Study to Investigate the Efficacy and Safety of FAB122 (Daily Oral Edaravone) in Patients With Amyotrophic Lateral Sclerosis: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Study to Investigate the Efficacy and Safety of FAB122 (Daily Oral Edaravone) in Patients With Amyotrophic Lateral Sclerosis (NCT05178810), a randomized phase 3 study. The primary outcome is Change From Baseline in Amyotrophic Lateral Sclerosis Functional Rating Scale - Revised (ALSFRS-R) Score After 48 Weeks..

2. Clinical Question

The primary outcome is a change score, not the final ALSFRS-R score alone. It describes how the scale score changed from each participant’s baseline to the 48-week assessment, then the posted group means compare those changes. The scale ranges from 0 to 48 points; higher scores represent better function.

The clinical question therefore has a specific time point and measure: the average 48-week change in ALSFRS-R score. Other registry outcomes cover function, survival, and functional subdomains at additional time points. Those outcomes can add context, but they do not replace the prespecified primary question. The registry record does not report the primary analysis population or the original statistical analysis plan, so the exact population and procedures used for the sponsor’s primary analysis are not reported in the registry record.

3. Trial Design

This was a randomized, parallel-group, placebo-controlled Phase III study of FAB122 in people with ALS. The official title describes a multicenter, randomized, double-blind study, while the registry’s masking field says quadruple. These descriptions are both part of the registry record; it does not explain the difference in terminology. The study summary describes multinational participation and a 2:1 allocation, with FAB122 compared with placebo.

The study investigated the efficacy and safety of FAB122 as an oral formulation taken once daily. The summary specifies a 100 mg daily dose. The primary endpoint was change from baseline in ALSFRS-R score after 48 weeks. The registry lists 19 outcome measures and 18 posted secondary outcomes. Examples include the Combined Assessment of Function and Survival (CAFS), survival probability, ALSFRS-R change at other time points, and functional subdomains.

The registry record lists a start date of 2021-10-18, primary completion on 2023-10-26, and status as completed. Enrollment is listed as 313. The outcome summaries do not all have the same group counts as the enrollment figure; those counts are reported alongside the relevant outcomes. The reasons for differences in analysis counts, and details such as the statistical analysis populations, are not reported in the registry record.

Random allocation is generally used to reduce systematic differences between groups at the point of assignment, while a placebo comparator supports a contemporaneous comparison. These are general design principles, not confirmation of how successfully randomization balanced characteristics in this trial. Baseline characteristics and the method of sequence generation or allocation concealment are not reported in the registry record.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

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 Change From Baseline in Amyotrophic Lateral Sclerosis Functional Rating Scale - Revised (ALSFRS-R) Score After 48 Weeks., measured over 48 weeks.

The primary endpoint is the mean change from baseline in the Amyotrophic Lateral Sclerosis Functional Rating Scale–Revised (ALSFRS-R) score after 48 weeks. The registry describes the scale as ranging from 0 to 48 points, with higher values representing better outcome and lower values representing worse outcome. A change score captures the direction and size of movement from baseline over the specified follow-up period.

ALSFRS-R is a functional measure. The registry also lists secondary outcomes that examine its slope over time and changes in bulbar, fine motor, gross motor, and respiratory function. Those additional measures can describe different aspects or time courses of function, but the primary endpoint is specifically the overall ALSFRS-R change at 48 weeks.

In general, a continuous endpoint such as a scale score retains information about the amount of change rather than reducing it to a yes-or-no event. Comparing group means can summarize the average difference, while the spread of scores indicates variability among participants. A group mean does not describe every participant’s experience, and a change score does not by itself explain why a score changed.

The registry record does not state the primary endpoint’s analysis population, the handling of missing 48-week assessments, or the model used in the sponsor’s analysis. Those details matter when interpreting an endpoint based on follow-up measurements and cannot be inferred from the group means alone.

7. Results Posted in the Registry

• FAB122: mean -11.20 versus -10.80 on control; difference -0.40 (95% CI -2.63 to 1.83), standardized effect d = -0.05; z-test p = 0.725.

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.

Combined Assessment of Function and Survival (CAFS) at 48 and 72 Weeks.

• 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 deviations.
• Result:
  • FAB122 72 Weeks: mean 48.70 versus 54.15 on control; difference -5.45 (95% CI -17.55 to 6.65), standardized effect d = -0.19; z-test p = 0.377.
  • FAB122 48 Weeks: mean 153.31 versus 54.15 on control; difference 99.16 (95% CI 83.80 to 114.52), standardized effect d = 1.23; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between FAB122 72 Weeks and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for FAB122 48 Weeks than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change From Baseline in ALSFRS-R Score After 24 and 72* Weeks

• 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 deviations.
• Result:
  • FAB122 100mg 24 Weeks: mean -6.00 versus -5.40 on control; difference -0.60 (95% CI -1.89 to 0.69), standardized effect d = -0.11; z-test p = 0.361.
  • FAB122 100mg 72 Weeks: mean -15.20 versus -5.40 on control; difference -9.80 (95% CI -13.11 to -6.49), standardized effect d = -1.35; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between FAB122 100mg 24 Weeks and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for FAB122 100mg 72 Weeks than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The Slope of the Decrease in ALSFRS-R Score Over Time at 24, 48 and 72* Weeks;

• 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:
  • FAB122 100mg 24 Weeks: mean -0.30 versus -0.24 on control; difference -0.05 (95% CI -0.57 to 0.47), standardized effect d = -0.04; z-test p = 0.840.
  • FAB122 100mg 48 Weeks: mean -0.29 versus -0.24 on control; difference -0.04 (95% CI -0.56 to 0.48), standardized effect d = -0.03; z-test p = 0.872.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between FAB122 100mg 24 Weeks and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between FAB122 100mg 48 Weeks and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes broaden the clinical picture beyond the primary 48-week ALSFRS-R change. They include functional status at additional time points, the slope of ALSFRS-R change, CAFS, survival probability, and functional subdomains. This range can help readers see whether posted summaries point in a consistent direction across related measures or vary according to the outcome and follow-up time.

The overall pattern is not uniform across all measures and time points. Some posted unadjusted intervals include zero, while others do not. The registry record reports group means and summary-based comparisons, but no reported analyses for the listed secondary comparisons. The results therefore provide descriptive context rather than a complete account of a prespecified secondary analysis strategy. No secondary measure should be treated as a replacement for the primary endpoint.

In general, secondary outcomes can support interpretation when they were chosen in advance, analyzed appropriately, and considered alongside the primary outcome. However, examining many outcomes and time points increases the chance that some comparisons will appear more pronounced by chance. Multiplicity adjustments can address that issue, but the registry record does not report whether any adjustment was planned or applied. Without that information, unadjusted secondary p-values carry less weight than a result from a clearly specified confirmatory testing plan.

Differences in the numbers contributing to different secondary outcomes and time points also matter. The registry record gives those counts with the corresponding summaries, but does not explain all changes in available observations or analysis populations. As a general principle, a result based on a different set of observations may not be directly comparable with one based on another set. The secondary outcomes are best interpreted as additional, qualified evidence about function and survival, not as independent confirmation of the primary comparison.

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

• Combined Assessment of Function and Survival (CAFS) at 48 and 72 Weeks.
• Survival Probability
• Change From Baseline in ALSFRS-R Score After 24 and 72* Weeks
• The Slope of the Decrease in ALSFRS-R Score Over Time at 24, 48 and 72* Weeks;
• Change From Baseline in ALSFRS-R Score on Bulbar Function (Question 1-3 of the ALSFRS-R) After 24, 48 and 72* Weeks;
• Change From Baseline ALS Functional Rating Scale - Revised Score - Fine Motor Function
• Change From Baseline ALS Functional Rating Scale - Revised Score - Gross Motor Function
• Change From Baseline ALS Functional Rating Scale - Revised Score - Respiratory Function

9. Statistical Interpretation

10. Statistical Methods Explained

The registry posts continuous outcome summaries as group means and standard deviations. For the primary endpoint, the mean change was -11.2 in the FAB122 group and -10.8 in the placebo group. The comparison is a mean difference of -0.4, calculated as the FAB122 group mean minus the placebo group mean. It is an unadjusted comparison of posted summaries; it should not be mistaken for a reported adjusted sponsor analysis.

What does a mean difference describe?

In general, a mean difference expresses the average contrast between two groups on the measure’s original scale. It preserves the units and can be read alongside the meaning of the measure. Here, the measure is ALSFRS-R change, in units on a scale. A negative mean change represents a lower follow-up score relative to baseline, while the between-group difference compares the averages, not the change of any one participant.

A mean can be affected by the distribution of observations and may not reflect the experience of every participant. The standard deviations reported for the primary groups are 7.9 and 8.4. In general, a standard deviation describes how dispersed individual observations are around a group mean; it is not the uncertainty interval for the mean difference.

What does the confidence interval add?

The primary 95% confidence interval is -2.629 to 1.829. In general, a confidence interval describes statistical uncertainty around an estimate under the assumptions of the method used. It provides a range of values compatible with the observed data and that method; it is not a guarantee that the true value lies inside the particular interval. Because the interval crosses zero, it includes no difference as well as differences in either direction.

The unadjusted p-value is 0.725. In general, a p-value evaluates how compatible the data are with a specified null hypothesis under the statistical model. It is not the probability that the null hypothesis is true, nor does it measure the size or importance of an effect. The registry record does not report the sponsor’s primary test procedure, so the p-value displayed with these summaries should be read as an unadjusted result rather than as a full account of the trial’s analysis plan.

Why does adjustment matter?

In general, adjusted analyses can account for prespecified covariates or features of the study design, potentially changing both the estimate and its uncertainty. Repeated measurements, outcome distributions, baseline scores, and missing follow-up can also affect model choice. The registry record does not report whether or how the sponsor’s primary analysis adjusted for such factors. No model or analysis population should be inferred from the posted means alone.

Recalculated comparisons in the secondary summaries are likewise unadjusted. Multiple outcome measures and follow-up times create opportunities for chance findings when many comparisons are examined. In general, multiplicity procedures can control the chance of false-positive conclusions across a defined family of tests. Whether the trial had a prespecified multiplicity strategy, and what it was, is not reported in the registry record. Thus, the posted secondary p-values should be treated as exploratory context rather than as a set of confirmatory tests.

Why does over-dispersion matter?

In general, over-dispersion occurs when variability in the data is greater than a statistical model expects. If a model assumes too little variability, standard errors may be too small and confidence intervals too narrow. This issue is most directly relevant to count or event data, although model assumptions matter for continuous outcomes too. The posted primary outcome is continuous, and the registry record does not report an over-dispersion assessment or a model for this endpoint. It would be inappropriate to claim that over-dispersion was present or that it affected the result.

The slope outcome is reported with standard errors as its dispersion measure, whereas other continuous outcomes list standard deviations. These quantities describe different aspects of uncertainty and should not be compared as if they were the same measure. General statistical interpretation requires attention to the measure used, the analysis method, and the population contributing data. The registry record does not provide the detailed methods needed to reconstruct the sponsor’s analyses.

11. Confidence Intervals and Precision

The primary estimated mean difference is -0.4, with a 95% confidence interval from -2.629 to 1.829. The interval is wide enough to include zero and values on either side of it. It therefore communicates uncertainty about both the direction and size of the group difference, rather than supporting a single precise value.

In general, a confidence interval is more informative than a point estimate alone because it displays a range of estimates compatible with the data under the method’s assumptions. A narrower interval indicates greater statistical precision; a wider interval indicates less precision. Precision is not the same as clinical importance, and the interval does not resolve whether a particular value would be important to patients. The registry record does not report a threshold for a clinically important difference.

The primary group standard deviations are 7.9 for FAB122 and 8.4 for placebo, while the outcome summary counts are 171 and 76, respectively. In general, precision depends on the observed variability and the amount of information contributing to the analysis. These posted counts and spreads offer context, but they do not reveal the full analysis method or account for any missing data, clustering, or adjustment used by the sponsor.

The unadjusted p-value of 0.725 is consistent with the interval including zero, but the p-value alone does not describe the range of plausible effects. The registry record does not report a sponsor confidence interval or adjusted primary estimate, so the posted interval should be read as a summary-based, unadjusted calculation rather than as a substitute for unreported model-based results.

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 sample-size figures are planning illustrations based on the observed effect, not the trial’s original design assumptions. For these continuous outcomes, the figures are participants per arm, not total participants or total events. The listed assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is the stated fraction of the observed effect. Time-to-event calculations, if present, are expressed as total events, but the posted planning figures described for these outcomes are participants per arm.

The 80% power column means the planned sample size is calculated to give an 80% chance of detecting the specified effect under the stated assumptions, if that effect is real and the assumptions hold. The 90% column uses a higher target chance of detection, and therefore generally requires more participants for the same effect. Neither column gives the probability that the observed result is true.

Each planning row scales the observed effect: 100% uses the full observed effect, 75% uses a smaller effect, and 50% uses a still smaller effect. Smaller effects are harder to distinguish from random variation, so the planning calculations require more participants per arm as the target effect gets smaller. For example, the primary outcome illustration lists 6,368 participants per arm for 80% power at 100% of the observed effect, and 25,472 participants per arm at 50% of the observed effect. These are illustrations derived from the observed result, not the trial’s enrollment target.

These figures are not observed power. Observed power calculated from an estimated effect would not add useful evidence beyond the estimate and its uncertainty. The trial’s own original sample-size justification and assumptions are not reported in the registry record. The planning display should therefore be read as a sensitivity illustration showing how the required scale of a hypothetical study changes with effect size, not as evidence about the adequacy or success of this trial’s design.

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

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -0.400; pooled standard deviation σ = 8.056.
2. n = 2 × (1.96 + 0.842)² × 8.056² / -0.400² = 6,367.9, rounded up to 6,368 participants per arm 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
delta <- -0.399999999999999                      # observed difference in means
sigma <- 8.05635761117787                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(5178810)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 6,368 (80% power), 8,525 (90% power)
 75% of observed effect: n per arm = 11,321 (80% power), 15,156 (90% power)
 50% of observed effect: n per arm = 25,472 (80% power), 34,100 (90% power)
power.t.test: 6368.8 
Simulated power at n = 6,368 per arm: 0.800 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Multiplicity, Missing Data and Analysis Populations

The registry record lists multiple outcome measures, including a primary endpoint and secondary measures spanning function, survival, and additional time points. When many outcomes or time points are tested, the chance of at least one apparently notable result can increase even when no underlying differences exist. In general, multiplicity methods define a family of comparisons and adjust interpretation or testing to limit that risk.

Whether the trial had a prespecified hierarchy of outcomes, a multiplicity adjustment, or another strategy for controlling false-positive findings is not reported in the registry record. The registry’s list of outcomes alone does not establish which comparisons were confirmatory, which were exploratory, or how the analyses were prioritized. The unadjusted secondary p-values should therefore be interpreted cautiously and not as a collection of independent confirmations.

Missing-data handling is another important uncertainty. Follow-up outcome counts vary across the posted results, but the reasons for unavailable observations and the methods used to handle them are not reported in the registry record. In general, complete-case summaries can be affected if the participants with observed outcomes differ systematically from those without them. Other methods make assumptions about missing outcomes, and different assumptions can produce different estimates.

The registry record does not report whether analyses used an intention-to-treat population, a per-protocol population, or another analysis set. It also does not state the sponsor’s approach to withdrawals, intercurrent events, imputation, or sensitivity analyses. These omissions limit assessment of whether the posted outcome summaries represent all randomized participants or a subset defined by data availability or protocol criteria.

Consequently, the posted means and recalculated comparisons can be described, but the robustness of the sponsor’s intended analysis cannot be evaluated from the registry record alone. The original statistical analysis plan, analysis-population definitions, and missing-data procedures are not reported in the registry record. These uncertainties do not establish that the analyses were inadequate; they identify information needed for a fuller statistical appraisal.

15. 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: respiratory failure (9.3%), pneumonia (2.9%), pulmonary embolism (2.1%), respiratory disorder (2.1%), covid-19 (2.0%).

The registry posts serious adverse event counts for 62 of 205 participants at risk in the FAB122 group and 28 of 97 at risk in the placebo group. It also posts other adverse event counts for 180 of 205 and 82 of 97, respectively, and deaths as 20 and 7. These are descriptive counts with the listed denominators; they do not by themselves establish that an event was caused by the study drug or show how events were defined, timed, or adjudicated.

The most frequently listed serious adverse event terms include respiratory failure (9.3%), pneumonia (2.9%), pulmonary embolism (2.1%), respiratory disorder (2.1%), COVID-19 (2.0%), and dysphagia (2.0%). The registry record does not clarify the denominator or whether these percentages represent participants, event counts, or another reporting basis, so they should be read as posted rather than compared with the group counts as if the basis were known.

In general, safety comparisons need information about exposure time, event definitions, severity, and attribution, in addition to counts. Those details and a statistical comparison of the safety groups are not reported in the registry record. The counts are useful for describing what was posted, but they do not establish comparative risk or causation.

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

The primary posted result describes a small estimated difference in mean ALSFRS-R change at 48 weeks, with uncertainty spanning zero and values on either side. It does not establish that the groups had identical outcomes, nor does it establish a definite difference. The interval and unadjusted p-value should be read together with the trial design and the limitations in the registry’s reported methods.

The result concerns group averages on a functional scale. It does not describe every participant’s outcome, explain why an individual’s score changed, or provide a direct measure of all aspects of ALS. The registry also includes secondary measures, but their multiplicity and analysis details are not reported. They add context without resolving the uncertainty in the primary comparison.

In general, statistical evidence and clinical importance are related but distinct. A confidence interval describes statistical precision under the analysis assumptions; whether the values it contains are clinically meaningful depends on a clinically justified threshold and context. Such a threshold is not reported in the registry record. The posted result should not be converted into a medical recommendation or a conclusion about whether an individual should receive a treatment.

The registry identifies the study as completed and gives an overall enrollment figure, but it does not report the detailed sponsor analysis, analysis population, or missing-data approach needed to fully evaluate the primary result. The comparisons presented from group summaries are unadjusted recalculations, not a replacement for an analysis with documented methods.

Thus, the most defensible reading is narrow: the registry’s posted 48-week summary does not show a clearly separated group mean difference, and its confidence interval leaves uncertainty about the direction and magnitude of the contrast. The record is not enough to settle broader questions about efficacy, safety, individual outcomes, or clinical decisions.

17. Why This Trial Matters Statistically

This trial is statistically informative as a worked example of how to read a randomized, placebo-controlled study when the registry provides group summaries but limited analysis detail. The primary endpoint is a continuous functional measure, and the posted mean difference, confidence interval, and p-value illustrate why a point estimate should not be interpreted alone. Uncertainty includes both the range of compatible effects and the assumptions behind the calculation.

The record also highlights why outcome counts matter. The registry lists enrollment, while different outcomes and follow-up times have their own contributing counts. Those figures should not be collapsed into a single analysis population without documentation. The reasons for variation and the handling of missing data are not reported in the registry record.

The many secondary outcomes make multiplicity a practical interpretive issue. A broad set of function and survival measures can give a more complete description, but unadjusted tests across outcomes and time points do not carry the same weight as a defined confirmatory plan. The registry record does not report the multiplicity strategy, so the distinction between confirmatory and exploratory findings remains uncertain.

Finally, the planning illustrations demonstrate how sample-size requirements depend on the effect targeted and the assumptions used. They are not a reconstruction of the original design rationale. Keeping observed results, unadjusted recalculations, and hypothetical planning calculations separate is essential to avoid overstating what the registry record establishes.

18. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

Several trial-specific details needed for a full statistical assessment are not reported in the registry record. These include the original sample-size justification, the detailed sponsor analysis method, the primary analysis population, the missing-data strategy, and any multiplicity procedure. Without them, the summary-based calculations cannot be verified against the intended primary analysis.

The outcome counts vary by endpoint and follow-up time, and the registry does not explain all reasons for that variation. The enrollment figure should not be assumed to equal the number contributing to each analysis. The record also does not describe participant flow, withdrawals, adherence, or the handling of participants who did not complete a given assessment.

The available primary comparison is based on group means and standard deviations, with an unadjusted recalculation. It does not provide individual-level data, baseline distributions, model diagnostics, or adjusted estimates. The 95% confidence interval therefore conveys uncertainty for the posted comparison, but not every uncertainty that might arise from design, measurement, or missingness.

For safety, the record posts adverse event counts and a list of serious event terms, but does not provide sufficient detail in the registry record about exposure duration, event adjudication, attribution, or the denominator basis for the listed percentages. The counts should not be interpreted as causal or as a complete comparative safety analysis.

These limitations concern what can be assessed from the registry record. They do not establish that the trial lacked procedures or analyses; details not included in the registry record are simply not reported in the registry record.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Study to Investigate the Efficacy and Safety of FAB122 (Daily Oral Edaravone) in Patients With Amyotrophic Lateral Sclerosis — NCT05178810.
• Registry record last updated 2025-03-18; status last verified 2025-03.
• Results first posted 2025-03-18.
• 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.

22. Record Summary

The registry record describes a completed, randomized, parallel-group, placebo-controlled Phase III study of FAB122 in ALS. The study summary specifies a 2:1 allocation and 100 mg FAB122 once daily as an oral formulation. Enrollment is listed as 313; the study start date is 2021-10-18 and primary completion is 2023-10-26.

The primary endpoint is mean change from baseline in ALSFRS-R score after 48 weeks. The posted group means are -11.2 for FAB122 and -10.8 for placebo, with an unadjusted mean difference of -0.4 and a 95% confidence interval from -2.629 to 1.829. The registry also posts secondary functional and survival outcomes and adverse event counts.

The registry record does not report the detailed sponsor analysis plan, analysis populations, missing-data procedures, or multiplicity approach. Secondary comparisons and sample-size illustrations therefore require cautious interpretation.