A Dose-ranging Study to Evaluate the Safety and Efficacy of UNR844 in Subjects With Presbyopia.: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Dose-ranging Study to Evaluate the Safety and Efficacy of UNR844 in Subjects With Presbyopia. (NCT04806503), a randomized phase 2 study. The primary outcome is Characterize Dose-response of UNR844 for Change From Baseline in Binocular Distance-corrected Near Visual Acuity (DCNVA) at Month 3.

2. Clinical Question

The primary outcome was measured without near correction at 40 cm and reported in logMAR. The registry description notes that a lower logMAR score represents better vision. The central comparison is therefore the difference between each dose group’s average change and the placebo group’s average change, rather than a comparison of final scores alone.

The study also included secondary measures of monocular near visual acuity and the proportion of participants reaching a specified gain in acuity. Those measures provide additional descriptions of the results, but they do not replace the primary question. The registry record does not report a prespecified threshold for what would constitute a clinically important difference on the primary measure.

3. Trial Design

This was a randomized, parallel-group Phase 2 study of UNR844 and placebo in participants with presbyopia. The registry lists the masking as triple, while the official study title describes the trial as double-masked. The registry record does not explain this difference in terminology. The sponsor was Novartis Pharmaceuticals.

Five regimens appear in the posted arm descriptions: UNR844 at 5 mg/mL, 13.3 mg/mL, 23 mg/mL, and 30 mg/mL, and placebo ophthalmic solution. Each regimen was one drop twice a day for three months. The posted primary outcome includes 48 participants in each of the 5 mg/mL, 13.3 mg/mL, and 30 mg/mL groups; 44 in the 23 mg/mL group; and 46 in the placebo group. The registry reports enrollment of 234.

The study start date is 2021-06-30, and the primary completion date is 2022-07-27. Its status is listed as terminated. The reason for termination, the timing of the decision, and whether termination affected the planned analyses are not reported in the registry record.

The primary outcome was change from baseline in binocular distance-corrected near visual acuity at Month 3, measured in logMAR. The registry reports a Full Analysis Set and sponsor comparisons using a mixed-effect model for repeated measures. The original protocol’s allocation details, planned sample-size justification, and full statistical analysis plan are not reported in the registry record.

4. Participant Flow and Accounting

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

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Full Analysis Set

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 Characterize Dose-response of UNR844 for Change From Baseline in Binocular Distance-corrected Near Visual Acuity (DCNVA) at Month 3, measured over Baseline, Month 3.

The primary endpoint measures change from baseline to Month 3 in binocular distance-corrected near visual acuity without near correction, at 40 cm. The measurement is expressed in logMAR. According to the registry description, lower logMAR scores represent better vision, so the endpoint focuses on how the measurement changed over the study period rather than on the Month 3 score in isolation.

The binocular measure captures near acuity using both eyes together. This makes it distinct from the secondary monocular measures, which assess the worse-seeing and better-seeing eyes separately. The registry record also lists secondary outcomes based on the proportion of participants gaining at least 0.30 logMAR.

A continuous change measure retains information about the size and direction of each participant’s change, which can be useful for comparing group averages. The endpoint is analyzed as a least-squares mean, an estimate from the sponsor’s repeated-measures model. The registry description gives the endpoint timeframe as baseline and Month 3, but further details about visit handling, the model’s covariates, or how missing measurements enter the primary analysis are not reported in the registry record.

The registry record does not state a threshold for interpreting the size of a change as clinically important. Statistical comparisons can describe how the group estimates differ and how uncertain those estimates are, but they do not by themselves establish the practical importance of a difference.

7. Results Posted in the Registry

• UNR844 5 mg/mL: mean -0.11 versus -0.11 on control; difference 0.01 (95% CI -0.05 to 0.06), standardized effect d = 0.05; z-test p = 0.823.
• UNR844 13.3 mg/mL: mean -0.11 versus -0.11 on control; difference 0.00 (95% CI -0.05 to 0.05), standardized effect d = 0.02; z-test p = 0.941.
• UNR844 23 mg/mL: mean -0.14 versus -0.11 on control; difference -0.02 (95% CI -0.08 to 0.03), standardized effect d = -0.18; z-test p = 0.393.
• UNR844 30 mg/mL: mean -0.10 versus -0.11 on control; difference 0.01 (95% CI -0.04 to 0.06), standardized effect d = 0.08; z-test p = 0.682.

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.

Characterize Dose Response of UNR844 as Measured by Change From Baseline in Monocular (Worse-seeing Eye) Distance-corrected Near Visual Acuity (DCNVA) at Month 3

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard errors.
• Result:
  • UNR844 5 mg/mL: mean -0.12 versus -0.15 on control; difference 0.02 (95% CI -0.04 to 0.08), standardized effect d = 0.14; z-test p = 0.505.
  • UNR844 13.3 mg/mL: mean -0.12 versus -0.15 on control; difference 0.02 (95% CI -0.04 to 0.09), standardized effect d = 0.16; z-test p = 0.430.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between UNR844 5 mg/mL 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 UNR844 13.3 mg/mL and the control. The interval gives the range of effects that remain compatible with the data.

Characterize Dose Response of UNR844 as Measured by Change From Baseline in Monocular (Better-seeing Eye) Distance-corrected Near Visual Acuity (DCNVA) at Month 3

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard errors.
• Result:
  • UNR844 5 mg/mL: mean -0.06 versus -0.09 on control; difference 0.03 (95% CI -0.03 to 0.08), standardized effect d = 0.21; z-test p = 0.305.
  • UNR844 13.3 mg/mL: mean -0.07 versus -0.09 on control; difference 0.01 (95% CI -0.05 to 0.07), standardized effect d = 0.07; z-test p = 0.726.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between UNR844 5 mg/mL 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 UNR844 13.3 mg/mL and the control. The interval gives the range of effects that remain compatible with the data.

Percentage of Participants Gaining at Least 0.30 logMAR in Binocular Distance-corrected Near Visual Acuity (DCNVA) (Without Near Correction) From Baseline at Month 3

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • UNR844 5 mg/mL: 4.2% (2/48) versus 4.3% (2/46) on control; risk difference -0.2 percentage points (95% CI -8.3 to 8.0), risk ratio 0.96 (0.14–6.52); unadjusted two-proportion z-test p = 0.965.
  • UNR844 13.3 mg/mL: 8.3% (4/48) versus 4.3% (2/46) on control; risk difference 4.0 percentage points (95% CI -5.8 to 13.8), risk ratio 1.92 (0.37–9.97); unadjusted two-proportion z-test p = 0.429.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between UNR844 5 mg/mL 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 UNR844 13.3 mg/mL and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes extend the primary analysis from binocular acuity to monocular acuity in the worse-seeing and better-seeing eyes, and to threshold-based gains in visual acuity. Across the posted continuous secondary outcomes, the average changes and dose-versus-placebo estimates do not form a consistent, clearly dose-ordered pattern. The threshold outcomes likewise do not provide a consistent pattern across doses. Several of the reported intervals are wide, which limits how specifically these results can describe differences.

These outcomes are related to the primary question because they examine other aspects of near visual acuity over the same baseline-to-Month 3 period. They are not identical measures: binocular and monocular assessments differ, and a threshold outcome classifies participants rather than estimating an average change. Results from one measure need not match another, and each should be interpreted according to its own definition.

The secondary findings do not overturn the primary result. The primary analysis itself is inconclusive about differences from placebo, and the secondary analyses provide no consistent pattern that resolves that uncertainty. The registry lists five secondary outcomes and reports several pairwise analyses, creating multiple opportunities for apparently notable results to occur by chance. Unadjusted secondary comparisons therefore carry less weight than a prespecified primary analysis, particularly when the record does not report a multiplicity adjustment strategy.

These secondary results are best treated as supportive or exploratory descriptions rather than as independent confirmation of a treatment effect. The registry record does not identify which secondary comparisons, if any, were designated for confirmatory interpretation, or specify a hierarchy among them. Their role in the original analysis plan is not reported in the registry record.

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

• Characterize Dose Response of UNR844 as Measured by Change From Baseline in Monocular (Worse-seeing Eye) Distance-corrected Near Visual Acuity (DCNVA) at Month 3
• Characterize Dose Response of UNR844 as Measured by Change From Baseline in Monocular (Better-seeing Eye) Distance-corrected Near Visual Acuity (DCNVA) at Month 3
• Percentage of Participants Gaining at Least 0.30 logMAR in Binocular Distance-corrected Near Visual Acuity (DCNVA) (Without Near Correction) From Baseline at Month 3
• Percentage of Participants Gaining at Least 0.30 logMAR in Monocular (Worse-seeing Eye) Distance-corrected Near Visual Acuity (DCNVA) (Without Near Correction) From Baseline at Month 3
• Percentage of Participants Gaining at Least 0.30 logMAR in Monocular (Better-seeing Eye) Distance-corrected Near Visual Acuity (DCNVA) (Without Near Correction) From Baseline at Month 3

9. Statistical Interpretation

10. Statistical Methods Explained

What is a change-from-baseline comparison? The endpoint is the difference between measurements at baseline and Month 3, summarized as a group mean. A comparison of changes asks whether the average movement over time differs between a dose group and placebo. It is not the same as comparing only the final measurements. Here the outcome is in logMAR, and the registry description states that lower scores represent better vision.

What does a least-squares mean represent? A least-squares mean is an estimated group mean produced by a statistical model. Unlike a raw arithmetic average, a model-based estimate can account for specified factors and repeated observations according to the model. The registry reports the sponsor’s primary comparisons as least-squares mean differences from a mixed-effect model for repeated measures. The model’s full specification, including its covariates and assumptions, is not reported in the registry record.

Why use a repeated-measures model? When an outcome is measured at more than one time, a repeated-measures model can use measurements across visits while accounting for the fact that observations from the same participant are related. That relationship matters: treating repeated measurements as unrelated can misrepresent uncertainty. The sponsor identifies a mixed-effect model for repeated measures for the primary comparisons. The registry record does not report all included visits, the covariance structure, or the details used to handle incomplete outcome records, so those aspects cannot be independently assessed from the posted description.

How should a mean difference be read? The sponsor’s estimate is expressed in logMAR and compares change in a dose group with change in placebo. An estimate of zero corresponds to no difference in average change. A positive or negative estimate indicates the direction of the contrast as coded in the reported comparison, but its practical meaning should be read in light of the endpoint’s direction and the confidence interval. Because logMAR lower scores indicate better vision, the sign of a change and the sign of a between-group contrast answer related but different questions.

What does a confidence interval add? A confidence interval describes the uncertainty around an estimated contrast under the analysis assumptions. A narrower interval indicates greater precision; a wider interval leaves more possible values compatible with the data and model. For the primary outcome, all sponsor-reported 95% intervals include zero. Their endpoints also extend in both directions, so the posted analyses do not precisely identify the direction or size of a difference.

What do the p-values convey? A p-value measures how compatible the observed data are with a specified null model, under the assumptions of the analysis. It is not the probability that the null hypothesis is true, nor a measure of clinical importance. The sponsor’s primary p-values are 0.817, 0.946, 0.380, and 0.667 for the four dose comparisons. The registry does not report an adjustment for multiple comparisons alongside these values; their interpretation should therefore be cautious, especially when considering several doses and outcomes together.

Why can unadjusted recalculations differ? The recalculated comparisons use posted summary statistics and are simple, unadjusted estimates. They are not a reconstruction of the sponsor’s repeated-measures model. The posted arm-level dispersion is a standard error, and the recalculation approximates standard deviations from those summaries. Such a process can differ from a model that uses participant-level repeated measurements, covariates, or a particular approach to missing outcomes. The recalculated estimates are useful as a check on the broad pattern, not as a replacement for the sponsor’s analysis.

What are the secondary analyses? The registry lists secondary continuous outcomes for monocular acuity and binary outcomes for participants gaining at least 0.30 logMAR. A continuous outcome summarizes an average measurement; a binary outcome classifies participants according to whether they meet a threshold. The registry reports multiple-imputation logistic regression for some threshold comparisons. Logistic regression models the odds of an outcome, and multiple imputation is a general method for reflecting uncertainty when values are missing, under assumptions about the missingness process. The full imputation procedure and its assumptions are not reported in the registry record.

What does over-dispersion mean in general? For count or binary outcomes, over-dispersion means the observed variability exceeds what a chosen model expects. It can make standard errors too small if ignored. This is a general statistical consideration, not a reported finding about this trial. The posted binary secondary outcomes involve small event counts in some comparisons, which can also produce wide uncertainty; the registry’s specific checks for model fit or over-dispersion are not reported.

What information is missing for a full statistical review? The registry record does not report the original sample-size assumptions, a complete multiplicity strategy, the prespecified missing-data approach for the primary analysis, interim analyses, or the complete statistical analysis plan. Without those details, the posted estimates and intervals can be described, but the degree to which every reported analysis follows the original plan cannot be assessed.

11. Confidence Intervals and Precision

The sponsor reports 95% confidence intervals for each primary comparison. For 5 mg/mL the interval is -0.045 to 0.056 logMAR; for 13.3 mg/mL it is -0.050 to 0.053; for 23 mg/mL it is -0.077 to 0.029; and for 30 mg/mL it is -0.039 to 0.062. Every interval includes zero, so the posted estimates leave no difference among the plausible values under the model’s assumptions.

Confidence intervals express uncertainty around an estimate; they are not ranges containing a fixed proportion of individual participants’ outcomes. Their width matters as much as whether they include zero. The primary intervals extend to values on either side of zero, leaving uncertainty about both the direction and magnitude of the difference. The registry record does not report a threshold for clinical importance, so these intervals cannot be classified as excluding or including a clinically important effect.

The group standard errors reported for the primary endpoint are between 0.018 and 0.020 logMAR. A standard error describes the uncertainty of a group estimate, not the spread of individual measurements. It should not be interpreted as a standard deviation. The sponsor’s intervals arise from the repeated-measures analysis; the recalculated intervals are based on simple unadjusted calculations and are not a substitute for the model-based intervals.

Secondary binary outcomes have particularly uncertain estimates when the number meeting the threshold is small. Their intervals cover a broad range of possible group differences, and the registry’s logistic-regression odds-ratio intervals are also wide. These findings reinforce that the reported secondary comparisons are imprecise. Precision is about how narrowly an effect is estimated; it is separate from whether an estimate is statistically or clinically important.

12. Planning a Similar Trial: Sample Size

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

The sample-size illustrations give participants per arm for comparisons between a single dose and placebo. They are not total event counts; the registry’s assumption note says total events apply only to time-to-event calculations, whereas these continuous and binary outcomes are expressed as participants per arm. The illustrations use a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. They use the observed effect as a reference and show planning for the stated fractions of that effect.

The 80% power column describes the participants per arm that the illustration estimates would be needed for an 80% chance of detecting the specified effect under its assumptions. The 90% power column gives the corresponding per-arm planning number for a 90% chance. These are planning quantities, not guarantees about what a future study would find. The original trial’s own sample-size assumptions and justification are not reported in the registry record.

Each displayed scenario uses either 100%, 75%, or 50% of the observed effect as the effect to detect. A smaller target effect generally requires more participants, because smaller differences are harder to distinguish from random variation. The planning figures can become very large when the observed contrast is close to zero, especially for binary outcomes with low event proportions. Such values are illustrations from the stated method, not a recommendation for a future study design.

These calculations are not observed power. They do not tell whether the trial had adequate power based on the effect that was ultimately observed; they illustrate sample sizes under specified assumptions.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

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

Worked calculation for this trial

1. Observed difference Δ = 0.006; pooled standard deviation σ = 0.130.
2. n = 2 × (1.96 + 0.842)² × 0.130² / 0.006² = 7,391.7, rounded up to 7,392 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 <- 0.00600000000000001                      # observed difference in means
sigma <- 0.130198467232012                     # 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(4806503)
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 = 7,392 (80% power), 9,896 (90% power)
 75% of observed effect: n per arm = 13,141 (80% power), 17,592 (90% power)
 50% of observed effect: n per arm = 29,567 (80% power), 39,582 (90% power)
power.t.test: 7392.7 
Simulated power at n = 7,392 per arm: 0.795 (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 primary results are least-squares mean differences from a mixed-effect model for repeated measures. The simple recalculations use the posted group summaries and are unadjusted; they approximate the comparison without reproducing the sponsor’s full model. The registry reports no discrepancy between the recalculated and sponsor analyses.

The two approaches give a similar broad reading: the estimated primary differences are small in magnitude relative to their uncertainty, and the intervals include zero. The sponsor-reported estimates are 0.006, 0.002, -0.024, and 0.011 logMAR for the dose groups in ascending order, with p-values of 0.817, 0.946, 0.380, and 0.667. The recalculations are useful for checking the direction and rough scale of the contrasts, but their assumptions differ from the repeated-measures model.

The sponsor’s analysis takes precedence as the trial’s reported analysis. In particular, its model can incorporate repeated observations and analysis features that cannot be reconstructed from summary means and standard errors alone. The registry does not supply enough detail to reproduce the full model independently. The recalculated results should therefore be read as a transparent secondary check, not as a competing primary result.

15. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when a study evaluates several doses, outcomes, time points, or pairwise comparisons. With more comparisons, the chance of observing at least one apparently unusual result can increase, even if none reflects a real difference. A prespecified adjustment or hierarchy can help control interpretation across comparisons. The registry record does not report a multiplicity adjustment strategy for the primary dose-versus-placebo comparisons or the secondary outcomes.

The primary outcome includes four comparisons with placebo, and the registry lists multiple secondary outcomes. The reported p-values should therefore be read as comparison-specific values, not as proof that the study-wide chance of a false-positive conclusion has been controlled. The fact that all sponsor-reported primary intervals include zero is relevant to the posted primary results, but it does not supply the missing prespecified multiplicity plan.

Missing data also affect interpretation. The primary outcome is described as coming from the Full Analysis Set, and the sponsor reports a mixed-effect model for repeated measures. Such models can use observed repeated measurements under their assumptions, but the registry record does not report the amount or pattern of missing primary data, the exact missing-data assumptions, or any sensitivity analyses. It is therefore not possible to judge from the record alone how robust the primary estimates are to alternative assumptions about missing measurements.

For some binary secondary outcomes, the sponsor reports multiple-imputation logistic regression. Multiple imputation can reflect uncertainty about missing values when its assumptions and procedure are appropriate. The imputation model, number of imputations, missingness pattern, and sensitivity analyses are not reported in the registry record.

The record identifies a Full Analysis Set for the primary outcome, but its precise membership rules and the handling of protocol deviations are not reported. The original statistical analysis plan, interim analyses, and sample-size justification are also not reported in the registry record. These omissions limit assessment of whether analyses and exclusions were fully prespecified and how results might change under other reasonable analytic choices.

16. Safety Results

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

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 0% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: road traffic accident (2.2%), pancreatic cystadenoma (2.2%), myelitis transverse (2.2%), appendicitis (2.1%), lumbar vertebral fracture (2.1%).

The registry reports serious adverse events for each group and an aggregate row. Serious adverse events were reported for 0 participants in the 5 mg/mL group, 1 in the 13.3 mg/mL group, 0 in the 23 mg/mL group, 1 in the 30 mg/mL group, and 3 in the placebo group. The aggregate row reports 5 participants with serious adverse events. Deaths were reported as 0 in each UNR844 group and 1 in the placebo group; the aggregate row reports 1.

These are counts, not estimates of comparative risk adjusted for follow-up or participant characteristics. Small counts provide limited precision, and the registry record does not provide enough detail to assess causes, timing, relatedness, or duration of follow-up. The listed serious-event terms and percentages are descriptive entries in the record; they do not establish that an event was caused by a study treatment.

Other adverse events were reported for 26 participants in the 5 mg/mL group, 22 in the 13.3 mg/mL group, 16 in the 23 mg/mL group, 23 in the 30 mg/mL group, and 21 in the placebo group. The registry record’s safety counts should be read as descriptive trial reports, not as a basis for individual medical decisions.

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

The posted primary results describe average change in binocular distance-corrected near visual acuity from baseline to Month 3 in four UNR844 dose groups and placebo. The sponsor-reported comparisons are close to zero, and each 95% confidence interval includes zero. The data therefore do not clearly distinguish any dose group from placebo on this endpoint in the posted analysis.

That conclusion is limited to the measured outcome, time point, participants, and analysis in the registry record. It does not prove that the groups are equivalent, that there is no effect, or that a difference of practical importance is impossible. The intervals retain uncertainty about the possible direction and size of the group differences. The registry record does not report a threshold for clinical importance, so statistical estimates alone cannot determine whether a difference would matter to participants.

The result also does not establish what would happen with different treatment durations, populations, outcome definitions, or follow-up periods. The listed regimen lasted three months, and the primary endpoint was measured at Month 3. The record’s status is terminated, but the reason for termination and its relationship to the study’s conduct or interpretation are not reported in the registry record.

Secondary measures offer additional descriptions but do not provide a consistent pattern that resolves the primary uncertainty. Safety counts are also descriptive, and the record does not establish causation for reported events. Overall, these results are evidence about the registered trial’s posted comparisons, not a definitive statement about all potential effects or risks of UNR844.

18. Why This Trial Matters Statistically

This trial illustrates how a dose-ranging study can pose several statistical questions at once: whether each dose differs from placebo, whether the pattern changes with dose, and whether related outcome definitions tell a consistent story. The primary endpoint focuses that assessment on one defined measure of binocular near acuity at a specified visit, while monocular and threshold outcomes provide additional perspectives.

It also shows why an estimate should be read together with its uncertainty. A group contrast near zero may look straightforward, but the confidence interval indicates how much uncertainty remains around its size and direction. Here the sponsor’s primary intervals include zero, and the record does not give a clinical-importance threshold. That combination calls for a measured interpretation rather than treating a p-value or a point estimate as a complete answer.

The comparison between a model-based result and a simple summary-statistic recalculation is another useful statistical distinction. The broad pattern is similar, but the sponsor’s repeated-measures analysis is the reported primary analysis; a summary-based check cannot reproduce all its features. Keeping those roles separate helps avoid giving an approximate calculation more authority than it warrants.

Finally, the record illustrates how multiple doses and secondary measures increase the need for transparent planning and reporting. A prespecified multiplicity strategy, sample-size rationale, model specification, and missing-data sensitivity analyses would help readers judge the strength and robustness of the evidence. Those details are not reported in the registry record, so the posted findings can be interpreted, but not fully audited against the original statistical plan.

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 registry reports the trial as terminated but does not give the reason for termination or clarify whether the registered enrollment and posted analyses reflect the originally planned study. The original sample-size assumptions and justification are not reported in the registry record, so it is not possible to assess the intended precision or the basis for selecting the enrollment target.

The registry’s masking field says triple, while the official title says double-masked. The record does not explain the difference. It also does not provide enough detail to assess allocation concealment or the practical implementation of masking.

For the primary analysis, the record names a mixed-effect model for repeated measures but does not give its full specification, including covariates, covariance structure, or all missing-data assumptions. The amount and pattern of missing outcome data and sensitivity analyses are not reported. These details matter for judging how dependent the estimates are on modeling choices.

The record does not report a multiplicity strategy despite comparisons across four doses and several secondary outcomes. It also does not report a clinically important difference threshold for the primary endpoint. Without those details, statistical significance and clinical relevance cannot be fully connected.

Finally, posted adverse-event counts are descriptive, and the record does not provide enough context to establish treatment relatedness or comparative safety precision. These limitations concern what can be determined from the registry record; they do not imply that the unreported analyses or procedures were absent from the full study documentation.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: A Dose-ranging Study to Evaluate the Safety and Efficacy of UNR844 in Subjects With Presbyopia. — NCT04806503.
• Registry record last updated 2024-06-20; status last verified 2024-06.
• Results first posted 2023-08-30.
• 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

NCT04806503 is a randomized, parallel-group Phase 2 dose-ranging study of UNR844 in participants with presbyopia, sponsored by Novartis Pharmaceuticals. It compares four UNR844 ophthalmic-solution concentrations with placebo, with each regimen administered as one drop twice a day for three months. Enrollment was 234, and the registry lists the study as terminated.

The primary outcome is change from baseline to Month 3 in binocular distance-corrected near visual acuity, measured in logMAR. The sponsor reported mixed-effect model comparisons of each dose with placebo. Each reported 95% confidence interval includes zero, leaving uncertainty about the direction and magnitude of the differences. The registry record does not report the original sample-size justification, complete analysis plan, multiplicity strategy, or detailed missing-data assumptions.