Myopia Assessment of Two Manufacturing Processes: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Myopia Assessment of Two Manufacturing Processes (NCT04126057), a randomized na study. The primary outcome is Change in Axial Length Progression From Baseline.

2. Clinical Question

This is a question about the difference between the two manufacturing processes among participants with juvenile myopia. It is not a question about whether DOT spectacle lenses outperform a different intervention or about the effect of wearing spectacles compared with no spectacles. The registry record posts one primary outcome measure and no secondary posted outcome measures. It does not report further detail about eligibility, participant characteristics, or the endpoint analysis population, so the scope of the result cannot be refined using those details.

3. Trial Design

The registry identifies this as a randomized, controlled trial with a parallel model and no masking recorded in the design fields. It lists planned enrollment of 50 and a completed status. The registry dates are 2019-12-02 for the start and 2020-09-15 for primary completion. The phase field is NA. The sponsor is SightGlass Vision, Inc.

The comparison is between DOT spectacle lenses made using manufacturing method A and DOT spectacle lenses made using manufacturing method B. The arm descriptions specify single-vision, impact-resistant spectacles. The primary outcome timeframe is 6 months. The brief summary describes the study as multisite, subject- and observer-masked, and contralateral, while the design fields list parallel allocation and masking as none. These descriptions do not agree. The registry record does not clarify how the outcome groups correspond to the contralateral description or resolve the difference in masking and model descriptions.

The outcome results report 43 participants in each group. Those group figures do not match the planned enrollment figure, and the registry record does not explain the relationship between enrollment and the reported outcome counts. It does not report the number of sites, the reasons for any difference in counts, or the handling of participants who may not have contributed to the endpoint result.

Randomization can help make groups comparable on average, but interpretation also depends on how allocation, follow-up, measurement, and analysis were carried out. Details of those procedures beyond the registry descriptions are not reported in the registry record. In particular, the record does not include the allocation sequence method, any concealment procedure, or an analysis plan. These absences limit how fully the randomized comparison can be assessed from the posted record alone.

4. Participant Flow and Accounting

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

Overall Study

5. Baseline Characteristics

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

Population: This was a contralateral eye study of 50 participants in which both eyes were enrolled. In the analysis set, each group has 43 eyes with a total of 43 participants.

6. Primary Endpoint

The registry lists the primary outcome as Change in Axial Length Progression From Baseline, measured over 6 months.

The primary endpoint is change in axial length progression from baseline, measured in millimeters over 6 months. The registry describes the reported measure as a mean of a continuous outcome, with standard deviation as the measure of dispersion. Axial length progression is defined in the record as axial length elongation attributable to myopia. The comparison asks whether the mean change differed between DOT spectacle lenses manufactured by method A and those manufactured by method B.

Axial length is a physical measurement of the eye. In general, using a continuous measurement preserves information about the size and direction of change rather than reducing observations to categories such as improved or not improved. A mean describes the center of the observed group values, while a standard deviation describes how dispersed individual values are around that mean. These summaries answer different questions: a mean contrast concerns the average group difference, whereas the standard deviation describes participant-level variability.

The endpoint is used in this trial to quantify a change relevant to the stated study question, namely axial elongation attributed to myopia. The registry record does not report further measurement procedures, timing details beyond the 6-month timeframe, or the method used to attribute elongation to myopia. It also does not report a threshold for interpreting a change as important. Therefore, the posted endpoint supports description of the measured group averages and their statistical uncertainty, but not a broader conclusion about the clinical importance of a particular difference.

7. Results Posted in the Registry

• DOT Spectacle Lenses Using Test: mean 0.05 versus 0.05 on control; difference -0.00 (95% CI -0.06 to 0.06), standardized effect d = -0.01; z-test p = 0.972.

8. Statistical Interpretation

9. Statistical Methods Explained

The statistical result combines a summary of each group with an estimate of the contrast between them. For this continuous endpoint, the group summaries are means and standard deviations. The reported comparison is a mean difference, accompanied by a confidence interval and an unadjusted p-value. Each quantity answers a different statistical question: the means describe the groups, the difference quantifies the contrast, the interval describes uncertainty in that contrast, and the p-value summarizes compatibility with a specified null model.

What does a mean difference represent?

A mean is the arithmetic average of the observed measurements in a group. The reported test-group mean is 0.046 mm, and the control-group mean is 0.047 mm. The reported contrast is -0.001 mm, with the test group compared against the control group. A negative estimate means the test-group average is lower in the direction used for the comparison. The estimate is not an individual participant’s change; it is a group-level summary of the difference in averages.

A group mean can conceal variation among participants. The standard deviations are 0.139 mm in the test group and 0.128 mm in the control group. In general, standard deviation describes the spread of measurements around a group mean. It is not the same as the uncertainty in the mean or the uncertainty in the between-group difference. A confidence interval for a mean difference accounts for the precision of the estimated contrast, which depends on variability and the amount of information contributing to the comparison.

What does the confidence interval contribute?

A confidence interval gives a range of values compatible with the data under the interval’s statistical procedure. In general, a narrower interval indicates a more precise estimate, while a wider interval leaves more uncertainty about the size and direction of the difference. The reported interval includes zero. Zero represents no difference between the group means. Because the interval covers zero and values on either side, the results do not identify a clear direction of difference at the interval’s stated procedure. The registry record does not report the confidence level or the calculation method, so those details cannot be evaluated from the entry.

An interval is not a guarantee that the true effect lies within its endpoints, nor does it tell whether values within the interval would be clinically important. That judgment needs a relevant threshold, and no threshold is reported in the registry record. The interval should be interpreted as a measure of statistical uncertainty rather than as a direct measure of clinical value.

How should the p-value be read?

The unadjusted p-value is 0.972. In general, a p-value measures how compatible the observed data are with a null hypothesis under the assumptions of the statistical test. It is not the probability that the null hypothesis is true. A large p-value does not establish equality, equivalence, or absence of an effect. Here, it accompanies a mean difference close to zero and an interval that includes zero, but these pieces of evidence still do not establish that any underlying difference is exactly zero.

The registry record does not name the test or specify its assumptions. It does not state whether the comparison used a model accounting for paired or contralateral measurements, despite the brief summary’s description of a contralateral trial. Nor does it explain whether the p-value was calculated from an adjusted analysis. Consequently, the result can be described as the posted unadjusted comparison, but the specific analytical method cannot be reconstructed from the registry entry.

Why do variation and design details matter?

In general, variability affects precision: with more spread in measurements, a given group contrast is harder to estimate precisely unless additional information is available. The standard deviations describe spread in the posted groups, but no additional outcome-level data are reported. The registry record does not report how within-participant dependence, if relevant to the contralateral description, was handled. Treating measurements as independent when they are related can misstate uncertainty; accounting for dependence requires an analysis consistent with the actual design.

Likewise, randomization supports a comparative interpretation when assignment and analysis are implemented as intended, but it does not resolve missing-data concerns or inconsistencies in the record’s design descriptions. The listed parallel model and absence of masking in the design fields differ from the brief summary’s contralateral and masked description. The record does not provide enough detail to determine which description governed the analysis. This uncertainty is relevant to assessing whether the reported standard errors and interval properly reflect the design.

What is not available for review?

The registry record reports no analysis entries, no secondary posted outcome measures, and no details of a statistical analysis plan. It does not report the analysis population, exclusions, missing-data methods, prespecified hypotheses, or model diagnostics. It is therefore not possible to determine from the registry record whether the reported analysis followed a prespecified plan or whether alternative analyses were considered. These absences do not change the numbers posted, but they constrain how completely their robustness can be assessed.

The appropriate statistical reading is therefore focused: the posted means are close, the reported mean difference is -0.001 mm, and the unadjusted p-value is 0.972. The confidence interval includes zero, with its confidence level and calculation method not reported. These statistics characterize the posted comparison but do not prove equivalence, resolve the design-description inconsistency, or establish clinical importance.

10. Confidence Intervals and Precision

The reported confidence interval for the mean difference includes zero and extends to both negative and positive values. This means the posted estimate is not precise enough to rule out a difference in either direction under the interval’s procedure. The point estimate, -0.001 mm, is close to zero, but a point estimate alone does not communicate how uncertain that estimate is. The interval provides the relevant context for interpreting its precision.

In general, a confidence interval is a range produced by a statistical method that reflects uncertainty in an estimate. Narrower intervals indicate greater statistical precision, while wider intervals indicate that a broader range of underlying values remains compatible with the data. Precision is distinct from clinical importance: a precise estimate can still be unimportant, and a potentially important estimate can remain imprecise. The registry record does not report a threshold for clinical importance, so the interval cannot be judged against such a threshold.

The record does not state the confidence level or interval calculation method. That prevents a full appraisal of the interval’s coverage properties and makes it inappropriate to attach an unstated confidence level. The interval should be read as the interval posted, with those methodological details unavailable. Its crossing of zero indicates that the result does not establish a nonzero mean difference using that interval, but it does not establish that the groups are equivalent.

The standard deviations of 0.139 mm and 0.128 mm describe substantial participant-level spread relative to the estimated mean difference. Standard deviations and confidence intervals are not interchangeable: the former describe variability among observations, and the latter describes uncertainty in the estimated group contrast. The reported group outcome counts are 43 in each arm, but the registry does not explain how those counts relate to planned enrollment or whether all randomized participants contributed endpoint data. This limits assessment of how the analysis population and missing data may affect precision.

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

For planning at 100% of the observed effect, the figures are 280,245 participants per arm for 80% power and 375,168 participants per arm for 90% power. For planning at 75% of the observed effect, they are 498,213 participants per arm for 80% power and 666,965 participants per arm for 90% power. For planning at 50% of the observed effect, they are 1,120,978 participants per arm for 80% power and 1,500,671 participants per arm for 90% power.

In general, power is the probability that a study will identify a specified effect under the assumptions used for its design. The 80% and 90% columns represent different target probabilities for detecting the stated effect under the planning assumptions. A higher target power requires more participants in these calculations. The rows illustrate that smaller effects need more participants to detect than larger effects. The figures are not observed power and should not be interpreted as the power achieved in this completed trial.

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 = -0.001; pooled standard deviation σ = 0.134.
2. n = 2 × (1.96 + 0.842)² × 0.134² / -0.001² = 280,244.3, rounded up to 280,245 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 <- -0.001                      # observed difference in means
sigma <- 0.133613247846162                     # 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(4126057)
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 = 280,245 (80% power), 375,168 (90% power)
 75% of observed effect: n per arm = 498,213 (80% power), 666,965 (90% power)
 50% of observed effect: n per arm = 1,120,978 (80% power), 1,500,671 (90% power)
power.t.test: 280245.2 
Simulated power at n = 280,245 per arm: 0.801 (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 record lists one primary outcome measure and zero secondary posted outcome measures. It does not report the number of outcomes considered in the original protocol, whether additional time points or analyses were examined, or whether any multiplicity adjustment was planned. Multiplicity arises when multiple hypotheses are tested: the chance of at least one false-positive result can increase as the number of tests grows. In general, prespecifying a primary outcome and an analysis strategy helps clarify how to interpret statistical evidence when many outcomes or comparisons are possible. The registry entry does not provide enough information to assess that planning.

The comparison p-value is labeled unadjusted. No multiplicity correction is reported. Because the record does not describe a broader analysis plan or the complete set of analyses considered, it is not possible to determine whether adjustment was unnecessary, omitted, or addressed elsewhere. The posted p-value should be read as the unadjusted value recorded, not as evidence that multiplicity was controlled.

Missing-data handling is not reported in the registry record. The posted endpoint results give 43 participants in each group, whereas planned enrollment is 50. The record does not explain whether the difference reflects exclusions, incomplete measurements, a distinction between enrollment and analysis counts, or another reason. No imputation method, complete-case definition, or sensitivity analysis is described. In general, missing data can affect both the estimate and its precision, especially when the reason measurements are unavailable is related to outcomes or group assignment.

The analysis population is also not reported in the registry record. It is therefore unclear whether the result includes all randomized participants, only participants with outcome measurements, or another defined population. The record does not specify whether an intention-to-treat analysis was planned or performed. These details are important for evaluating how randomization was preserved in the analysis and how broadly the result applies to those assigned in the trial.

Finally, the registry’s design fields and brief summary differ on masking and trial model. The record does not report whether the statistical analysis accounted for the described contralateral structure. Without an analysis plan, population definition, and missing-data description, the posted comparison can be reported but its full analytic robustness cannot be established.

14. 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 4.65% reporting threshold.

The adverse-event entries report zero serious adverse events in the test group and zero in the control group. They also report zero other adverse events in each group and zero deaths in each group. The entries list 43 participants at risk for serious adverse events and 43 at risk for other adverse events in each group.

These are the counts recorded for the groups and event categories. A zero count means that no events in that category were reported in the registry entry; it does not demonstrate that an event is impossible or that the lenses have no risks. In general, uncommon events may not be observed in a study of limited size or follow-up, and event detection depends on collection and reporting procedures. The registry record does not give further details about safety monitoring, event definitions, or the method of attribution.

The adverse-event figures should be interpreted in the context of the recorded 6-month timeframe and the reported group counts. They do not establish comparative safety beyond the events and period recorded. The registry record does not report additional safety analyses or event narratives.

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

The result describes a randomized comparison of two DOT spectacle lens manufacturing methods for juvenile myopia. For change in axial length progression over 6 months, the reported means were 0.046 mm in the test group and 0.047 mm in the control group. The reported mean difference was -0.001 mm, and the unadjusted p-value was 0.972. The confidence interval includes zero, leaving uncertainty about the direction and size of any underlying mean difference.

These figures do not demonstrate that the manufacturing methods are identical. A result with a p-value that does not indicate a difference is not equivalent to evidence of equivalence. Equivalence requires a prespecified range of differences considered acceptably small and an analysis designed to test whether the uncertainty lies within that range. The registry record does not report an equivalence margin or an equivalence analysis.

The result also does not establish whether a difference of any particular size would matter clinically. No clinical importance threshold is reported, and the endpoint findings address the stated measurement rather than every possible outcome relevant to juvenile myopia. The registry lists no secondary posted outcome measures. The posted means and uncertainty therefore should not be generalized to unreported outcomes, longer follow-up, other populations, or comparisons with interventions not studied in this trial.

In general, the strongest interpretation of a randomized comparison depends on clear information about assignment, masking, follow-up, outcome measurement, and analysis. Here, the record describes a randomized parallel design with no masking in its design fields, while its brief summary calls the study masked and contralateral. The analysis method, analysis population, and missing-data handling are not reported. These gaps prevent a complete assessment of how the trial’s design was reflected in the posted comparison.

The result is best understood as a close pair of observed group means with an interval that includes zero, rather than proof of no difference. The safety entries report zero serious adverse events, zero other adverse events, and zero deaths in both groups, but those recorded counts do not establish absence of risk. No medical advice or broader conclusion follows from the registry statistics alone.

16. Why This Trial Matters Statistically

This trial is statistically informative because it makes a direct comparison between two manufacturing methods for the same general category of DOT spectacle lens. That design focuses the endpoint question on whether the manufacturing process is associated with a difference in mean axial length progression, rather than mixing the manufacturing comparison with a comparison of different intervention types. The reported means, mean difference, and interval make clear that both the estimate and its uncertainty matter.

The close group means are not sufficient by themselves to establish that the methods are equivalent. The interval includes zero, and the registry record does not report a clinically meaningful equivalence margin. This distinction is important in clinical research: failure to establish a difference and affirmative evidence that differences are small enough to be unimportant are different statistical claims. A reader should not infer the latter from a large p-value.

The record also illustrates why design documentation is part of statistical interpretation. The brief summary describes a masked contralateral trial, while the registry design fields indicate an unmasked parallel trial. Those design features can affect what constitutes an independent observation and how uncertainty should be calculated. Since the analysis method is not reported, the reader cannot verify how the comparison reflects the study structure.

Finally, the planning illustrations show how sample-size requirements depend on the effect targeted and the desired power under stated assumptions. They should not be confused with the trial’s original design or with power observed after completion. The record does not report the original design assumptions. Together, the endpoint result and the documentation gaps emphasize the importance of prespecified analysis plans, clear participant accounting, and transparent reporting of uncertainty.

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.

Several trial-specific limitations affect interpretation of the posted result. The registry record gives a planned enrollment of 50, while each endpoint group reports 43 participants. It does not explain the relationship between planned enrollment and the group outcome counts, or whether participants lacked measurements, were excluded, or were handled in another way. This makes it difficult to assess the analysis population and the possibility of bias from missing endpoint data.

The record contains inconsistent design descriptions. The structured design fields identify a randomized parallel trial with no masking, whereas the brief summary describes a multisite, subject- and observer-masked, contralateral trial. The record does not resolve these differences. It also does not report the allocation procedure, measurement procedures, or whether the analysis accounted for paired observations. These details matter to understanding whether the reported uncertainty matches the actual design.

The statistical analysis plan and analysis population are not reported in the registry record. The record does not state which statistical test or model produced the p-value and interval, the confidence level, whether covariates were used, or how missing values were addressed. It reports no sponsor analysis entries and no secondary posted outcomes. There is no reported equivalence margin or threshold for clinical importance, so neither equivalence nor practical importance can be established from the posted comparison.

The primary endpoint timeframe is 6 months. The registry record does not provide longer-term results or further participant characteristics. Accordingly, interpretation is limited to the posted endpoint and the groups described in this record; extrapolation to other durations, populations, or outcomes is not supported by these data.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Myopia Assessment of Two Manufacturing Processes — NCT04126057.
• Registry record last updated 2022-01-25; status last verified 2021-12.
• Results first posted 2022-01-25.
• 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

The registry record describes a completed randomized comparison of SightGlass Vision DOT spectacle lenses manufactured by method A or method B for juvenile myopia. Planned enrollment was 50. The primary outcome was mean change in axial length progression over 6 months, measured in millimeters.

The outcome entries report 43 participants in each group. The test-group mean was 0.046 mm and the control-group mean was 0.047 mm. The reported mean difference was -0.001 mm, with an unadjusted p-value of 0.972; the confidence interval includes zero. The record reports zero serious adverse events, zero other adverse events, and zero deaths in each group.

The registry does not report the analysis plan, analysis population, missing-data handling, interval confidence level, or original sample-size assumptions. Its brief summary and structured design fields also differ in their descriptions of masking and trial model. These limitations leave important aspects of the result’s analysis and design unresolved.