Because the endpoint is an annual rate of FVC decline, the sign should be interpreted according to the registry's coding and model definition rather than treated as a simple cross-sectional difference in FVC at week 52.

The 95% CI of -52.3 to 97.6 mL/year spans zero. In practical statistical terms, the registry-reported interval is compatible with treatment effects on either side of zero under the model and sampling framework. The interval also shows substantial uncertainty around the point estimate.

The P-value of 0.5525 is a measure of compatibility with the null hypothesis under the specified statistical test; it is not a measure of effect size. A P-value of 0.5525 does not mean that the treatment effect is "55.25% absent," nor does it quantify clinical importance.

Because the analysis is based on longitudinal slopes, interpretation also depends on the mixed-model specification and the handling of incomplete follow-up. The ClinicalTrials.gov record does not provide additional details about missing-data imputation or model diagnostics, so no stronger assumption should be attributed to the trial.

GLPG1690 200 mg vs Placebo

LS mean difference in annual FVC decline

-26.7 mL/year

95% CI: -100.5 to 47.1 mL/year   ·   P = 0.4776

Estimated from the treatment-by-time interaction using the mixed-model slope approach.

Clinical Biostats interpretation

The reported LS mean difference was -26.7 mL/year for GLPG1690 200 mg versus placebo. The negative point estimate is not sufficient by itself to establish a treatment effect because the corresponding 95% CI of -100.5 to 47.1 mL/year crosses zero.

The confidence interval is wide relative to the point estimate, indicating considerable statistical uncertainty. It is therefore important not to interpret the point estimate in isolation.

The P-value of 0.4776 does not measure the magnitude of the observed difference. It addresses the statistical evidence against the specified null under the reported analysis. It should be read together with the point estimate and confidence interval.

The two primary comparisons were specified as superiority analyses. Because both confidence intervals include zero and both reported P-values are substantially above conventional significance thresholds, the ClinicalTrials.gov record does not provide a formal statistical basis for claiming superiority on this endpoint.

Primary comparisonEffect measureEstimate95% CIP-value
GLPG1690 600 mg vs PlaceboLS mean difference22.7 mL/year-52.3 to 97.60.5525
GLPG1690 200 mg vs PlaceboLS mean difference-26.7 mL/year-100.5 to 47.10.4776

9. Secondary Results: Disease Progression at Week 52

The registry reports disease progression through week 52 as a binary endpoint. Both dose comparisons used logistic regression and reported odds ratios with two-sided 95% confidence intervals.

GLPG1690 600 mg vs Placebo

Odds ratio for disease progression

0.99

95% CI: 0.56–1.74   ·   P = 0.9648

GLPG1690 200 mg vs Placebo

Odds ratio for disease progression

1.05

95% CI: 0.60–1.84   ·   P = 0.8530

ComparisonOR95% CIP-valueMethod
600 mg vs Placebo0.990.56–1.740.9648Logistic regression
200 mg vs Placebo1.050.60–1.840.8530Logistic regression

Both confidence intervals include 1.00, the null value for an odds ratio. The estimates therefore do not provide evidence of a clear difference in the odds of disease progression under the reported superiority analyses.

10. Secondary Results: Respiratory-Related Hospitalization

Respiratory-related hospitalization through the end of study was analyzed as a time-to-event endpoint. The registry describes the time frame as up to EoS, week 121, and reports hazard ratios from Cox proportional-hazards models.

GLPG1690 600 mg vs Placebo

Hazard ratio for respiratory-related hospitalization

1.01

95% CI: 0.50–2.05

GLPG1690 200 mg vs Placebo

Hazard ratio for respiratory-related hospitalization

0.93

95% CI: 0.47–1.88

Clinical Biostats interpretation

A hazard ratio of 1.01 for the 600 mg comparison is very close to 1, while the 200 mg estimate of 0.93 is below 1. Neither point estimate should be interpreted without its confidence interval. The 95% CIs of 0.50–2.05 and 0.47–1.88 are both broad and include 1.

The registry does not post a P-value for these Cox analyses in the ClinicalTrials.gov record. Accordingly, no P-value-based conclusion should be added. The appropriate focus is the hazard-ratio estimate and its uncertainty.

Because these are time-to-event analyses, censoring and the proportional-hazards assumption are relevant. The ClinicalTrials.gov record identifies the Cox model but do not provide diagnostics for proportional hazards.

11. Secondary Results: SGRQ Total Score at Week 52

Change from baseline in St. George's Respiratory Questionnaire (SGRQ) total score at week 52 was analyzed using a mixed model. The registry reports LS mean differences with two-sided 95% confidence intervals and P-values.

ComparisonLS mean difference95% CIP-value
GLPG1690 600 mg vs Placebo-0.5-4.4 to 3.30.7850
GLPG1690 200 mg vs Placebo0.3-3.4 to 4.10.8617

The registry-reported model specification included treatment, categorical time, treatment-by-time interaction, stratum, and baseline SGRQ total score as fixed effects, with participant as a random effect. This is a repeated-measures structure: the model recognizes that observations from the same participant are correlated rather than treating them as independent observations.

12. Secondary Results: Annual Rate of FVC Decline Until EoS

The registry also reports annual rate of decline in FVC from baseline through EoS, defined as week 121. These analyses used a mixed-effects model and again derived treatment effects from estimated slopes based on the time-by-treatment interaction.

ComparisonLS mean difference95% CI
GLPG1690 600 mg vs Placebo19.4 mL/year-46.9 to 85.7
GLPG1690 200 mg vs Placebo-29.1 mL/year-93.9 to 35.8

Both intervals include zero. These EoS slope estimates therefore show substantial uncertainty and should not be read as establishing superiority from the point estimates alone.

13. Secondary Results: Disease Progression Until EoS

Disease progression through EoS was analyzed using logistic regression.

ComparisonOdds ratio95% CI
GLPG1690 600 mg vs Placebo1.150.68–1.95
GLPG1690 200 mg vs Placebo1.250.74–2.09

Both confidence intervals include 1.00. The registry registry-reported no P-values for these EoS logistic-regression analyses, so the interpretation here is based on the odds-ratio estimates and their confidence intervals.

14. Secondary Results: SGRQ Total Score at Week 100

ComparisonLS mean difference95% CI
GLPG1690 600 mg vs Placebo3.7-11.5 to 19.0
GLPG1690 200 mg vs Placebo2.9-11.1 to 16.8

The registry-reported analysis notes state that these effects were estimated as the LS mean difference between each active treatment group and placebo from the mixed model. Both confidence intervals span zero, so the posted estimates are compatible with differences in either direction under the model.

15. Secondary Time-to-Event Results

The registry contains a substantial group of EoS time-to-event outcomes. These are particularly useful for understanding how different clinical definitions of progression or hospitalization can produce related but non-identical statistical estimands.

All-Cause Hospitalization

ComparisonHazard ratio95% CI
GLPG1690 600 mg vs Placebo1.080.65–1.78
GLPG1690 200 mg vs Placebo1.230.76–1.98

The analysis was a Cox proportional-hazards model for time to first all-cause hospitalization. Both confidence intervals include 1.

Acute Idiopathic Pulmonary Fibrosis Exacerbation

ComparisonHazard ratio95% CI
GLPG1690 600 mg vs Placebo1.290.44–3.81
GLPG1690 200 mg vs Placebo1.210.42–3.50

These intervals are notably broad, illustrating how relatively uncommon time-to-event outcomes can produce imprecise hazard-ratio estimates.

All-Cause Mortality or Hospitalization for Non-Elective Lung Transplant

ComparisonHazard ratio95% CI
GLPG1690 600 mg vs Placebo1.640.66–4.08
GLPG1690 200 mg vs Placebo0.980.36–2.61

The analysis population for this endpoint was described as FAS-EF with available data at the specified time point. The wide intervals show substantial uncertainty, particularly for the 600 mg comparison.

All-Cause Mortality, Non-Elective Lung Transplant, or Hospitalization for Qualifying for Lung Transplant

ComparisonHazard ratio95% CI
GLPG1690 600 mg vs Placebo1.640.66–4.08
GLPG1690 200 mg vs Placebo0.980.36–2.61

The registry values are identical to the preceding composite endpoint. This page reports them as separate registry outcomes rather than assuming that identical estimates represent a data-entry error.

All-Cause Mortality or Hospitalization Meeting a ≥10% Absolute Decline in %FVC or Respiratory-Related Hospitalization

ComparisonHazard ratio95% CI
GLPG1690 600 mg vs Placebo1.060.59–1.91
GLPG1690 200 mg vs Placebo0.790.43–1.46

All-Cause Mortality or Respiratory-Related Hospitalization

ComparisonHazard ratio95% CI
GLPG1690 600 mg vs Placebo1.060.59–1.91
GLPG1690 200 mg vs Placebo0.790.43–1.46

These composite endpoints illustrate an important statistical principle: combining several clinically meaningful events creates an estimand that is different from any single component. The hazard ratio describes time to the first qualifying event in the composite, not the treatment effect on each component separately.

16. Consolidated Secondary Results

Endpoint600 mg vs Placebo200 mg vs Placebo
Disease progression to week 52 OR 0.99 (95% CI 0.56–1.74); P = 0.9648 OR 1.05 (95% CI 0.60–1.84); P = 0.8530
Respiratory-related hospitalization to EoS HR 1.01 (95% CI 0.50–2.05) HR 0.93 (95% CI 0.47–1.88)
SGRQ change at week 52 LS mean difference -0.5 (95% CI -4.4 to 3.3); P = 0.7850 LS mean difference 0.3 (95% CI -3.4 to 4.1); P = 0.8617
Annual FVC decline to EoS LS mean difference 19.4 mL/year (95% CI -46.9 to 85.7) LS mean difference -29.1 mL/year (95% CI -93.9 to 35.8)
Disease progression to EoS OR 1.15 (95% CI 0.68–1.95) OR 1.25 (95% CI 0.74–2.09)
SGRQ change at week 100 LS mean difference 3.7 (95% CI -11.5 to 19.0) LS mean difference 2.9 (95% CI -11.1 to 16.8)
All-cause hospitalization to EoS HR 1.08 (95% CI 0.65–1.78) HR 1.23 (95% CI 0.76–1.98)
Acute IPF exacerbation to EoS HR 1.29 (95% CI 0.44–3.81) HR 1.21 (95% CI 0.42–3.50)
Mortality or non-elective lung transplant to EoS HR 1.64 (95% CI 0.66–4.08) HR 0.98 (95% CI 0.36–2.61)
Mortality, non-elective transplant, or qualifying-for-transplant hospitalization to EoS HR 1.64 (95% CI 0.66–4.08) HR 0.98 (95% CI 0.36–2.61)
Mortality or hospitalization meeting ≥10% absolute decline in %FVC or respiratory-related hospitalization HR 1.06 (95% CI 0.59–1.91) HR 0.79 (95% CI 0.43–1.46)
Mortality or respiratory-related hospitalization to EoS HR 1.06 (95% CI 0.59–1.91) HR 0.79 (95% CI 0.43–1.46)

17. Safety Results

The ClinicalTrials.gov record reports serious adverse events by treatment arm. The figures are presented as affected participants divided by the number at risk.

Study armSerious adverse eventsAffected / at risk
GLPG1690 600 mgSerious adverse events38 / 174
GLPG1690 200 mgSerious adverse events38 / 175
PlaceboSerious adverse events36 / 174
Serious adverse events: affected participants
GLPG1690 600 mg
38
GLPG1690 200 mg
38
Placebo
36

The ClinicalTrials.gov record does not provide a statistical comparison or confidence interval for serious adverse events. The appropriate interpretation is therefore descriptive rather than a formal hypothesis test.

Denominator matters: the serious-adverse-event denominators reported here are 174, 175, and 174, respectively. They should not be silently substituted with the overall enrollment of 525.

18. Statistical Methods Explained

Why was a mixed-effects model used for the primary FVC endpoint?

The primary endpoint is an annual rate of decline rather than a single measurement. Repeated FVC observations over time contain information about each participant's trajectory. A mixed-effects model can represent systematic treatment and time effects while accounting for repeated observations from the same participant. In this registry analysis, the treatment effect was specifically based on the time-by-treatment interaction and the resulting estimated slopes.

What does the FVC LS mean difference represent?

The LS mean difference is a model-based comparison of the estimated annual FVC decline between an active-treatment group and placebo. The 600 mg estimate was 22.7 mL/year, while the 200 mg estimate was -26.7 mL/year. These are slope differences, not differences between two raw FVC measurements at week 52.

Why are confidence intervals important for the primary endpoint?

The point estimate is only one possible summary of the data. The 95% confidence interval describes statistical uncertainty around that estimate under the model and sampling framework. For the 600 mg comparison, the interval was -52.3 to 97.6 mL/year; for 200 mg, it was -100.5 to 47.1 mL/year. Both include zero, the null value for a mean difference.

What does an odds ratio of 0.99 mean?

An odds ratio of 0.99 for disease progression in the 600 mg comparison means that the estimated odds ratio was very close to the null value of 1.00. It does not mean that the probability of progression was exactly 0.99 times the probability of progression, because odds and probabilities are different quantities.

Why was a Cox model used for hospitalization and exacerbation endpoints?

These outcomes are time-to-event endpoints: the analysis is concerned not only with whether an event occurred but also with when the first event occurred. Cox regression incorporates event times and right-censored observations and produces a hazard ratio as a relative measure of the instantaneous event rate.

What does a hazard ratio of 0.79 mean?

For the 200 mg comparison in the composite endpoint involving all-cause mortality or respiratory-related hospitalization, the reported hazard ratio was 0.79. Under the fitted Cox model, that corresponds to an estimated instantaneous event rate about 21% lower than placebo, because 1 - 0.79 = 0.21. This is a model-based relative statement; it does not mean that 21% of participants avoided the event or that cumulative event probability was reduced by exactly 21%.

Why should a hazard ratio not be interpreted as a constant risk ratio?

A hazard ratio concerns the relative instantaneous event rate at a given point in time under the model. A risk ratio compares cumulative probabilities over a specified period. They are mathematically different quantities. Cox interpretation also depends on the proportional-hazards framework, and the ClinicalTrials.gov record does not provide a diagnostic assessment of that assumption.

19. Primary Endpoint Interpretation in Detail

Effect estimate

The primary 600 mg comparison produced an LS mean difference of 22.7 mL/year, while the 200 mg comparison produced -26.7 mL/year. Because the endpoint represents annual FVC decline and the treatment effect was estimated from longitudinal slopes, these values should be interpreted as differences between fitted trajectories rather than as simple end-of-study differences.

Precision

The 600 mg 95% CI was -52.3 to 97.6 mL/year; the 200 mg 95% CI was -100.5 to 47.1 mL/year. Both intervals span zero. The widths of these intervals also show that the point estimates are not highly precise summaries of a single underlying treatment effect.

P-values

The primary P-values were 0.5525 and 0.4776. A P-value is not an effect-size measure and should not be converted into a percentage benefit or percentage probability that the treatment works. Its role is to quantify the statistical evidence against the specified null under the reported test.

Superiority framework

The registry identifies the primary hypothesis type as superiority. For a mean-difference analysis, the relevant null value is zero. The confidence intervals for both primary comparisons include zero, so the posted results do not establish statistical superiority on the registered primary endpoint.

20. Understanding the Time-to-Event Analyses

The EoS analyses use a common statistical framework but address different clinical events. The distinction is important because changing the event definition changes the estimand.

Endpoint familyStatistical estimandModel
Respiratory-related hospitalizationTime to respiratory-related hospitalizationCox proportional-hazards model
All-cause hospitalizationTime to first all-cause hospitalizationCox proportional-hazards model
Acute IPF exacerbationTime to first acute IPF exacerbationCox proportional-hazards model
Mortality / transplant compositesTime to first qualifying componentCox proportional-hazards model
Mortality / hospitalization compositesTime to first qualifying componentCox proportional-hazards model

A composite endpoint can increase the number of observed events, but it also combines events that may differ in clinical meaning. The reported hazard ratio therefore describes the composite endpoint as defined, not a generalized effect on every component.

21. Confidence Intervals and Null Values

Two null values recur throughout the ISABELA 1 statistical results:

Zero for mean differences

For LS mean differences in FVC decline and SGRQ change, zero represents no difference between treatment and placebo under the specified model.

One for ratios

For odds ratios and hazard ratios, one represents equal estimated odds or hazards between the compared groups.

This distinction is fundamental when reading the confidence intervals. A mean-difference interval that crosses zero and a ratio interval that crosses one are both compatible with their respective null values.

22. Multiplicity and Multiple Comparisons

The ClinicalTrials.gov record contains two primary treatment comparisons for the same primary endpoint and numerous secondary analyses across different outcome definitions and time frames. The ClinicalTrials.gov record identifies the hypotheses as superiority but do not provide an alpha-allocation or multiplicity-adjustment procedure.

Interpretation caution: the presence of multiple analyses means individual P-values should not automatically be treated as if each were the sole confirmatory test in the trial. Because the ClinicalTrials.gov record does not specify a multiplicity-control strategy, this page does not infer one.

This distinction is especially important when a trial contains multiple doses, multiple endpoints, repeated time points, and several related composite outcomes. Reporting all posted estimates is informative; it does not by itself establish that every individual comparison was confirmatory.

23. Interim Analysis and Early Termination

The registry caveat states that the study was prematurely terminated based on recommendations of the Independent Data Monitoring Committee.

This design feature affects how the final statistical record should be interpreted. An early-terminated trial may contain less accumulated information than originally anticipated. If the reason for stopping is not accompanied by the full stopping rule, information fraction, decision boundary, and statistical analysis plan, the registry result alone does not allow those design details to be reconstructed.

What is documented

The study was prematurely terminated following recommendations of the Independent Data Monitoring Committee.

What is not reported here

The ClinicalTrials.gov record does not specify an interim-analysis boundary, alpha-spending function, stopping threshold, or detailed missing-data procedure.

24. Missing Data and Model-Based Interpretation

The longitudinal FVC and SGRQ analyses rely on model-based estimates rather than simply calculating a complete-case arithmetic difference at one time point. That is a key statistical feature because longitudinal trials frequently have observations at some visits but not others.

However, the ClinicalTrials.gov record does not state a specific missing-data imputation method for the primary FVC analysis. This page therefore does not attribute a particular multiple-imputation, last-observation-carried-forward, or other missing-data procedure to ISABELA 1.

For the time-to-event analyses, participants who have not experienced the specified event by the end of their observed follow-up can contribute censored information. The ClinicalTrials.gov record identifies Cox modeling but does not provide detailed censoring rules beyond the endpoint definitions and analysis descriptions included in the data.

25. Dose Comparisons: Why the Two Estimates Should Be Read Separately

The primary results provide separate comparisons of 600 mg versus placebo and 200 mg versus placebo. They do not provide a formal 600 mg versus 200 mg treatment comparison in the statistical analyses posted on ClinicalTrials.gov.

Feature600 mg vs Placebo200 mg vs Placebo
Primary LS mean difference22.7 mL/year-26.7 mL/year
95% CI-52.3 to 97.6-100.5 to 47.1
P-value0.55250.4776

It would be statistically incorrect to infer a dose-response relationship simply by comparing the two point estimates. A formal comparison between doses would require its own estimand and analysis.

26. Limitations

27. Why This Trial Matters Statistically

ISABELA 1 is a useful statistical teaching case because it combines several common clinical-trial estimands in one randomized phase 3 study. The primary endpoint is longitudinal and slope-based, while the secondary outcomes include binary, repeated-measures, and time-to-event endpoints.

ConceptHow it appears in ISABELA 1
RandomizationRandomized parallel-group phase 3 design
BlindingQuadruple masking
Longitudinal analysisAnnual rate of decline in FVC estimated from treatment-specific slopes
Mixed-effects modelPrimary FVC analysis and SGRQ analyses
Time-by-treatment interactionBasis for the estimated slope treatment effect in FVC analyses
Logistic regressionDisease progression endpoints
Odds ratioEffect measure for binary disease-progression outcomes
Cox proportional-hazards modelHospitalization, exacerbation, mortality, transplant, and composite time-to-event outcomes
Hazard ratioRelative measure for time-to-event comparisons
Confidence intervalsUncertainty around mean differences, odds ratios, and hazard ratios
Superiority testingPrimary and secondary hypothesis type reported as superiority
Early terminationPremature termination following Independent Data Monitoring Committee recommendations

28. What the Primary Results Do and Do Not Establish

What the estimates show

The reported primary LS mean differences were 22.7 mL/year for 600 mg versus placebo and -26.7 mL/year for 200 mg versus placebo, with 95% confidence intervals of -52.3 to 97.6 and -100.5 to 47.1, respectively.

What the confidence intervals show

Both intervals include zero, indicating that the ClinicalTrials.gov record is compatible with no mean difference as well as effects in either direction under the reported model.

What the P-values show

The reported primary P-values were 0.5525 and 0.4776. These quantify statistical evidence against the relevant null hypothesis; they do not measure clinical magnitude, probability of treatment benefit, or the probability that the null hypothesis is true.

What the results do not establish

The registry-reported primary analyses do not establish superiority of either GLPG1690 dose over placebo for the registered annual rate of decline in FVC through week 52.

29. Secondary Endpoint Interpretation

The secondary analyses show the same need to keep effect size, precision, and endpoint definition separate.

Binary endpoints

Disease progression was analyzed with odds ratios. The null value is 1, and both week 52 confidence intervals include 1.

Longitudinal endpoints

SGRQ and longer-term FVC analyses use mixed-effects models, allowing treatment effects to be estimated in the presence of repeated observations.

Time-to-event endpoints

Hospitalization, exacerbation, mortality, transplant, and composite outcomes were analyzed with Cox proportional-hazards models.

Safety

Serious adverse events are reported descriptively by arm. The ClinicalTrials.gov record does not contain a formal safety hypothesis test.

30. Related Tutorials

Learn more about the methods used in this trial:

31. Related Calculators

Explore statistical tools corresponding to the main analysis concepts in this trial:

32. Sources

Continue with the statistical methods

Use the related tutorials and calculators to explore the longitudinal, categorical, and time-to-event methods represented in ISABELA 1.

33. Record Summary

ISABELA 1 provides a useful example of a phase 3 randomized trial in which the primary estimand is based on the longitudinal rate of FVC decline rather than a single cross-sectional measurement. The primary treatment effects were estimated from treatment-specific slopes using the time-by-treatment interaction in a mixed model, with LS mean differences of 22.7 mL/year for GLPG1690 600 mg versus placebo and -26.7 mL/year for GLPG1690 200 mg versus placebo. Their two-sided 95% confidence intervals both crossed zero, and the corresponding P-values were 0.5525 and 0.4776.

The secondary analyses broaden the statistical picture: disease progression was evaluated using logistic regression and odds ratios; SGRQ outcomes used mixed-effects models; and hospitalization, acute IPF exacerbation, mortality, transplant, and composite outcomes used Cox proportional-hazards models and hazard ratios. The ClinicalTrials.gov record reports serious adverse events in 38/174 participants in the 600 mg arm, 38/175 in the 200 mg arm, and 36/174 in the placebo arm.

The most important interpretive feature of the trial is that it was prematurely terminated based on recommendations of the Independent Data Monitoring Committee. That fact, together with the breadth of the confidence intervals for several secondary time-to-event endpoints and the absence of registry-reported details on multiplicity, interim boundaries, and missing-data procedures, means that the registry results should be read as a collection of prespecified and posted statistical estimates rather than as a single summary number.

Clinical Biostats methodology: A trial-results page should distinguish the estimand, effect measure, uncertainty interval, P-value, analysis population, and model assumptions. ISABELA 1 illustrates why the statistical method must be interpreted together with the clinical endpoint rather than treating every reported number as interchangeable evidence of treatment effect.