HEALEY ALS Platform Trial - Regimen E SLS-005 - Trehalose: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for HEALEY ALS Platform Trial - Regimen E SLS-005 - Trehalose (NCT05136885), a randomized phase 2, phase 3 study. The primary outcome is Disease Progression as Assessed by the ALSFRS-R Slope.

2. Clinical Question

The ALSFRS-R records physical function across activities affected by ALS. The registry describes scores from 0 to 48, with higher scores indicating more physical function. The primary outcome is the slope, expressed in points per month, so it represents the rate of change rather than a single score at the end of follow-up.

The posted arm means were -0.91 points per month for SLS-005 and -1.06 points per month for matching placebo. The registry’s own primary analysis instead reports a Bayesian shared-parameter model estimate as a disease rate ratio of 0.87, with a 95% confidence interval from 0.665 to 1.102. These are different statistical summaries and should not be treated as interchangeable. The interval for the reported ratio includes 1, so the registry estimate does not clearly distinguish the modeled rate from equality on that scale.

3. Trial Design

The HEALEY ALS Platform Trial is described in the registry as a perpetual, multicenter, multi-regimen trial evaluating investigational products for ALS. Regimen E evaluates SLS-005, a trehalose injection, against matching placebo. The record lists the study as randomized, quadruple-masked, and parallel, with Phase 2 and Phase 3 classifications. Its status is completed.

For Regimen E, both SLS-005 and matching placebo were administered by infusion once weekly for 24 weeks. The primary outcome timeframe was 24 weeks. The registry lists enrollment as 161. That enrollment figure should not be confused with the counts contributing to the posted primary outcome: the outcome population was a Full Analysis Set that included shared placebo participants from other regimens, and the posted arm counts are 120 for SLS-005 and 204 for matching placebo.

The registry identifies the primary outcome as disease progression assessed by the ALSFRS-R slope. Secondary outcomes include respiratory function, muscle strength, and participants experiencing death or death equivalent. The record lists 5 outcome measures and 4 analyses, while the posted secondary outcomes include the measures described in the statistical results.

The record gives the study start as 2022-02-21 and primary completion as 2023-08-25. It does not report the randomization procedure, the masking procedures for each role, eligibility criteria, the planned allocation ratio, or the original sample-size justification. The detailed protocol and the trial’s original design assumptions are not reported in the registry record. The summary describes the broader platform’s purpose, but does not supply additional design details for this comparison.

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

Analysis population for the primary outcome, as defined in the registry: Outcome measure data was analyzed using the Full Analysis Set, which included shared placebo from other regimens, as pre-specified in the Regimen Statistical Analysis Plan. Regimen A (NCT04436497), Regimen B (NCT04436510), Regimen C (NCT04414345) and Regimen D (NCT04615923) contributed placebo participants into the shared placebo cohort used for analysis.

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

Population: Baseline Analysis Population includes only placebo participants from the Regimen E Efficacy Regimen Only (ERO) sample; shared placebo participants from other regimens are not included in the Baseline Analysis Population.

6. Primary Endpoint

The registry lists the primary outcome as Disease Progression as Assessed by the ALSFRS-R Slope, measured over 24 Weeks.

The primary endpoint is disease progression assessed by the ALSFRS-R slope over 24 weeks, expressed in points per month. The ALSFRS-R measures functional abilities affected by ALS. Each type of function is scored from 0 to 4; the total ranges from 0 to 48, and higher scores indicate more physical function. The slope expresses the rate of change in the total score over time, rather than relying on a single measurement.

A slope is useful for describing progression because it incorporates the direction and rate of change during the stated observation period. The registry reports arm means of -0.91 points per month with SLS-005 and -1.06 points per month with matching placebo. Because higher ALSFRS-R scores indicate more function, a less negative slope is descriptively consistent with a slower decline in score. That description alone is not a treatment conclusion: the comparison needs to be interpreted alongside the prespecified analysis and its uncertainty.

The registry’s reported primary analysis uses a Bayesian shared-parameter model and presents a disease rate ratio, not a difference between the posted arm slopes. The reported ratio is 0.87, with a 95% confidence interval from 0.665 to 1.102. That model-based estimate and the arm means answer related but not identical statistical questions. The registry does not report a p-value for the primary analysis.

7. Results Posted in the Registry

• SLS-005: mean -0.91 versus -1.06 on control; difference 0.15 (95% CI 0.13 to 0.17), standardized effect d = 1.66; z-test p = <0.001.

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.

Respiratory Function

• 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:
  • SLS-005: mean -11.40 versus -10.85 on control; difference -0.55 (95% CI -4.07 to 2.97), standardized effect d = -0.04; z-test p = 0.760.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between SLS-005 and the control. The interval gives the range of effects that remain compatible with the data.

Muscle Strength

• 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:
  • SLS-005: mean -26.19 versus -27.11 on control; difference 0.92 (95% CI -5.31 to 7.15), standardized effect d = 0.03; z-test p = 0.772.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between SLS-005 and the control. The interval gives the range of effects that remain compatible with the data.

Number of Participants That Experienced Death or Death Equivalent

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • SLS-005: 8.3% (10/120) versus 4.9% (10/203) on control; risk difference 3.4 percentage points (95% CI -2.4 to 9.2), risk ratio 1.69 (0.73–3.95); unadjusted two-proportion z-test p = 0.220.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between SLS-005 and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes cover different aspects of ALS: respiratory function, muscle strength, and death or death equivalent. Their analyses do not form a single combined measure, and each outcome has its own scale and statistical method. Taken together, the posted results do not provide a consistent body of precise evidence that resolves the uncertainty in the primary analysis.

The continuous secondary outcomes are analyzed as net mean differences, while the death-or-death-equivalent result is assessed with a log-rank test. These analyses therefore address different statistical quantities. Their results can add context to the primary outcome, but they do not directly validate or overturn the Bayesian disease-rate-ratio estimate. The secondary results should be viewed as complementary outcome-specific evidence, not as a single confirmatory test.

Unadjusted secondary results carry less inferential weight when several outcomes are examined. In general, making multiple comparisons increases the chance of finding an apparently notable result by chance, unless an analysis plan accounts for multiplicity. The registry record does not report a multiplicity adjustment or a hierarchy that identifies which secondary outcomes were confirmatory. The reported secondary p-values should therefore be read cautiously and not treated as if each were the sole planned test.

The secondary analyses also have limits as a check on the primary result. Their endpoints differ from the ALSFRS-R slope, their populations and measures can differ, and their reported analysis methods are not identical. A non-significant result does not prove the absence of an effect, just as an isolated favorable result would not establish one. The broad pattern is that the posted secondary analyses do not supply a clear, precise basis for a stronger conclusion than the primary analysis supports.

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

• Respiratory Function
• Muscle Strength
• Number of Participants That Experienced Death or Death Equivalent

9. Statistical Interpretation

10. Statistical Methods Explained

The registry presents more than one statistical summary for the primary outcome, and the summaries use different methods. Reading them correctly begins with distinguishing the reported sponsor analysis from a simple recalculation based on the posted group summaries.

What does the registry’s primary model report?

The primary reported method is a Bayesian shared-parameter model. A Bayesian model combines the observed trial data with a statistical model to estimate quantities of interest and their uncertainty. A shared-parameter structure allows information to be represented jointly across related parts of an analysis. The registry labels its primary estimate a disease rate ratio and reports 0.87 with a 95% confidence interval from 0.665 to 1.102. The registry record does not describe the model’s full specification, prior distributions, computational details, or the exact interpretation of the shared parameter beyond the method and result it names.

A ratio is interpreted relative to 1: a ratio of 1 corresponds to equality on the ratio scale. The confidence interval includes 1, so the reported range is compatible with equality as well as values on either side. No p-value is reported for this primary model. A confidence interval should not be converted into an unreported p-value or treated as a complete account of the analysis.

What is the unadjusted recalculation?

The posted primary arm means are -0.91 and -1.06 points per month. The simple recalculation compares those means, producing a mean difference of 0.15. This calculation is unadjusted: it does not reproduce the registry’s Bayesian shared-parameter model or any features of its analysis that are not captured by the displayed summaries. It is therefore a supplementary check on the posted group summaries, rather than a competing sponsor analysis.

The scale also matters. For ALSFRS-R, higher scores indicate more physical function, so a less negative slope corresponds descriptively to a less rapid decline in the score. But a favorable-looking direction in the means is not itself proof of a reliable difference. In particular, the sponsor’s analysis uses a different estimand and method. Its result takes precedence in interpreting the trial’s reported inference.

How should secondary analyses be read?

Respiratory function and muscle strength are continuous outcomes reported as percent change from baseline to 24 weeks. The registry gives least-squares means and standard errors for the arms, and reports mixed models analyses of net mean difference. A least-squares mean is a model-based group estimate, while its standard error describes uncertainty in that estimate. The registry does not give the full model specifications, covariate details, or missing-data procedures for these mixed models.

The posted respiratory-function analysis reports a net mean difference of -0.55, with a 95% confidence interval from -4.06 to 2.97 and p = 0.761. The muscle-strength analysis reports a net mean difference of 0.92, with a 95% confidence interval from -5.37 to 7.21 and p = 0.774. In each case the interval crosses zero, the no-difference value for a difference scale. These analyses do not establish a clear between-group difference in the stated outcomes.

The death-or-death-equivalent outcome is a count of participants during baseline to 24 weeks. Its posted analysis uses a log-rank test and reports p = 0.214. A log-rank test compares event-time patterns over follow-up, rather than simply comparing end-of-period percentages. The record does not provide a corresponding hazard ratio or confidence interval for this analysis.

Why can variability affect an estimate?

In general, variability describes how widely individual observations or estimates vary. Greater variability usually makes a group comparison less precise, while less variability can yield a narrower interval when other aspects of the analysis are unchanged. For continuous outcomes, the registry lists standard deviations for the primary arm means and standard errors for the secondary least-squares means. These quantities describe different aspects of the data and model; they should not be treated as equivalent.

In general, over-dispersion occurs when observed variation is greater than a statistical model expects. If a model assumes too little variation, it can understate uncertainty and make evidence appear more precise than it is. The registry record does not report an over-dispersion assessment for these outcomes, so no conclusion about whether it was present can be drawn from the posted results.

What do the reported p-values mean?

In general, a p-value measures how unusual data at least as incompatible with a specified null model would be if that model held, subject to the assumptions of the test. It is not the probability that the null hypothesis is true, nor a measure of clinical importance. The unadjusted p-values shown for secondary outcomes do not account, in their stated form, for the possibility of multiple outcome comparisons. The registry’s multiplicity plan is not reported.

Finally, none of the statistical methods alone explains how missing observations were handled or how analysis populations were constructed beyond the stated Full Analysis Set description for the primary outcome. Those details are not reported in the registry record. This limits the ability to independently reproduce the sponsor’s model-based estimates from the posted summaries.

11. Confidence Intervals and Precision

A confidence interval describes a range of values compatible with the data and the statistical method, while reflecting sampling uncertainty. It is not a guarantee that the true effect lies within the interval, and it does not show the range of individual participant outcomes. Its width is informative about precision: a narrower interval indicates a more tightly estimated comparison under the model; a wider interval indicates greater uncertainty.

For the primary outcome, the registry reports a disease rate ratio of 0.87 with a 95% confidence interval from 0.665 to 1.102. Because the interval includes 1, the result is compatible with no difference on the ratio scale as well as values on either side. The registry does not report a p-value for this primary analysis. The interval should be interpreted as the uncertainty around the sponsor’s model-based estimate, not around the separate unadjusted mean difference.

The recalculated primary mean difference is 0.15 points per month. It is based on the posted arm summaries and is not the same estimand or model as the sponsor’s shared-parameter result. For that reason, the very different summaries should not be compared as though they were alternative calculations of an identical quantity.

The secondary continuous-outcome intervals are wide enough to include zero: respiratory function has a reported interval from -4.06 to 2.97, and muscle strength has an interval from -5.37 to 7.21. Those ranges include no net mean difference and also allow differences in either direction. The death-or-death-equivalent analysis reports a p-value but no confidence interval in the registry results. Precision is therefore not conveyed in the same way for that endpoint.

Confidence intervals do not address every source of uncertainty. They do not, by themselves, resolve questions about analysis populations, missing observations, outcome measurement, or multiplicity. The registry record does not report several of those details. The intervals should be read as method-specific measures of statistical uncertainty, alongside those limits.

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 illustrations translate the observed effect into planning scenarios. For continuous outcomes and the death-or-death-equivalent comparison, the displayed figures are participants per arm. The general planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation; each scenario uses the stated fraction of the observed effect as the effect to detect. For time-to-event tables, the figures instead represent the total number of events, but the posted secondary death-or-death-equivalent illustration is based on a participant count comparison.

The 80% power column describes the number of participants per arm that a hypothetical study would need, under those assumptions, to have an 80% chance of detecting the specified effect if that effect were the true one. The 90% power column uses a higher chance of detecting that effect and therefore generally requires more participants per arm. These are planning quantities, not guarantees that a future study will produce a statistically significant result.

Rows that plan for 75% or 50% of the observed effect use smaller effects than the row planning for 100% of the observed effect. Smaller effects are harder to distinguish from random variation, so they require more participants under the same assumptions. The pattern is particularly important when the observed effect is small or uncertain: the planning result can become very large, and the calculation may be sensitive to how the observed effect was estimated.

These figures are not observed power for the completed trial. They are planning illustrations computed from the observed effect, not the trial’s own design justification. The original design assumptions and sample-size justification are not reported in the registry record. The illustrations should not be used to infer whether the completed study was adequately designed or whether its findings are true.

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 = 0.150; pooled standard deviation σ = 0.091.
2. n = 2 × (1.96 + 0.842)² × 0.091² / 0.150² = 5.7, rounded up to 6 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 <- 0.15                      # observed difference in means
sigma <- 0.0906317201406449                     # 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(5136885)
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 (80% power), 8 (90% power)
 75% of observed effect: n per arm = 11 (80% power), 14 (90% power)
 50% of observed effect: n per arm = 23 (80% power), 31 (90% power)
power.t.test: 6.8 
Simulated power at n = 6 per arm: 0.733 (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. Analyses Reported by the Sponsor

The registry’s own primary result comes from a Bayesian shared-parameter model and is reported as a disease rate ratio of 0.87 with a 95% confidence interval from 0.665 to 1.102. That is the result to prioritize when describing the trial’s formal primary analysis. The interval includes 1, and the registry does not report a primary p-value.

The separate recalculation uses the posted arm means of -0.91 and -1.06 points per month to give a mean difference of 0.15. It is a simple, unadjusted comparison of summary statistics. It does not reproduce the sponsor’s model, its shared-parameter structure, or necessarily the same estimand. It can be useful for understanding the displayed arm values, but should not replace or overrule the reported analysis.

The registry marks the discrepancy indicator as false. Regardless, the distinction between the analyses remains important: the sponsor’s model-based estimate is the reported primary inference, while the recalculation is an auxiliary summary. The two estimates should not be treated as equivalent merely because they concern the same clinical outcome. Interpretation should center on the sponsor’s analysis and its uncertainty, while using the group means as descriptive context.

15. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when a study assesses several outcomes, comparisons, or analyses. Even when each individual test uses a conventional significance threshold, examining many tests can increase the chance of at least one apparently unusual result by chance. Statistical plans may address this through prespecified outcome hierarchies, adjustment procedures, or other strategies. The registry record does not report whether the secondary analyses were adjusted for multiplicity, or how the primary and secondary outcomes were ordered for confirmatory interpretation.

This matters because the secondary results include distinct endpoints and different statistical methods. Without a reported multiplicity strategy, the secondary p-values should be treated as outcome-specific, unadjusted evidence rather than as a set of independent confirmations. The registry’s own primary analysis remains the most relevant formal result for the primary question.

Analysis populations are only partly described. The primary outcome population is stated to be a Full Analysis Set that included shared placebo participants from other regimens, as prespecified in the Regimen Statistical Analysis Plan. The record names other regimens contributing placebo participants. However, the complete population definition, handling of protocol deviations, and population rules for all secondary analyses are not reported in the registry record.

Missing-data methods are also not reported in the registry record. The posted counts vary across outcomes, and the primary outcome includes shared placebo participants, but those details alone do not explain why particular observations are available or absent. The record does not specify the amount or pattern of missing data, whether imputation was used, or how participants with incomplete follow-up contributed to each model. No assumption about those procedures should be inferred from the summary statistics.

Likewise, the registry does not report the full model specifications, covariates, sensitivity analyses, or interim-analysis procedures. These omissions limit independent assessment of robustness. They do not show that a particular analysis choice was inappropriate; they mean the posted registry record does not allow those aspects to be evaluated.

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: acute respiratory failure (2.5%), amyotrophic lateral sclerosis (2.5%), pneumonia aspiration (2.4%), hip fracture (2.4%), subdural haemorrhage (2.4%).

The registry reports serious adverse events affecting 19 of 120 participants in the SLS-005 safety group and 3 of 41 participants in the matching-placebo safety group. It also reports other adverse events affecting 107 of 120 and 33 of 41, respectively. Death counts are listed as 6 for SLS-005 and 0 for matching placebo. These are descriptive counts within the reported safety groups, not estimates of treatment effect.

The serious-event terms listed most frequently include acute respiratory failure and amyotrophic lateral sclerosis, each reported as 2.5%, alongside pneumonia aspiration, hip fracture, subdural haemorrhage, and colitis ischaemic, each reported as 2.4%. The record does not provide further context for these percentages in the listed summary, such as event-level counts for every term or whether participants could contribute more than one event. The categories should not be added together.

The safety denominators differ from the posted primary efficacy counts, especially for matching placebo. That reflects the distinct reported groups and should not be obscured by comparing counts alone. The registry summaries do not establish whether an event was caused by study treatment. Safety counts require clinical context, event timing, severity, and the trial’s adverse-event assessment procedures, some of which are not reported in the registry record.

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

The results describe a randomized, quadruple-masked, parallel comparison of SLS-005 with matching placebo in Regimen E of the HEALEY ALS Platform Trial. The primary outcome was ALSFRS-R disease-progression slope over 24 weeks. The posted arm means were -0.91 and -1.06 points per month, while the registry’s own analysis reported a Bayesian disease rate ratio of 0.87 with a 95% confidence interval from 0.665 to 1.102.

Those results do not establish a clear difference on the sponsor’s reported ratio scale: its interval includes 1. They also do not establish that the treatments are equivalent. An interval that includes the no-difference value can reflect uncertainty about whether an effect exists and about its magnitude. The registry does not report a p-value for the primary model, and the simple recalculation from group means is not a substitute for that model-based analysis.

The secondary outcomes add information about respiratory function, muscle strength, and death or death equivalent, but they use distinct measures and analyses. Their posted results do not remove the primary uncertainty. Their interpretation is further limited by the absence of a reported multiplicity plan and details about missing data and some analysis populations.

These registry results do not, on their own, establish a treatment recommendation or settle the broader question of benefit and risk. They are a summary of statistical comparisons for specified outcomes and timeframes. The registry record does not provide all details needed to independently reconstruct the analyses, assess every assumption, or understand the full clinical context. The appropriate statistical reading is limited to what the reported estimates, intervals, and outcome summaries support.

18. Why This Trial Matters Statistically

This trial is statistically notable as part of a platform design described as a perpetual, multicenter, multi-regimen evaluation in ALS. Regimen E compares SLS-005 with matching placebo, while the primary analysis uses a Full Analysis Set that includes shared placebo participants from other regimens. That pooling feature is central to interpreting the posted group counts and the Bayesian shared-parameter analysis.

The primary outcome uses an ALSFRS-R slope, a rate-based summary of functional change rather than a single endpoint score. The reported arm means provide a direct descriptive view, while the sponsor’s model supplies the primary inferential result on a disease-rate-ratio scale. Seeing both makes clear why estimates from different methods and estimands should not be conflated.

The registry also illustrates the difference between statistical evidence and statistical precision. The primary model’s interval includes the ratio-scale value corresponding to no difference, and the secondary confidence intervals allow effects in either direction. A result can be informative without settling the treatment question; uncertainty is part of the result, not a reason to substitute an unadjusted recalculation for the reported analysis.

Finally, the posted planning illustrations show why planning based on an observed effect must be treated carefully. Their numbers depend on the chosen effect fraction and stated assumptions, while the original design justification is not reported. This trial record therefore offers useful material for learning about estimands, shared controls, model-based inference, secondary outcomes, and the limits of post hoc planning calculations.

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.

Interpretation is constrained by the registry’s limited description of the primary model. It names a Bayesian shared-parameter model and reports a disease rate ratio, but does not report the model specification, prior distributions, computational details, or sensitivity analyses. The sponsor’s result can be described, but cannot be independently reconstructed from the registry summary alone.

The primary outcome population includes shared placebo participants from other regimens, while the overall enrollment and posted outcome counts are not the same quantities. The record provides the Full Analysis Set description and names contributing regimens, but does not fully explain how participants were selected for each analysis or how the analysis populations relate to enrollment. Safety counts use a different placebo denominator from the posted primary outcome, so efficacy and safety summaries should not be directly conflated.

The registry does not report missing-data procedures, the complete secondary-outcome population definitions, multiplicity control, interim analyses, or the trial’s original sample-size justification. It also does not provide all details of the secondary mixed models. These omissions limit assessment of robustness and reproducibility; they do not establish that any particular method was unsuitable.

The 24-week outcome window gives a defined period for the posted results, but the registry summary does not establish what longer-term outcomes might be. The observed-effect planning illustrations are not the original trial design calculation and should not be read as evidence of observed power. Finally, adverse-event counts are descriptive and do not by themselves show causation.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: HEALEY ALS Platform Trial - Regimen E SLS-005 - Trehalose — NCT05136885.
• Registry record last updated 2025-05-14; status last verified 2025-05.
• Results first posted 2024-08-28.
• 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

The completed HEALEY ALS Platform Trial Regimen E compared weekly intravenous SLS-005 (trehalose) with matching placebo over 24 weeks in participants with ALS. The record classifies the study as randomized, quadruple-masked, parallel, and Phase 2 and Phase 3. Enrollment is listed as 161.

The primary outcome was ALSFRS-R disease-progression slope. The registry’s reported Bayesian shared-parameter analysis gives a disease rate ratio of 0.87, with a 95% confidence interval from 0.665 to 1.102. Its interval includes 1. The posted arm means and the simple recalculation are descriptive and do not replace that reported analysis.

Secondary outcomes cover respiratory function, muscle strength, and death or death equivalent. The record also posts adverse-event counts. Important details—including missing-data methods, multiplicity handling, and the original sample-size justification—are not reported in the registry record.