Clarithromycin for the Treatment of Hypersomnia: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Clarithromycin for the Treatment of Hypersomnia (NCT01146600), a randomized phase 2 study. The primary outcome is Psychomotor Vigilance Task (PVT) Reaction Time.

2. Clinical Question

The clinical question was whether Psychomethor Vigilance Task (PVT) reaction time differed between clarithromycin and placebo at the end of week 2 of each intervention among participants with hypersomnia who took both study drugs. On this task, lower reaction-time values indicate faster responses and therefore greater vigilance. The comparison is a measure of task performance, not a direct measure of every aspect of daytime sleepiness or daily functioning.

3. Trial Design

This was a phase 2, randomized, quadruple-masked crossover trial. The registry lists an enrollment of 26. In a crossover design, each participant receives the intervention and its comparator in different periods, so the participant can contribute measurements under both conditions. The listed sequences were clarithromycin followed by placebo and placebo followed by clarithromycin. The registry describes the order as opposite between groups and says investigators and subjects remained blinded to group allocation and treatment order.

The primary analysis population was narrower than the enrollment: it comprised subjects who took both study drugs. The posted primary summaries include 20 participants in each condition, as well as a baseline summary for 20 participants. The registry record does not explain why the primary analysis population was smaller than the enrolled group, or provide a participant flow accounting for those not included.

The primary outcome was assessed at week 2 of each intervention. The record also lists PVT reaction time at week 1, PVT lapses, Epworth Sleepiness Scale, FOSQ, SF-36 Vitality Subscale, and PSQI as secondary outcomes. Numeric secondary results are posted for PVT reaction time at week 1, PVT number of lapses, and the Epworth Sleepiness Scale. Numeric results for FOSQ, the SF-36 Vitality Subscale, and PSQI are not reported in the registry record.

The duration and details of any washout between treatment periods, the method used to account for sequence or period effects, and the original sample-size justification are not reported in the registry record. The registry lists the study as completed. Its stated analysis population and posted summaries should therefore be distinguished from the full enrollment count.

4. Participant Flow and Accounting

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

Before assignment: All subjects underwent screening laboratories after enrollment but before beginning medication. In the case of abnormal laboratory results (n = 2), subjects did not begin treatment with either study drug (clarithromycin or placebo). One patient dropped out after consent but before randomization (because of scheduling conflict).

Period 1 (Weeks 1 & 2)

Washout (Week 3)

Period 2 (Weeks 4 & 5)

Analysis population for the primary outcome, as defined in the registry: Analysis was performed on all subjects who took both study drugs (i.e., clarithromycin and placebo)

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 Psychomotor Vigilance Task (PVT) Reaction Time, measured over week 2 of each intervention.

The primary endpoint was mean median reaction time on the Psychomotor Vigilance Task at the end of week 2 on each study drug. The unit was milliseconds. For each test, the PVT presents a series of stimuli during a 10 minute test and records reaction times. Each subject had two PVT tests at each visit; the two median reaction-time values were averaged, and the outcome summarized the mean across participants for each condition.

Lower reaction-time values represent faster responses and greater vigilance on this task. The PVT is used as an objective performance measure relevant to alertness and sustained attention. It does not capture every dimension of hypersomnia, and the posted result should be interpreted as a comparison of this specific task measure rather than as a comprehensive assessment of symptoms or functioning.

The registry reports a mean of 279.1 msec with standard deviation 77.3 for clarithromycin and a mean of 311.6 msec with standard deviation 114.1 for placebo. These condition summaries describe the measured endpoint; by themselves, they do not show how precisely the treatment contrast is estimated. That precision is better assessed using the contrast interval and the study's analysis information.

7. Results Posted in the Registry

• Clarithromycin: mean 279.10 versus 311.60 on control; difference -32.50 (95% CI -92.90 to 27.90), standardized effect d = -0.33; z-test p = 0.292.
• Baseline: mean 333.80 versus 311.60 on control; difference 22.20 (95% CI -114.95 to 159.35), standardized effect d = 0.10; z-test p = 0.751.

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.

PVT Median Reaction Time at Week 1

• 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:
  • Clarithromycin: mean 285.40 versus 308.40 on control; difference -23.00 (95% CI -84.40 to 38.40), standardized effect d = -0.23; z-test p = 0.463.
  • Baseline: mean 333.80 versus 308.40 on control; difference 25.40 (95% CI -112.81 to 163.61), standardized effect d = 0.11; z-test p = 0.719.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Clarithromycin 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 Baseline and the control. The interval gives the range of effects that remain compatible with the data.

PVT Number of Lapses

• 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:
  • Clarithromycin: mean 5.70 versus 10.30 on control; difference -4.60 (95% CI -14.18 to 4.98), standardized effect d = -0.30; z-test p = 0.346.
  • Baseline: mean 6.50 versus 10.30 on control; difference -3.80 (95% CI -14.85 to 7.25), standardized effect d = -0.21; z-test p = 0.500.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Clarithromycin 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 Baseline and the control. The interval gives the range of effects that remain compatible with the data.

Epworth Sleepiness Scale

• 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:
  • Clarithromycin: mean 10.10 versus 14.10 on control; difference -4.00 (95% CI -6.87 to -1.13), standardized effect d = -0.86; z-test p = 0.006.
  • Baseline: mean 15.00 versus 14.10 on control; difference 0.90 (95% CI -1.01 to 2.81), standardized effect d = 0.29; z-test p = 0.356.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Clarithromycin than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Baseline and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes cover task performance, reported sleepiness, and broader self-reported functioning or health measures. Numeric results are posted for three secondary measures: PVT reaction time at week 1, PVT number of lapses, and the Epworth Sleepiness Scale. The registry lists FOSQ, the SF-36 Vitality Subscale, and PSQI as additional secondary outcomes, but numeric results for those measures are not reported in the registry record.

Across the secondary outcomes with posted numbers, the pattern is not uniform across measures. The week 1 reaction-time and lapse comparisons do not provide the same statistical signal as the sleepiness-scale comparison. This matters when relating them to the primary endpoint: secondary measures can add context about different dimensions of performance and symptoms, but they do not replace the prespecified primary question. In particular, a pattern on a self-reported scale is not the same as a result on the objective vigilance task.

The registry reports ANOVA results across clarithromycin, placebo, and baseline for the secondary outcomes with numeric results. Those analyses are separate from the unadjusted clarithromycin-versus-placebo recalculations, and the registry record does not give details of an adjustment for examining multiple outcomes. When many measures or contrasts are examined, the chance of seeing an apparently notable result by chance can increase. Consequently, unadjusted secondary findings are best treated as exploratory context rather than definitive confirmation of the primary result.

The secondary results do not erase the uncertainty in the primary confidence interval. Nor should the primary result be taken to establish that all other symptom or functioning measures behave the same way. The record's incomplete numeric posting across the listed secondary outcomes further limits an overall account of how broad the results were.

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

• PVT Median Reaction Time at Week 1
• PVT Number of Lapses
• Epworth Sleepiness Scale
• FOSQ
• SF-36, Vitality Subscale
• PSQI

9. Statistical Interpretation

10. Statistical Methods Explained

The registry reports an ANOVA across clarithromycin, placebo, and baseline for the primary outcome. It gives a 95% confidence level and p = 0.47, but does not report the ANOVA's parameter estimate, confidence limits, or further details of the model. The record therefore does not identify all assumptions or adjustments used in the sponsor's analysis. The separate recalculated contrasts are simple, unadjusted comparisons derived from the posted summary statistics; they are not replacements for the sponsor's analysis.

What does a mean difference express?

A mean difference is the average value in one condition minus the average value in another. For the primary contrast, the order is clarithromycin minus placebo, so a negative estimate corresponds to a lower mean reaction time during clarithromycin. Given the endpoint's definition, a lower reaction time corresponds to faster responses on the PVT. The contrast is in the endpoint's original unit, milliseconds, which makes its direction and scale interpretable alongside the condition means.

General statistical explanation: a mean difference summarizes a contrast between group or condition averages. It does not describe every participant's response. Variation among participants and the analysis design affect the uncertainty around that average contrast.

Why distinguish the reported analysis from the recalculation?

The trial used a crossover design, in which participants received both study drugs in different sequences. The primary analysis population was described as all subjects who took both drugs. The recalculated contrast uses condition-level means and standard deviations and is explicitly unadjusted. It does not use participant-level paired observations or account for the ordering of each person's measurements. That distinction matters because repeated measurements from the same person are related, and a crossover analysis can use that within-person structure. The registry record does not provide enough detail to reconstruct the sponsor's full model or its handling of within-person, sequence, or period effects.

The sponsor's ANOVA includes three conditions, including baseline, while the primary recalculation contrasts clarithromycin with placebo. Those methods address related but nonidentical questions. Their p-values should not be read as competing estimates from the same model. The primary recalculation is useful as a transparent summary-statistic contrast, while the sponsor's posted ANOVA is the reported trial analysis.

How should p-values be read?

General statistical explanation: a p-value describes how unusual data at least as incompatible with a specified null model would be if that model were true and the model assumptions held. It is not the probability that the null hypothesis is true, nor does it measure the size or clinical importance of an effect. A p-value also does not convey the full range of effects compatible with the data; a confidence interval is more informative for that purpose.

The unadjusted p-value for the primary recalculation is 0.292. The sponsor's ANOVA p-value is 0.47. Neither number alone establishes the size or practical importance of a treatment difference. The registry record does not report a multiplicity adjustment for the family of outcomes and comparisons, so the secondary p-values should be treated as unadjusted unless otherwise stated in the record.

Why can variability matter?

General statistical explanation: standard deviation describes the spread of participant measurements around a mean. Greater spread can make an average contrast less precise, especially when the analyzed group is limited. The primary standard deviations were 77.3 for clarithromycin and 114.1 for placebo; the baseline standard deviation was 291.4. These summaries indicate differing amounts of observed variability across conditions. A standard deviation is not the same as a standard error or a confidence interval: it describes participant-level spread, whereas the latter quantities address uncertainty in an estimated mean or contrast.

General statistical explanation: over-dispersion refers to variability greater than a model expects. It can make standard errors too small and inference too confident if the model does not accommodate the extra variation. The registry record does not identify an over-dispersion model for these continuous outcomes, and the posted summary statistics alone do not establish that over-dispersion was present. For these results, the key practical points are the observed spread and the width of the contrast interval.

What can the planning illustrations tell readers?

The planning figures use the observed effect as a reference and show hypothetical participant counts under stated assumptions. They are not evidence that the original trial was designed with those counts, and they do not recover the original protocol's sample-size calculation. The original design assumptions are not reported in the registry record. The illustrations also do not transform the observed result into evidence of a treatment effect: their purpose is to show how sample-size requirements change under particular hypothetical effect sizes and power targets.

General statistical explanation: power is the probability, under a specified alternative and model, of rejecting a null hypothesis using a defined test. A planning calculation depends on assumptions about the effect to detect, variability, allocation, and significance level. If those assumptions change, the resulting participant requirement changes. A planning estimate is not a measure of how likely the observed trial result is to be true.

11. Confidence Intervals and Precision

The primary recalculated mean difference was -32.5 msec, with a 95% confidence interval from -92.9 to 27.9 msec. The interval spans zero. In practical terms, the posted data do not isolate a single direction for the underlying mean contrast: values on either side of zero remain compatible with the interval. The point estimate is negative, but the interval also allows a positive difference.

General statistical explanation: a confidence interval is a range generated by a statistical procedure intended to cover the underlying parameter at its stated rate over repeated use of the same procedure, when the model assumptions hold. It is not a range containing a fixed proportion of individual participant values, and it is not a statement that there is a 95% probability that this particular interval contains the true effect. Its width conveys precision: a narrower interval is more precise than a wider one, all else equal.

The interval is wide enough to include both a substantial negative estimate and a positive estimate. This means the primary summary is not precise enough to determine the direction of the underlying contrast from the interval alone. Precision should be considered alongside the endpoint's scale and the condition means, rather than inferred from the point estimate or p-value by itself.

The posted summaries include 20 participants per condition, and the primary analysis population was subjects who took both drugs. Because the trial is a crossover, participant-level pairing could affect the uncertainty of the treatment contrast. The recalculated interval is an unadjusted comparison from summary statistics, not a reconstructed paired crossover interval. The registry record does not report the sponsor's confidence interval for the ANOVA or enough model detail to derive it from the record.

For the baseline comparison, the recalculated difference was 22.2 msec and the 95% confidence interval ran from -115.0 to 159.4 msec. That interval also includes zero and is broad. The baseline contrast is not the primary clarithromycin-versus-placebo comparison, but it illustrates the uncertainty around the baseline summary contrast.

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 illustrations report participants per arm for these continuous outcomes; they are not total event counts. Their assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each row uses a stated fraction of the observed effect as the effect to detect. The original trial's design assumptions and its own sample-size justification are not reported in the registry record.

The 80% power column gives the hypothetical number of participants per arm for a design with an 80% chance of detecting the stated effect under the planning assumptions, if that effect and model assumptions were correct. The 90% power column gives the corresponding per-arm count for a 90% chance. These are prospective planning quantities: they depend on a chosen effect size and analysis assumptions, not just on the data already observed.

Rows planning for 75% or 50% of the observed effect represent smaller effects than a row planning for 100% of the observed effect. Smaller effects are harder to distinguish from random variation, so they require more participants under otherwise identical assumptions. The counts should be read as illustrations of that relationship, not as a recommended design or a claim about what the completed trial would have found at those sizes.

This is not observed power. It does not tell how likely the completed study was to detect an effect after the outcome was known, and it should not be used to reinterpret a nonsignificant result as proof of absence. The estimates also do not account for crossover-specific features in the registry record; the stated planning assumptions use equal allocation between two arms and a normal approximation.

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 = -32.500; pooled standard deviation σ = 97.453.
2. n = 2 × (1.96 + 0.842)² × 97.453² / -32.500² = 141.1, rounded up to 142 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 <- -32.5                      # observed difference in means
sigma <- 97.4528090924012                     # 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(1146600)
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 = 142 (80% power), 189 (90% power)
 75% of observed effect: n per arm = 251 (80% power), 336 (90% power)
 50% of observed effect: n per arm = 565 (80% power), 756 (90% power)
power.t.test: 142.1 
Simulated power at n = 142 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. Analyses Reported by the Sponsor

The sponsor's reported primary analysis is an ANOVA across clarithromycin, placebo, and baseline, with p = 0.47. It is the trial's own posted inferential analysis. The recalculated primary comparison instead contrasts clarithromycin with placebo using the posted condition summaries. That unadjusted mean difference is -32.5 msec, with a 95% confidence interval from -92.9 to 27.9 msec and p = 0.292.

The distinction is substantive: the ANOVA includes three conditions, while the recalculation addresses the two treatment conditions alone. The recalculation also uses summary statistics rather than participant-level paired data from the crossover. Its p-value and interval therefore need not match the sponsor's result. The registry record does not report enough detail about the sponsor's model to reproduce its analysis or make the two approaches identical.

The condition means are numerically lower on clarithromycin than placebo, but the recalculated interval includes zero. The sponsor's p-value is also not evidence of a precise treatment contrast by itself. Read the reported analysis and the recalculation as different summaries with different analytical scope, rather than treating one as a correction of the other. The registry data indicate no discrepancy flag; the recalculation remains a supplementary unadjusted analysis, not the sponsor's model.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists several secondary outcomes in addition to the primary PVT endpoint, and it reports analyses for more than one condition contrast. The record does not report whether the investigators prespecified a hierarchy among these tests, adjusted for multiple comparisons, or used another strategy to control the family-wise chance of false-positive findings. Without that information, the posted secondary p-values should be read as unadjusted evidence for their individual analyses, not as results protected against the full set of outcome and comparison choices.

General statistical explanation: multiplicity arises when several hypotheses are tested. Even if each test is conducted at a chosen error rate, the chance of at least one false-positive finding across a set of tests can rise as the number of tests grows. Adjustment methods or a prespecified testing hierarchy can address this issue, but the registry record does not state that one was used. This uncertainty is a reason to give secondary results less weight than the primary endpoint, not a reason to discard them entirely.

The primary outcome population is described as all subjects who took both study drugs. The registry posts 20 participants for each primary condition summary, while enrollment was 26. It does not report the reasons participants were not represented in the primary analysis, how missing outcome measurements were handled, whether any imputation was performed, or whether a sensitivity analysis assessed the effect of missing data. Thus, the posted primary result pertains to the stated analysis population, and the record does not establish how it would compare with results from all enrolled participants.

Because the design is crossover, it is also relevant whether participants completed both treatment periods and whether sequence, period, or carryover effects were considered. The registry describes the treatment sequences and the population who took both drugs, but detailed crossover-model specifications, washout information, and handling of incomplete sequences are not reported in the registry record. These omissions make it difficult to judge how fully the sponsor's analysis used the within-person design.

The registry's reported primary ANOVA includes clarithromycin, placebo, and baseline, but detailed model terms and analysis diagnostics are not reported. These gaps limit independent reproduction and a complete assessment of missingness, multiplicity, and model assumptions.

16. Safety Results

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

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 5% reporting threshold.

Most frequent non-serious adverse event terms

The registry reports zero serious adverse events among 22 participants at risk in the clarithromycin group and zero among 20 participants at risk in the placebo group. These counts describe the serious adverse-event totals posted for the study; they do not establish that serious events could not occur, particularly given the size and duration of the analyzed exposure described in the record. The registry's deaths field does not contain a count, so deaths are not reported in the registry record.

Other adverse events were reported for 21 of 22 participants at risk with clarithromycin and 15 of 20 at risk with placebo. These are participant counts, not a measure of event severity or a comparison adjusted for exposure time. The record does not provide the specific non-serious adverse-event terms in the material used for this summary, so the counts alone cannot describe their nature, duration, or clinical importance.

In a crossover trial, participants may receive both conditions at different times. The posted safety groups have different numbers at risk, and the registry record does not explain the exposure accounting or provide a paired safety analysis. The counts should therefore be read descriptively, not as a definitive comparative estimate of risk. No medical advice or conclusion about safety follows from these figures alone.

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

The posted primary condition means show lower PVT reaction time during clarithromycin than during placebo, and the endpoint definition associates lower values with faster responses. The unadjusted recalculated contrast is negative, but its 95% confidence interval includes zero and extends in both directions. The registry's sponsor-reported ANOVA gives p = 0.47 across clarithromycin, placebo, and baseline. Together, these results describe an observed numerical pattern with substantial uncertainty; they do not establish a precise treatment difference.

The result applies to the PVT measure at the end of week 2 of each intervention in the primary analysis population, described as subjects who took both study drugs. It does not by itself answer whether participants experienced changes in all aspects of sleepiness, functioning, or quality of life. Nor does the presence of a secondary result on a different measure make the primary contrast more precise. Each measure addresses a different question and carries its own uncertainty and multiplicity context.

The trial was randomized, masked, and crossover, but important details for interpreting the reported model—such as treatment-period handling and any washout—are not reported in the registry record. The unadjusted recalculation also does not use paired participant-level data. These considerations constrain what can be inferred from the condition summaries.

The numbers should not be turned into a treatment recommendation. They do not establish that clarithromycin works or does not work, and they do not determine how a result would generalize beyond the analyzed participants or the measured timeframe. A broad confidence interval means the posted data leave uncertainty about the size and direction of the underlying contrast. The appropriate statistical reading is therefore bounded: note the observed mean pattern, recognize the interval's imprecision, and distinguish the sponsor's three-condition analysis from the supplementary two-condition recalculation.

18. Why This Trial Matters Statistically

This trial is statistically informative because its crossover design gives an opportunity to compare measurements from the same participant under clarithromycin and placebo. Such designs can, in principle, account for stable differences between participants and use within-person information. The registry identifies the two treatment sequences and states that the primary population consisted of subjects who took both drugs. However, the posted summary statistics do not allow readers to reconstruct a paired treatment analysis, and detailed model specifications are not reported.

The comparison also illustrates why direction, magnitude, and precision should be considered together. The clarithromycin mean is numerically lower on the PVT, which corresponds to faster reactions, but the recalculated confidence interval includes zero and the sponsor's posted ANOVA does not provide a treatment-specific estimate or interval. A point estimate can be visually or verbally compelling while remaining uncertain; the interval makes that uncertainty explicit.

The trial also places an objective vigilance measure alongside symptom and functioning measures. Those outcomes represent distinct constructs and can show different patterns without being logically inconsistent. The missing numeric results for some listed secondary outcomes and the unreported multiplicity approach limit a complete synthesis of those domains.

Finally, the difference between enrollment and the primary analysis population highlights the importance of knowing who contributes to a result and how missing observations are handled. The registry record does not explain the reduction or the missing-data strategy. These features make this trial useful for understanding how study design, analysis population, estimand, and precision shape interpretation—not as a stand-alone resolution of the clinical question.

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 primary analysis population was limited to subjects who took both study drugs, and the posted summaries include 20 participants per condition despite enrollment of 26. The registry record does not report why the analysis population was smaller, whether any participants lacked outcome measurements, or how missing data were handled. That prevents assessment of whether the analyzed participants differ from those not represented in the primary summaries.

The crossover structure is important to interpreting the treatment comparison, but the simple recalculation uses condition summaries and does not use participant-level paired data. The sponsor's reported ANOVA includes baseline, but the registry does not provide its model terms, estimate, or confidence interval. Treatment sequence and period effects, washout details, and possible carryover handling are not reported in the registry record. These gaps limit independent evaluation of how the design was reflected in the inferential analysis.

The primary confidence interval is broad and includes zero, so the magnitude and direction of the underlying contrast remain uncertain. The posted primary endpoint is a specific PVT performance measure at week 2, not a comprehensive measure of hypersomnia or longer-term functioning. The record does not report a minimal clinically important difference for this endpoint, so statistical summaries cannot be translated into a threshold for practical importance using the registry information alone.

Several secondary outcomes are listed, but numeric results are not reported in the registry record for FOSQ, the SF-36 Vitality Subscale, and PSQI. The record also does not state whether multiplicity was addressed. Adverse-event counts are descriptive, and deaths are not reported in the registry record. These limitations narrow the conclusions that can be drawn from the posted outcomes.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Clarithromycin for the Treatment of Hypersomnia — NCT01146600.
• Registry record last updated 2017-11-06; status last verified 2017-10.
• Results first posted 2014-06-12.
• 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

NCT01146600 is a completed phase 2 randomized, quadruple-masked crossover study titled “Clarithromycin for the Treatment of Hypersomnia.” The registry lists an enrollment of 26 and conditions including hypersomnia, idiopathic hypersomnia, and narcolepsy. Participants received clarithromycin and placebo in opposite treatment sequences.

The primary endpoint was mean median PVT reaction time at week 2 of each intervention. The primary analysis population was subjects who took both study drugs, with 20 participants represented in each posted condition summary. The sponsor reported an ANOVA across clarithromycin, placebo, and baseline with p = 0.47. The unadjusted recalculated clarithromycin-versus-placebo mean difference was -32.5 msec, with a 95% confidence interval from -92.9 to 27.9 msec.

The registry lists six secondary outcomes, with numeric results posted for three. Serious adverse events were reported for zero participants in each safety group; other adverse events were reported for 21 of 22 at risk with clarithromycin and 15 of 20 at risk with placebo. Important details about missing data, multiplicity, and the crossover analysis are not reported in the registry record.