MP-376 (Aeroquin™, Levofloxacin for Inhalation) in Patients With Cystic Fibrosis: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for MP-376 (Aeroquin™, Levofloxacin for Inhalation) in Patients With Cystic Fibrosis (NCT01180634), a randomized phase 3 study. The primary outcome is Time to an Exacerbation.

2. Clinical Question

The trial addressed a treatment question in cystic fibrosis, where chronic lower respiratory tract infections can involve Pseudomonas aeruginosa. The registry rationale describes inhaled antibiotics as a way to deliver medication directly to the lungs and identifies a need for additional therapies. Aeroquin is described as an inhaled formulation of levofloxacin.

The primary outcome was time to an exacerbation, rather than a single measurement of lung function or bacterial density. That choice captures how long participants remained without a qualifying exacerbation during follow-up. The study also assessed lung function, sputum density, respiratory quality-of-life scores, use of other antimicrobials, hospitalization, and treatment-emergent adverse events. These outcomes address distinct aspects of the trial question and should not be treated as interchangeable measures of benefit.

3. Trial Design

This was a phase 3, randomized, double-blind, placebo-controlled, parallel-group study described as multicenter and multinational. The registry lists quadruple masking. A total of 330 participants were enrolled, with 220 assigned to Aeroquin 240 mg and 110 assigned to placebo. The record reports the study as completed.

Participants assigned to Aeroquin inhaled 240 mg twice daily for 28 days. Participants assigned to placebo received matching inhaled placebo on the same twice-daily schedule for 28 days. The primary outcome timeframe was baseline to the end of the study, up to 59 days. The registry identifies the primary analysis population as intent-to-treat, including all randomized participants.

Random assignment is intended to make the groups comparable at the start of a trial, on average, with respect to measured and unmeasured characteristics. Masking is intended to reduce the influence of treatment knowledge on participant experience, care, outcome assessment, and analysis. The registry names quadruple masking but does not report which specific roles were masked.

The record does not report the original sample-size justification or the assumptions used to plan enrollment. It also does not report an interim-analysis plan, the detailed statistical analysis plan, or how missing observations were handled. Those omissions limit assessment of whether the final analysis followed a prespecified plan. The record does identify the method used for the primary comparison as a log-rank test and reports a hazard ratio.

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: Intent-to-treat (IIT) population included all randomized participants.

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 Time to an Exacerbation, measured over Baseline to end of study (up to 59 days).

The primary endpoint was time to an exacerbation, measured in days from baseline to the end of the study, up to 59 days. The registry describes exacerbation onset as the earliest date on which a participant met at least 4 of the 12 modified Fuchs symptoms or signs concurrently, discontinued early, died, or received an antipseudomonal agent for an event that did not meet the modified Fuchs criteria but was judged to be an exacerbation by the blinded exacerbation process.

The listed symptoms and signs include changes in sputum, cough, dyspnea, hemoptysis, general well-being, temperature, appetite or weight, sinus symptoms, chest examination, lung function, and chest imaging. Thus, the endpoint reflects a clinical event defined using several features rather than a change in one laboratory measure. The registry states that medians and 95% confidence intervals were estimated using Kaplan-Meier estimates.

Time-to-event outcomes account for both whether an event occurred and when it occurred during the observation period. They are useful when the timing of an event matters and when participants may have different lengths of follow-up. The registry record does not describe further details of event censoring or the adjudication process beyond the definition above. The reported primary comparison is a hazard ratio from a log-rank analysis.

7. Results Posted in the Registry

• Aeroquin 240 mg vs Placebo: hazard ratio 1.33 (95% CI 0.96–1.84), reported p = 0.071 (as reported in the registry).

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Absolute Change in Percent Predicted Forced Expiratory Volume in One Second (FEV1)

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard errors.
• Result:
  • Aeroquin 240 mg: mean 0.08 versus 1.49 on control; difference -1.41 (95% CI -3.04 to 0.22), standardized effect d = -0.17; z-test p = 0.089.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Aeroquin 240 mg and the control. The interval gives the range of effects that remain compatible with the data.

Change From Baseline in Pseudomonas Aeruginosa Sputum Density

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard errors.
• Result:
  • Aeroquin 240 mg: mean 0.04 versus -0.59 on control; difference 0.63 (95% CI 0.20 to 1.06), standardized effect d = 0.28; z-test p = 0.004.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Aeroquin 240 mg than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change From Baseline in the Respiratory Domain of the Cystic Fibrosis Questionnaire Revised (CFQ-R)

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard errors.
• Result:
  • Aeroquin 240 mg: mean 4.66 versus 4.94 on control; difference -0.28 (95% CI -3.75 to 3.19), standardized effect d = -0.02; z-test p = 0.874.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Aeroquin 240 mg and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes address different dimensions of the study: lung function, Pseudomonas aeruginosa sputum density, respiratory quality of life, use of other antimicrobials, hospitalization, and treatment-emergent adverse events. The posted sponsor analyses include repeated-measures comparisons for continuous outcomes. Across the reported continuous results, the lung-function and sputum-density confidence intervals exclude the null value, while the respiratory questionnaire interval includes it. This is a mixed pattern rather than a uniform signal across every measure.

These outcomes complement the primary time-to-exacerbation result, but they do not answer the same question. A change in lung function or sputum density is not equivalent to delaying an exacerbation, and a questionnaire score reflects another outcome domain. The primary hazard-ratio interval includes the value representing equal hazards, so the secondary findings should be understood as additional, distinct results rather than as confirmation of a clear primary difference.

The registry record does not report a multiplicity adjustment for the secondary analyses. When many outcomes are tested, the chance of at least one apparently notable result can increase, even if there is no true difference across outcomes. General explanation: multiplicity procedures can control that risk, but they may also change the thresholds or intervals used for interpretation. Without a reported adjustment strategy or prespecified hierarchy, individual secondary results carry less weight than a single primary endpoint and should be considered exploratory in the broader pattern.

The registry lists additional secondary outcomes for time to other antimicrobial treatment, time to first hospitalization, and treatment-emergent adverse events, but detailed results for all listed outcomes are not included in the record. Those results are not reported in the registry record. The available secondary findings cannot establish a comprehensive pattern across all planned outcomes.

Secondary outcomes registered for this trial, for reference (only those above were recalculated):

• Absolute Change in Percent Predicted Forced Expiratory Volume in One Second (FEV1)
• Change From Baseline in Pseudomonas Aeruginosa Sputum Density
• Change From Baseline in the Respiratory Domain of the Cystic Fibrosis Questionnaire Revised (CFQ-R)
• Relative Change From Baseline in Percent Predicted FEV1
• Time to Administration of Other Systemic and/or Inhaled Antipseudomonal Antimicrobials
• Time to First Hospitalization
• Number of Participants With Treatment Emergent Adverse Events

9. Statistical Interpretation

10. Statistical Methods Explained

What does the primary method compare? The registry reports a log-rank test and hazard ratio for time to an exacerbation. A log-rank test compares the event-time patterns between groups over follow-up, rather than comparing only the proportion with an event at a single endpoint. A hazard ratio summarizes the relative event hazard between groups over time. General statistical interpretation assumes that the groups and event definition are correctly identified; the registry record does not provide additional model diagnostics or details of the hazard-ratio estimation.

The primary estimate is 1.33, with a 95% confidence interval from 0.96 to 1.84. A hazard ratio of 1 corresponds to equal hazards under the comparison. Because the interval includes 1, the range of values compatible with the data includes no relative difference as well as differences in either direction. The estimate is not an absolute risk difference and should not be read as a percentage change in the number of participants with an exacerbation.

How are medians and confidence intervals used? The registry reports Kaplan-Meier estimates for median time and 95% confidence intervals. Kaplan-Meier estimation accounts for the timing of events and can incorporate participants whose event status is not observed through the full follow-up, using censoring information. General explanation: censoring means the event time is not observed during the available follow-up; the participant contributes information up to the point at which follow-up ends. The record does not provide the censoring rules or details of how those rules were applied. The posted arm-level results give lower confidence bounds but no upper bounds, so the complete intervals cannot be described from the registry values.

What do confidence intervals convey? A confidence interval represents uncertainty around an estimate under the statistical method used. A narrower interval indicates greater precision than a wider interval on the same scale, while an interval that includes the null value indicates that the data do not distinguish the estimate from that null at the corresponding confidence level. General explanation: confidence intervals do not give the probability that a particular treatment effect is true, and they do not account for biases or analysis choices not captured by the model.

How do the secondary analyses differ? The posted continuous secondary outcomes report least-squares means and standard errors, and the sponsor-reported comparisons use repeated-measures models. Such models can analyze measurements collected over time and estimate group differences while accounting for the repeated structure specified in the model. The registry record does not describe the model’s covariance structure, adjustment variables, or missing-data assumptions. Those details are not reported in the registry record.

The recalculated secondary comparisons are simple unadjusted calculations from the posted summary statistics. For continuous outcomes, the listed recalculations use an approximate pooled standard deviation based on the posted standard errors and sample sizes. They are not the same as the sponsor’s repeated-measures model and do not reproduce its adjustment or use of repeated observations. The recalculations can serve as a basic comparison of the posted group summaries, but their uncertainty and test results should not be substituted for the sponsor’s reported model results.

General explanation: over-dispersion occurs when variation is greater than a statistical model assumes. If a model underestimates variability, standard errors may be too small and intervals too narrow; if it accounts for more variability, precision may be lower. The registry record does not report an over-dispersion assessment for the outcomes in this study, so no conclusion about its presence or effect can be drawn.

What does the analysis population mean? The primary endpoint population is described as intent-to-treat and includes all randomized participants. This approach retains participants in their assigned groups for the primary comparison, regardless of treatment adherence, according to the usual general meaning of intent-to-treat. The record does not give further details about inclusion of participants with missing outcome information or how those observations entered the analysis. Secondary outcome sample sizes differ from the full randomized group counts for some outcomes; the reasons are not reported in the registry record.

What is not documented? The registry reports the primary method and several sponsor analyses, but does not report the original sample-size justification, a full statistical analysis plan, interim analyses, or the handling of missing data. It also does not report multiplicity procedures for the many outcomes. These gaps matter because analytic choices can affect estimates, uncertainty, and the interpretation of multiple statistical tests. They prevent a complete assessment of whether the posted analyses match prespecified methods.

11. Confidence Intervals and Precision

The main precision measure for the primary comparison is the reported 95% confidence interval around the hazard ratio. The estimate is 1.33, and the interval runs from 0.96 to 1.84. It includes 1, the value representing equal hazards, and spans values on both sides of that reference. This means the posted result is compatible with no relative difference as well as with a range of possible differences. The estimate should not be treated as a precise determination of the size or direction of an effect.

The arm-specific median estimates are 58 days for Aeroquin and 51.5 days for placebo. The registry values include lower confidence bounds of 52 days and 43.0 days, respectively, but the upper bounds are not reported in the registry record. These incomplete bounds do not permit a full assessment of precision for the medians from the posted values alone. The comparative hazard-ratio interval is the available reported measure for the primary between-group analysis.

Confidence intervals are useful because they show a range of estimates compatible with the data and analysis assumptions. General explanation: width reflects statistical precision, not freedom from bias, and a confidence interval does not ensure that the model assumptions are correct. The primary interval is broad enough to leave meaningful uncertainty about the relative hazard. No additional precision measure for the primary outcome is reported in the registry record.

Secondary outcomes have their own scales and uncertainty estimates. Their intervals should be interpreted against the appropriate null value for each measure and in light of the analysis used. Differences in endpoint, model, and sample size mean that secondary interval widths cannot be compared directly with the hazard-ratio interval as if they measured the same quantity.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning figures are illustrations based on observed effects, not the trial’s original design assumptions. The original design assumptions and sample-size justification are not reported in the registry record. The listed planning assumptions are a two-sided significance level of 0.05, equal allocation between two arms, a normal approximation, and an effect to detect set to the stated fraction of the observed effect.

For the time-to-event outcome, the figures are total events needed across the groups, estimated using the Schoenfeld approach. They are not participants per arm. For the continuous outcomes, the figures are participants per arm. The outcome type therefore determines how to interpret the unit in each planning row.

The 80% power column describes the number of events or participants that the planning calculation estimates would be needed to have an 80% chance of detecting the assumed effect, if the assumptions hold and the effect is present. The 90% power column describes the corresponding requirement for a 90% chance. These are planning probabilities under a specified statistical model, not probabilities that the observed finding is true.

Rows based on a smaller fraction of the observed effect require more events or participants, because smaller differences are harder to distinguish from random variation. The planning values depend on the observed estimate, which itself is uncertain, and on assumptions that may not match a real future trial. These figures are not observed power.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

d is the total number of events needed (Schoenfeld's formula) with 1:1 allocation and proportional hazards.

Worked calculation for this trial

1. Hazard ratio HR = 1.330, so ln(HR) = 0.2852.
2. d = 4 × (1.96 + 0.842)² / [ln(1.330)]² = 386.0, rounded up to 387 events in total for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
hr <- 1.33                              # observed hazard ratio
events_needed <- function(power, frac = 1) ceiling(round(4 * (z_a + qnorm(power))^2 / log(hr^frac)^2, 6))   # Schoenfeld, 1:1 allocation
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: events = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(events_needed(0.80, f), big.mark = ","), format(events_needed(0.90, f), big.mark = ",")))

# Simulation: given d total events under proportional hazards, events in the treatment arm are Binomial(d, hr / (1 + hr)).
# The score (log-rank type) statistic is (D1 - d / 2) / sqrt(d / 4).
set.seed(1180634)
d    <- events_needed(0.80)
reps <- 20000
D1 <- rbinom(reps, d, hr / (1 + hr))
z  <- (D1 - d / 2) / sqrt(d / 4)
cat(sprintf("Simulated power with %s events: %.3f (%d replicates)\n", format(d, big.mark = ","), mean(abs(z) > z_a), reps))

Output from running the code

100% of observed effect: events = 387 (80% power), 517 (90% power)
 75% of observed effect: events = 687 (80% power), 919 (90% power)
 50% of observed effect: events = 1,545 (80% power), 2,068 (90% power)
Simulated power with 387 events: 0.806 (20000 replicates)

The simulation uses the fact that, with d events in total and proportional hazards, the number of events in the treatment arm is binomial. It is an approximation that conditions on the total number of events, and it should land close to the target power.

14. Analyses Reported by the Sponsor

The registry reports a sponsor analysis for the primary endpoint using a log-rank method and a hazard ratio. The recalculation approach for this endpoint does not generate an alternative estimate; the posted primary hazard ratio and its confidence interval are the relevant reported comparative result.

For the continuous secondary outcomes, sponsor-reported analyses use repeated-measures models. The recalculated comparisons are simpler unadjusted re-calculations from posted summary statistics and do not reproduce those models. The estimates can differ because the model-based analysis and the summary-statistic calculation use different information and assumptions. In particular, a repeated-measures model can incorporate the structure of measurements over time, whereas a simple calculation from summary values cannot reconstruct all of that structure.

The registry record does not report enough model detail to reproduce the sponsor’s analyses independently. The recalculations should therefore be treated as rough, unadjusted checks on the posted summaries, not as replacements for the sponsor’s analysis or as a correction to it. The posted sponsor results remain the appropriate record of the analyses reported by the trial sponsor.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists one primary endpoint and several secondary outcomes, including lung function, sputum density, respiratory quality of life, additional antimicrobial use, hospitalization, and treatment-emergent adverse events. It reports multiple analyses, but does not report a multiplicity procedure, a testing hierarchy, or a strategy for controlling the chance of false-positive findings across outcomes. The record also does not state whether particular secondary outcomes were designated as confirmatory or exploratory.

General explanation: testing multiple outcomes creates more opportunities for a result to appear statistically notable by chance. Adjustment methods can address that issue by changing how evidence is evaluated across the family of tests. Without a reported approach, the secondary results should not be treated as if each were the only planned statistical test. Their role is supportive and descriptive, particularly when the primary comparison itself remains uncertain.

The primary population is identified as intent-to-treat and includes all randomized participants. The record does not report how missing primary outcome information was handled, whether participants were censored for particular reasons, or what assumptions were made about unavailable observations. It also does not provide a full account of the analysis population for every secondary endpoint. Some outcome sample sizes are smaller than the randomized arm totals, but the reasons for those differences are not reported in the registry record.

The original sample-size justification, any interim-analysis plan, and the detailed statistical analysis plan are also not reported in the registry record. These omissions make it difficult to determine whether the trial had been planned around the posted primary outcome and whether analysis decisions were prespecified. They do not invalidate the estimates, but they limit independent assessment of the potential for selective analysis, missing-data effects, or multiplicity-related overinterpretation.

16. 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: disease progression (10.0%), pyrexia (0.5%), bronchopneumonia (0.5%), influenza (0.5%), pyelonephritis (0.5%).

The registry reports serious adverse events in 21 of 219 participants at risk in the Aeroquin group and 11 of 110 at risk in the placebo group. It reports other adverse events in 207 of 219 and 106 of 110 participants at risk, respectively. No deaths are listed in either group. These are descriptive counts from the posted safety results and do not, by themselves, establish that an event was caused by treatment.

The serious-event terms listed include disease progression at 10.0%, and pyrexia, bronchopneumonia, influenza, pyelonephritis, and small intestinal obstruction at 0.5% each. The registry record does not provide enough detail in these figures to interpret each term’s timing, relatedness, duration, or clinical course. A participant may also contribute to more than one event term, so listed terms should not be added together to infer a count of affected participants.

Safety counts need to be read with their denominators and the study’s follow-up period in mind. The record describes a 28-day treatment period and primary follow-up of up to 59 days. These results characterize events recorded during the trial; they do not establish the frequency of events outside the observed study period.

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

The primary result describes the timing of exacerbations in a randomized comparison of inhaled Aeroquin and placebo among stable cystic fibrosis patients. The reported hazard ratio is 1.33, with a 95% confidence interval from 0.96 to 1.84. Because the interval includes 1, the primary analysis does not establish a clear difference between groups. The posted median estimates provide additional description of time to event, but the comparative hazard ratio is the reported primary analysis.

This result does not show that the treatments are equivalent. An interval that includes the null can reflect uncertainty about whether there is a difference, and the primary confidence interval still includes values on either side of no relative difference. It also does not establish that one treatment works or fails to work. Statistical results describe the evidence in this trial, not a treatment recommendation.

The findings apply to the participants, treatment schedule, endpoint definition, and follow-up described in the registry record. Aeroquin was given by inhalation at 240 mg twice daily for 28 days, and primary follow-up extended to the end of the study, up to 59 days. The posted results do not answer questions about longer treatment, longer-term outcomes, or other patient groups not described in this record.

The secondary results cover several distinct domains and show a mixed pattern. They can add context, but the registry does not report multiplicity procedures, full analysis details, or the handling of missing observations. Those limits matter when weighing secondary findings alongside the primary result. Safety counts are also descriptive and cannot establish causality from the registry figures alone.

Overall, the record supports a careful reading of the estimated primary comparison and its uncertainty, alongside the separate secondary and safety outcomes. It does not provide enough information to resolve every design and analysis question or to make claims beyond the reported trial.

18. Why This Trial Matters Statistically

This trial illustrates why clinical interpretation should distinguish an endpoint estimate from its uncertainty. The primary outcome is a time-to-event measure, and its reported hazard ratio summarizes the relative event hazard over follow-up. The confidence interval, rather than the point estimate alone, shows that the data remain compatible with a range of possible relative effects, including no difference.

It also illustrates why median times and hazard ratios should not be treated as interchangeable summaries. Medians describe a point in each group’s estimated event-time distribution, while the hazard ratio and log-rank analysis compare event-time patterns across follow-up. Both can be informative, but they answer related rather than identical statistical questions.

The secondary outcomes demonstrate another key issue: a trial can produce different patterns across endpoints that measure different constructs. Lung function, sputum density, quality of life, and exacerbation timing cannot be combined into one result without a prespecified rationale. When many outcomes are reported and the registry does not describe multiplicity control, isolated secondary findings require caution.

Finally, the difference between sponsor-reported repeated-measures analyses and simple unadjusted recalculations underscores the importance of understanding the method behind an estimate. Summary-statistic recalculations can provide a rough check, but they cannot reproduce a model that uses repeated measurements and its associated assumptions. The registry’s omissions about the original sample-size rationale, missing data, and analysis plan also show why transparent methods are essential to interpreting trial results.

19. 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 registry record provides limited detail about several features needed for a full statistical appraisal. It does not report the original sample-size justification, the statistical analysis plan, interim analyses, or the handling of missing data. It also does not describe the reasons for censoring in the primary time-to-event analysis or provide the complete upper confidence bounds for the arm-specific median times.

The record identifies the primary analysis as intent-to-treat and names a log-rank test, but does not provide further information about model diagnostics, proportional-hazards assessment, or how deviations from any model assumptions were addressed. General explanation: a hazard ratio is easiest to interpret as a constant relative comparison when hazards are proportional over time; the record does not report whether this assumption was assessed. No conclusion about that assumption can be made from the posted information.

For the continuous outcomes, the sponsor reports repeated-measures models, but the model specifications, covariance structure, adjustment variables, and missing-data assumptions are not reported in the registry record. The unadjusted recalculations use posted summary statistics and cannot substitute for those model details. The registry also does not report a multiplicity strategy for the many endpoints, limiting the strength of conclusions drawn from secondary comparisons.

Finally, follow-up was limited to the study period, up to 59 days for the primary endpoint, and treatment lasted 28 days. The posted safety and efficacy findings therefore describe a limited observation window. The registry does not provide detailed results for every listed secondary outcome, so the available results do not permit a complete assessment of all endpoints named in the study record.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: MP-376 (Aeroquin™, Levofloxacin for Inhalation) in Patients With Cystic Fibrosis — NCT01180634.
• Registry record last updated 2024-12-18; status last verified 2024-12.
• Results first posted 2024-04-30.
• 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.

23. Record Summary

NCT01180634 is a completed phase 3, randomized, quadruple-masked, parallel-group, placebo-controlled study of inhaled Aeroquin in stable cystic fibrosis patients. The trial enrolled 330 participants: 220 assigned to Aeroquin 240 mg twice daily and 110 assigned to matching placebo, with treatment lasting 28 days.

The primary endpoint was time to an exacerbation, assessed from baseline to the end of the study, up to 59 days. The reported hazard ratio for Aeroquin versus placebo was 1.33, with a 95% confidence interval from 0.96 to 1.84. The interval includes 1 and leaves uncertainty about the comparative effect.

Secondary outcomes covered lung function, sputum density, respiratory quality of life, antimicrobial use, hospitalization, and adverse events. The registry does not report the original sample-size justification, multiplicity procedures, interim analyses, or detailed missing-data methods. Safety results list serious events, other adverse events, and no deaths in either group.