Ocular Comfort and OCT Observation of Post Lens Clearance and Ocular Tissue Compression: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Ocular Comfort and OCT Observation of Post Lens Clearance and Ocular Tissue Compression (NCT01423773), a randomized na study. The primary outcome is Final Comfort.

2. Clinical Question

The registry describes the study purpose as comparing the fit and comfort of two types of contact lenses. The posted primary outcome is Final Comfort, measured in units on a scale and summarized as a mean with a standard deviation. The comparison is between the test lens and control lens, not between separate groups assigned to use only one lens throughout the study: the record describes a crossover in which participants wore both products in different orders.

The key statistical question is whether the observed average rating for the test product differs from the average rating for the control product at the specified assessment time. A difference in averages describes the group-level contrast; it does not show how every participant rated either lens. The registry record does not report a threshold defining a meaningful comfort difference, so the statistical comparison cannot establish whether a particular score difference would matter to participants.

3. Trial Design

The registry classifies this as a randomized, single-masked crossover study. Enrollment was 20, and the study status is completed. The record lists the start as 2011-08 and primary completion as 2011-12. The sponsor is CIBA VISION. The phase is listed as NA.

Two sequences are described. In one sequence, participants wore the Lotrafilcon A test contact lens first and the Lotrafilcon A control contact lens second; in the other, the order was reversed. Each product was worn bilaterally for two days, with 20 minutes of wear on Day 1 and 10 hours on Day 2. The primary comfort assessment was specified for Day 2, Hour 10. The record does not describe a washout period or other details about the transition between products.

In a crossover design, each participant receives or uses the conditions in sequence. General statistical rationale: comparing conditions within the same participant can account for stable differences between participants, while the sequence order can matter if there are period or carryover effects. The registry identifies randomization and the crossover model, but the method used to generate the sequence, the allocation ratio, and any handling of period, sequence, or carryover effects are not reported in the registry record.

Single masking is recorded, but the identity of the masked party is not reported in the registry record. The registry lists an Ultra-High Resolution Optical Coherence Tomographer (OCT) as an intervention device, while the posted primary endpoint is participant-rated comfort. How OCT observations were collected or analyzed is not reported in the registry record. No additional outcome analyses are listed.

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: This reporting group includes all enrolled participants.

Period One, 2 Days

Period 2, 2 Days

Analysis population for the primary outcome, as defined in the registry: All enrolled participants

5. Baseline Characteristics

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

6. Primary Endpoint

The registry lists the primary outcome as Final Comfort, measured over Day 2, Hour 10.

The primary endpoint, Final Comfort, is the participant’s rating of lens comfort at Day 2, Hour 10. It is measured on a Visual Analog Scale from 0 to 100. The registry defines 0 as “Extremely Uncomfortable” (“My eyes are in pain. I cannot tolerate my lenses”) and 100 as “Extremely Comfortable” (“My eyes feel GREAT, better than normal. I cannot feel my lenses”). The outcome is a continuous measure, summarized by a mean and standard deviation.

A participant-reported scale is used to quantify an experience that is directly perceived by the wearer. A mean gives a concise description of the group’s average rating, while the standard deviation describes how ratings vary around that average. Neither statistic captures the full distribution of individual responses, and the group mean does not imply that all participants felt similarly.

The specified assessment time makes the endpoint a comparison at the end of the stated Day 2 wear period, rather than a summary across all wear times. The registry lists the outcome population as all enrolled participants. It does not report a meaningful-difference threshold, a rule for combining repeated ratings, or details about handling missing ratings. Thus, the endpoint supports description of the posted comfort scores and their comparison, but by itself does not establish how important a score difference would be to participants.

7. Results Posted in the Registry

• Lotrafilcon A Test: mean 87.60 versus 87.90 on control; difference -0.30 (95% CI -7.00 to 6.40), standardized effect d = -0.03; z-test p = 0.930.

8. Statistical Interpretation

9. Statistical Methods Explained

What does a mean difference describe?

For a continuous outcome, a mean is the arithmetic average of participants’ recorded values. The registry reports mean comfort scores for the test and control lenses and gives their comparison as a mean difference. The direction depends on the stated contrast: the estimate is test minus control, so a negative value means the test-lens sample mean is lower. Here, the means are 87.6 and 87.9, and the recorded difference is -0.3.

A mean difference is expressed in the outcome’s original units. In this study those are units on a 0-to-100 comfort scale, rather than a relative percentage or a ratio. It summarizes a difference between group averages and does not describe the full range of participant-level experiences. Two sets of scores can have similar averages while still differing in their distributions or in how ratings pair within participants.

What does the standard deviation add?

The standard deviation describes the spread of observations around a mean. The registry records standard deviations of 10.5 for the test lens and 11.1 for the control lens. These values provide context for the means: individual ratings varied, rather than all participants necessarily reporting the group average. A standard deviation is not the uncertainty of the mean difference, and it is not a confidence interval. The comparison’s uncertainty is represented separately by its confidence interval.

General explanation: the standard error measures how much an estimate would tend to vary across repeated samples under a statistical model. It depends on the observed variability and the amount of information in the data. The registry records standard errors of 2.348 for the test mean and 2.482 for the control mean. The record does not state the full analysis model from which these were obtained. In particular, it does not report whether the uncertainty calculation used the crossover pairing.

How should the p-value be read?

The posted unadjusted p-value is 0.93. General explanation: a p-value measures how compatible the observed data, or data more extreme under a specified test statistic, are with a null hypothesis under the assumptions of that test. A large p-value is not proof of no effect, does not assign a probability to the null hypothesis, and does not show that the two products are equivalent. Interpretation depends on the design, analysis method, and assumptions.

The registry does not report the test procedure, model specification, or a protocol-defined statistical analysis plan. The word “unadjusted” indicates that the listed p-value is not adjusted for multiplicity, but the record does not identify a family of tests or describe any adjustment strategy. The listed analysis count is zero, so the record does not give further outcome-analysis details. It is therefore not possible to verify from the registry record how the p-value incorporated the randomized crossover structure.

Why does a crossover structure matter?

General explanation: in a crossover study, the same participant experiences multiple conditions. A within-participant comparison can remove some variability caused by stable characteristics that differ between people. However, observations from the same participant are related, not independent. A suitable analysis generally needs to account for that relationship. Period effects, order effects, or effects that persist after a participant changes conditions can also influence a crossover comparison.

The registry describes randomized sequences and the order in which the test and control lenses were worn. It does not report a washout, the statistical treatment of sequence or period, or an assessment of carryover. The summary comparison includes a pooled standard deviation of 10.8 and a standardized difference of -0.028, but the record does not explain how those quantities were used or whether they reflect a paired analysis. They should be treated as descriptive comparison statistics rather than proof that a particular crossover model was fitted.

What assumptions matter?

General explanation: statistical comparisons rely on assumptions about how the data were generated and how the analysis represents their variability. For continuous outcomes, assumptions may concern the outcome distribution, the independence or dependence structure, and the appropriateness of the model. In a crossover study, accounting for repeated observations within a person is especially relevant. Over-dispersion, when present, means the data vary more than a model expects; if not accommodated, uncertainty may be understated. The registry record does not report a distributional assessment, an over-dispersion assessment, or a model specification, so none can be confirmed for this analysis.

Random allocation is recorded, but randomization alone does not establish that every analysis assumption was met. The record also does not provide participant-level observations, the number of missing comfort ratings, or the handling of any missing values. The published means, standard deviations, confidence interval, and p-value are therefore the available statistical summaries, not a complete account of the analysis choices.

10. Confidence Intervals and Precision

The comparison’s confidence interval runs from -6.996 to 6.396 for the test-minus-control mean difference. A confidence interval expresses uncertainty around an estimate under the assumptions of the method used to calculate it. It shows a range of values compatible with the observed data and that method; it does not guarantee that the true difference lies in the interval, nor does it describe the range of individual participant ratings.

The interval includes zero, the value corresponding to no mean difference, and extends to values on both sides of zero. Thus, the posted estimate is not precise enough to establish the direction of a difference. Its width also matters: the data remain compatible with more than a negligible difference in either direction, depending on what magnitude would be meaningful. The registry does not report a comfort-score threshold for interpreting clinical or practical importance, so the interval cannot be classified against such a threshold.

The confidence level and calculation method for this interval are not reported in the registry record. The crossover structure makes the dependence between a participant’s ratings relevant, but the record does not specify whether that dependence was incorporated. The individual arm means are accompanied by standard deviations, not arm-specific confidence intervals. The comparison interval should be interpreted as uncertainty around the reported mean contrast, with the analysis details unavailable for further assessment.

Precision is distinct from whether a p-value crosses a decision threshold. The unadjusted p-value is 0.93, but neither that value nor the interval proves equality. A precise equivalence conclusion would require a prespecified equivalence margin and an analysis designed to evaluate it; such a margin and plan are not reported in the registry record.

11. Planning a Similar Trial: Sample Size

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

The planning figures are participants per arm for 80% power and participants per arm for 90% power; they are not total event counts. They are planning illustrations based on the observed effect, not the trial’s original design calculation. The stated 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 set to the stated fraction of the observed effect.

In plain language, the 80% power column gives the number of participants per arm that the planning calculation estimates would be needed for an 80% chance of detecting the chosen effect under those assumptions, if that effect and the model assumptions were correct. The 90% power column gives the corresponding planning number for a 90% chance. These are prospective illustrations; they are not observed power.

The display considers planning for 100% of the observed effect, 75% of the observed effect, and 50% of the observed effect. The corresponding figures are 20,360 and 27,257 participants per arm for 80% and 90% power when planning for 100% of the observed effect; 36,196 and 48,456 when planning for 75% of the observed effect; and 81,440 and 109,026 when planning for 50% of the observed effect. Smaller effects require more participants to detect under the same assumptions, which is why the planning figures rise as the target effect becomes smaller.

These very large planning estimates reflect the small observed mean difference used as the planning basis; they are not a statement about the number enrolled in the completed trial. The registry does not report the original sample-size justification or its assumptions, so the planning illustration should not be mistaken for the study’s protocol target.

12. 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 = -0.300; pooled standard deviation σ = 10.804.
2. n = 2 × (1.96 + 0.842)² × 10.804² / -0.300² = 20,360.0, rounded up to 20,360 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 <- -0.300000000000011                      # observed difference in means
sigma <- 10.8041658632215                     # 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(1423773)
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 = 20,360 (80% power), 27,257 (90% power)
 75% of observed effect: n per arm = 36,196 (80% power), 48,456 (90% power)
 50% of observed effect: n per arm = 81,440 (80% power), 109,026 (90% power)
power.t.test: 20361 
Simulated power at n = 20,360 per arm: 0.802 (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.

13. Multiplicity, Missing Data and Analysis Populations

The registry lists one outcome measure and no secondary outcomes. It records zero outcome analyses. The primary endpoint is Final Comfort at Day 2, Hour 10; no other posted endpoint results are described in the record. The comparison p-value is identified as unadjusted. The registry does not report a multiplicity plan, a hierarchy of outcomes, or whether any additional analyses were conducted outside the posted record.

General explanation: multiplicity arises when several hypotheses or outcomes are tested. Repeated testing can increase the chance of at least one apparently unusual result, so a prespecified strategy may control that risk. Because the record does not describe a set of planned tests or an adjustment method, it is not possible to determine whether multiplicity was relevant to the sponsor’s complete analysis. The unadjusted p-value should be read as unadjusted, not as evidence that all possible testing has been accounted for.

The outcome population is listed as all enrolled participants, and enrollment is 20. The arm summaries each show 20 participants. However, the record does not report a missing-data count, whether all enrolled participants contributed a usable endpoint value, or how missing values would be handled. It also does not specify an intention-to-treat, per-protocol, or other analysis population definition. The listed population label alone does not resolve those questions.

The registry identifies a randomized crossover design but does not report whether the analysis followed assigned sequence, how participants who did not complete both periods would be handled, or whether any exclusions were made. No imputation method or sensitivity analysis is reported in the registry record. These absences limit assessment of how the result might depend on missing outcomes or analysis-population choices; they do not establish that data were missing or that exclusions occurred.

14. 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 0% reporting threshold.

For both the Lotrafilcon A test and control groups, the registry records 20 participants at risk for serious adverse events and 0 participants affected. It also records 20 participants at risk for other adverse events and 0 participants affected. No serious adverse event terms are listed. The deaths field is not reported in the registry record.

These figures are counts of participants affected in the registry’s adverse-event summaries. They are not a complete description of event severity, timing, duration, or causality, and they do not establish that no event of any kind occurred beyond what was posted. The registry record does not provide further safety definitions, event narratives, or details about how adverse events were collected.

Because the study is a crossover, the safety group labels should be read as recorded rather than interpreted as independent parallel groups. The registry does not explain whether adverse events were attributed to a particular wear period or how participants who wore both products were handled in these summaries. The posted counts describe the registry record and do not support broader conclusions about safety.

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

The posted results describe similar group-average comfort ratings at the specified assessment: 87.6 for the test lens and 87.9 for the control lens. The recorded mean difference is -0.3 units, with a confidence interval from -6.996 to 6.396 and an unadjusted p-value of 0.93. These statistics show that the estimated average contrast is close to zero in this sample, while the interval leaves uncertainty about the direction and magnitude of the underlying contrast.

This is not a demonstration that the products are equivalent. Equivalence requires a prespecified margin defining differences small enough to count as practically equivalent, along with an analysis designed to evaluate that question. The registry does not report such a margin. Nor does a non-small p-value show that there is no difference; it indicates that the observed contrast does not provide strong evidence against the null under the test assumptions, which are not detailed in the record.

The result concerns participant-reported comfort at Day 2, Hour 10 under the described wear schedule. It does not establish how participants rated fit, comfort at other times, OCT observations, or any outcome not posted. Although the registry’s purpose statement includes fit and comfort, the posted primary endpoint is Final Comfort. The registry does not report a relationship between comfort ratings and OCT findings.

Group averages cannot reveal each participant’s experience or preference. The reported summaries do not show whether most participants gave similar ratings for both lenses, whether some participants preferred one lens strongly, or whether changes differed by sequence. The record also lacks a stated threshold for a meaningful score difference, so statistical estimates cannot be translated into a claim about practical importance.

The findings should be understood within the study’s recorded sample and design. Enrollment was 20, and the record does not describe participant characteristics or provide detailed analysis methods. It does not justify medical advice, claims about all contact lens wearers, or conclusions about outcomes beyond the posted comfort measure.

16. Why This Trial Matters Statistically

This study is statistically useful as an example of why a near-zero point estimate needs to be read alongside its uncertainty. The test and control mean ratings are close, but the confidence interval spans values favoring either product. Reporting the point estimate alone could make the comparison sound more conclusive than the interval supports. Considering both gives a clearer account of what the data can and cannot distinguish.

The crossover structure also makes the analysis question important. Each participant wore both products in a randomized order, so the observations are related within a participant. General statistical principle: a method that uses this pairing can represent a different source of variation from a method that treats observations as independent. The registry does not state which method generated the posted comparison, illustrating why design labels and analysis details both matter when assessing precision.

The study also distinguishes statistical evidence from practical importance. A p-value does not determine whether a score difference matters to lens wearers, and the record does not supply a meaningful-difference threshold. Without such a threshold, neither a near-zero estimate nor a confidence interval can settle a practical equivalence question.

Finally, sample-size planning based on a very small observed effect produces large illustrative participant counts under the stated assumptions. Those figures can help readers understand the relationship between target effect size, power, and sample size, but they are not the trial’s original justification. The registry’s lack of a reported protocol calculation is a reminder to separate retrospective planning illustrations from the design decisions made before a study began.

17. Limitations

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

The registry provides limited detail for assessing how the randomized crossover comparison was analyzed. It does not report the statistical model, whether participant-level pairing was incorporated, or how period, sequence, or possible carryover effects were handled. A washout period is not described. These omissions prevent a full evaluation of whether the uncertainty estimates reflect the design appropriately.

The endpoint summaries do not include participant-level ratings or a distribution of changes within participants. The record does not report missing outcome counts, the handling of missing data, exclusions, or a more detailed analysis-population definition. Although the endpoint population is labeled all enrolled participants and each arm summary records 20 participants, those summaries do not resolve whether all enrolled participants had complete data for every relevant assessment.

The registry does not report a clinically or practically meaningful difference threshold, a confidence level for the interval, the analysis plan, the original sample-size justification, or the identity of the masked party. It also does not provide detailed eligibility criteria or participant characteristics. These omissions constrain interpretation of precision, generalizability, and the intended statistical decision rule.

The posted primary result concerns comfort at Day 2, Hour 10. The registry does not post secondary outcome results, and although an OCT device is listed, the record does not describe OCT findings or their analysis. The safety summary is limited to affected-participant counts and does not provide event narratives or deaths information. These limitations define what can be concluded from the registry record; they do not establish that unreported procedures or analyses did not occur.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Ocular Comfort and OCT Observation of Post Lens Clearance and Ocular Tissue Compression — NCT01423773.
• Registry record last updated 2013-06-28; status last verified 2012-11.
• Results first posted 2012-12-21.
• 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.

21. Record Summary

NCT01423773 is a completed randomized, single-masked crossover study sponsored by CIBA VISION, with enrollment of 20. It compared the Lotrafilcon A test contact lens with the Lotrafilcon A control contact lens, worn bilaterally in randomized order. Each product was worn for 20 minutes on Day 1 and 10 hours on Day 2.

The primary endpoint was participant-rated Final Comfort at Day 2, Hour 10, on a Visual Analog Scale from 0 to 100. The recorded mean was 87.6 for the test lens and 87.9 for the control lens. The test-minus-control mean difference was -0.3, with a confidence interval from -6.996 to 6.396 and an unadjusted p-value of 0.93.

The registry records 0 participants affected by serious adverse events and 0 affected by other adverse events in each group. Detailed analysis methods, missing-data handling, the original sample-size rationale, and deaths information are not reported in the registry record.