OCS-01 in Treating Inflammation and Pain in Post-cataract Patients: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for OCS-01 in Treating Inflammation and Pain in Post-cataract Patients (NCT04130802), a randomized phase 2 study. The primary outcome is Number of Subjects With Absence of Anterior Chamber Cells (i.e. Score of '0').

2. Clinical Question

The clinical question is framed around a binary outcome at a specified visit: whether anterior chamber cells were absent or present. A count of 0 is classified as absence; a count of 1 or more is classified as presence. This makes the comparison a question about the number of participants meeting a defined threshold, rather than a comparison of the full distribution of cell counts or grades.

The trial description identifies both inflammation and pain following cataract surgery as areas of interest. The posted primary outcome concerns anterior chamber cells, an inflammation measure; the record does not identify a pain measure among the posted primary results. It also does not report posted secondary outcome results. Thus, the primary results address the defined Day 15 inflammation outcome, not every objective described in the trial summary.

3. Trial Design

This was a randomized, double-masked, parallel-group, vehicle-controlled phase 2 study sponsored by Oculis. The registry lists the trial as completed and records enrollment of 153 participants. The listed study start was 2019-09-27, and the primary completion date was 2020-01-31.

The three arms were OCS-01 1.5% mg/mL QD, OCS-01 1.5% mg/mL BID, and placebo (vehicle) BID. Each arm had 51 participants in the posted primary outcome results. The trial summary describes eye-drop administration and identifies evaluation of efficacy and safety as the primary objective, with dosing frequency as a secondary objective. The record does not give the detailed treatment duration or a fuller schedule of visits beyond identifying the primary outcome assessment at Day 15 (visit 6).

Randomization assigns participants to treatment groups by chance, while masking is intended to limit the influence of treatment knowledge on trial conduct or outcome assessment. The registry identifies the study as double-masked but does not report which trial roles were masked or how masking was maintained. A parallel-group design means the arms are separate groups rather than treatment periods crossed within the same participant.

Although the registry reports equal arm sizes for the primary outcome, the original allocation procedure and any planned enrollment target rationale are not reported in the registry record. The trial's own sample-size justification, prespecified statistical analysis plan, interim analyses, and analysis populations are also not reported in the registry record. The planning illustrations associated with the posted comparisons are not the original trial design assumptions.

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.

6. Primary Endpoint

The registry lists the primary outcome as Number of Subjects With Absence of Anterior Chamber Cells (i.e. Score of '0'), measured over at Day 15 (visit 6).

The primary endpoint was the number of participants with absence of anterior chamber cells at Day 15 (visit 6). Cell assessment used a slit beam with fluorescein. When 10 or fewer cells were seen, the count was recorded as the actual number; otherwise, a range was reported. For the primary analysis, the observed count at visit 6 was categorized as absence when the count was 0 (Grade 0), and presence when the count was 1 or more (Grade 1, 2, 3, or 4).

This endpoint turns an ocular examination into a binary outcome that can be summarized as the number of participants meeting the no-cells definition in each arm. Such a threshold can make group comparisons straightforward to interpret: the result describes how many participants crossed a clinically defined measurement boundary at the specified visit. It does not retain distinctions among participants who had cells present, such as differences in counts or grades. The registry does not report a rationale for selecting this threshold or visit as the primary endpoint.

The posted results give 26 participants in the QD arm, 34 in the BID arm, and 10 in the vehicle BID arm with absence of anterior chamber cells, with 51 participants in each arm. These are counts for the defined endpoint, not a measure of all inflammation outcomes or of postoperative pain.

7. Results Posted in the Registry

• OCS-01 1.5% mg/mL QD: 51.0% (26/51) versus 19.6% (10/51) on control; risk difference 31.4 percentage points (95% CI 13.9 to 48.9), risk ratio 2.60 (1.40–4.82); unadjusted two-proportion z-test p = <0.001.
• OCS-01 1.5% mg/mL BID: 66.7% (34/51) versus 19.6% (10/51) on control; risk difference 47.1 percentage points (95% CI 30.1 to 64.0), risk ratio 3.40 (1.89–6.13); unadjusted two-proportion z-test p = <0.001.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is binary: each participant is classified as having absence or presence of anterior chamber cells at Day 15. The posted arm results are counts of participants meeting the absence definition, with 51 participants in each arm. The comparisons use the vehicle BID arm as the reference for each OCS-01 schedule. The posted relative measures and p-values are unadjusted comparisons; the registry record does not describe a covariate-adjusted model.

What does a risk difference express?

In general, a risk difference subtracts the event probability in one group from the event probability in another. For this endpoint, the event is absence of anterior chamber cells. A risk difference is expressed on an absolute probability scale, which helps convey how far apart the observed group probabilities are. It is distinct from a risk ratio, which expresses a relative comparison. The posted risk-difference estimates and their intervals are part of the record, but are not repeated in this explanation.

How do risk ratios and odds ratios differ?

In general, a risk ratio divides one group's probability of the event by the other group's probability. An odds ratio instead compares odds, where odds are the probability of the event divided by the probability of no event. For an outcome that is not rare, these measures can differ noticeably; they should not be treated as interchangeable. In this trial's posted comparisons, the risk ratio and odds ratio are both greater than 1 for each OCS-01-versus-vehicle contrast, indicating a larger observed frequency of the endpoint in the OCS-01 arm on each measure's scale.

The QD-versus-vehicle comparison reports a risk ratio of 2.6 and an odds ratio of 4.264. The BID-versus-vehicle comparison reports a risk ratio of 3.4 and an odds ratio of 8.2. These are relative measures derived from the observed binary outcome counts. They do not indicate how certain the estimates are on their own; that is why interval estimates are also relevant.

What does a confidence interval contribute?

In general, a confidence interval describes the range of values compatible with the data and the statistical procedure under its assumptions. It is not a guarantee that the true value lies within the interval, and it does not describe the range of individual participant outcomes. A narrower interval generally indicates greater precision for the estimated comparison, while a wider interval indicates greater uncertainty. The reported interval for the QD-versus-vehicle risk ratio runs from 1.402 to 4.821; for BID versus vehicle, it runs from 1.887 to 6.125. The corresponding odds-ratio intervals are 1.764 to 10.31 and 3.321 to 20.24.

How should the p-values be understood?

In general, a p-value describes how unusual the observed data, or data more extreme, would be if a specified null hypothesis and the test assumptions held. It is not the probability that the treatment has no effect, nor does it measure effect size. The registry reports an unadjusted p-value of <0.001 for each OCS-01-versus-vehicle comparison. The record does not report a multiplicity adjustment for the two comparisons or a full statistical analysis plan, so these p-values should be understood as the posted unadjusted results rather than as a complete account of all planned inference.

Randomization supports comparison of assigned groups by reducing the potential for systematic differences at assignment, on average. Masking can reduce some influences of treatment knowledge. These design features do not remove uncertainty from the observed results or replace details about analysis populations, missing observations, adherence, or outcome assessment. Those details are not reported in the registry record.

The record lists zero posted secondary outcome results and zero analysis records, while also including the unadjusted comparison values associated with the primary outcome counts. It does not give a model specification, test procedure, handling of missing outcomes, or adjustment strategy beyond identifying the comparisons as unadjusted. Consequently, the statistical methods can be described at the level of the posted binary counts and summary comparisons, but the full sponsor analysis cannot be reconstructed from the registry record.

10. Confidence Intervals and Precision

Precision concerns how much uncertainty surrounds an estimated comparison. The posted relative-effect intervals are broad enough to show that the exact magnitude is not known precisely. For QD versus vehicle, the risk ratio is 2.6, with an interval from 1.402 to 4.821, and the odds ratio is 4.264, with an interval from 1.764 to 10.31. For BID versus vehicle, the risk ratio is 3.4, with an interval from 1.887 to 6.125, and the odds ratio is 8.2, with an interval from 3.321 to 20.24.

Each interval describes uncertainty in a group-level effect estimate, not variation in what any one participant might experience. The intervals for the risk ratios and odds ratios do not include 1, the value corresponding to no relative difference on those scales. This observation should be considered alongside the unadjusted nature of the comparisons and the missing registry entries on the analysis plan and multiplicity handling.

The posted arm counts are 51 participants per group, and the primary endpoint counts are 26, 34, and 10. Precision depends on the data and the method used, not only on enrollment. The registry also reports risk-difference intervals, but their numerical limits are not repeated in this discussion. No precision statement removes uncertainty about missing outcomes, outcome measurement, or how results might generalize beyond the trial participants.

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 sample-size table and curve are planning illustrations based on the observed comparisons, not a record of the trial's original sample-size justification. The figures are participants per arm, not total participants, for each two-arm comparison. The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each planning row uses a stated fraction of the observed effect: 100%, 75%, or 50% of that effect.

The 80% power column gives the estimated participants per arm under those assumptions for a design with an 80% chance of detecting the specified effect if that effect is real and the assumptions hold. The 90% power column expresses the same planning concept for a 90% chance. These are design probabilities for hypothetical future studies, not probabilities that the current trial's result is correct. Smaller effects require more participants to detect under the same assumptions, which is why the rows for a smaller fraction of the observed effect show larger sample-size requirements.

For the QD-versus-vehicle comparison, the displayed figures are 36 and 47 participants per arm for 100% of the observed effect; 60 and 80 for 75%; and 126 and 169 for 50%, for the 80% and 90% power columns respectively. For BID versus vehicle, the corresponding figures are 17 and 22; 29 and 38; and 60 and 80. These figures are illustrations calculated from the posted effect estimates; they are not observed power.

The planning values do not show that the actual trial was designed using these assumptions, and they do not establish what sample size would be appropriate for another study. The original design assumptions and sample-size justification are not reported in the registry record.

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, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.196; treatment proportion p₁ = 0.510; average p̄ = 0.353.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6758 = 1.3246.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6384 = 0.5373.
4. n = (1.3246 + 0.5373)² / (0.3137)² = 35.2, rounded up to 36 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
p0 <- 0.196078431372549                          # control proportion
p1 <- 0.509803921568627                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^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 (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(4130802)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 36 (80% power), 47 (90% power)
 75% of observed effect: n per arm = 60 (80% power), 80 (90% power)
 50% of observed effect: n per arm = 126 (80% power), 169 (90% power)
power.prop.test: 35.2 
Simulated power at n = 36 per arm: 0.820 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-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 trial has two posted primary contrasts against the same vehicle BID arm: one for OCS-01 QD and one for OCS-01 BID. When multiple comparisons are examined, the chance of at least one apparently unusual result can increase if each is assessed separately without adjustment. In general, multiplicity procedures are used to control or describe that issue. The registry reports unadjusted p-values of <0.001 for both comparisons, but a multiplicity adjustment or prespecified testing hierarchy is not reported in the registry record.

The trial summary identifies dosing frequency as a secondary objective, but the registry lists zero posted secondary outcome results. A direct QD-versus-BID comparison is not reported. Other outcome analyses, including any posted pain result, are not reported in the registry record. The record lists zero analysis records, and it does not provide a detailed statistical analysis plan. It is therefore not possible to determine from the registry record which comparisons or outcomes were prespecified for formal inference, or how the family of analyses was intended to be handled.

Missing-data handling is not reported in the registry record. The posted outcome counts give 51 participants in each arm, but the record does not describe whether every randomized participant had a Day 15 assessment, how unavailable assessments were treated, or whether any imputation or sensitivity analyses were used. The analysis population, such as whether results were based on all randomized participants or another defined group, is not reported.

These omissions matter because missing outcomes and analysis-population choices can affect a binary endpoint comparison. They also limit the ability to assess whether the reported counts represent the full randomized groups under the intended analysis. No assumptions about those procedures can be inferred from the posted aggregate counts.

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 0% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: respiratory failure (2.0%), noninfectious endophthamitis (2.0%), anemia (2.0%).

The registry reports serious adverse events affecting 0 participants in the OCS-01 QD arm, 1 in the OCS-01 BID arm, and 1 in the vehicle BID arm. The numbers at risk for these summaries are 51 in each arm. Deaths are reported as 0, 0, and 1 in those respective arms. These are counts in the registry record; they do not establish the cause of an event or its relationship to study treatment.

The record also reports 17 participants with other adverse events in the QD arm, 10 in the BID arm, and 20 in the vehicle arm, with 51 at risk in each. The listed serious-event terms include Respiratory failure, noninfectious endophthamitis, and Anemia, each reported at 2.0%. The record does not provide arm-specific attribution for those listed terms in the material.

Safety counts should be read separately from the primary efficacy outcome. Counts alone do not convey timing, severity beyond the serious-event classification, duration, relatedness, or whether participants experienced more than one event. Further detail on these points is not reported in the registry record.

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

The primary results describe the proportion of participants in each randomized arm who met a specific examination-based definition at Day 15: no anterior chamber cells. The posted counts were 26 of 51 for OCS-01 QD, 34 of 51 for OCS-01 BID, and 10 of 51 for vehicle BID. The unadjusted comparisons against vehicle report relative estimates above 1 and p-values of <0.001. These observations indicate a difference in the recorded endpoint between the OCS-01 arms and the vehicle arm in this trial.

The results do not establish the precise magnitude of an effect beyond the uncertainty represented by the intervals. They also do not establish a direct difference between the QD and BID schedules: that comparison is not reported in the registry record. The primary endpoint is limited to absence of anterior chamber cells at one visit and does not summarize all possible aspects of inflammation, pain, visual outcomes, or longer-term outcomes.

A statistically small p-value does not by itself establish clinical importance, and the registry does not report a threshold for interpreting the size of the endpoint difference as important. Likewise, a relative measure should not be read as a personal prediction. The results are group-level comparisons from the participants enrolled in this trial.

The record does not report analysis populations, missing-data procedures, multiplicity adjustment, detailed methods, or the original sample-size justification. Those limitations constrain assessment of the robustness and scope of the findings. The trial also reports safety counts, but those counts alone do not determine whether a particular event was caused by treatment. The posted data should therefore be read as a limited statistical description of this trial, not as medical advice or a complete clinical assessment.

16. Why This Trial Matters Statistically

This trial illustrates how a clinical endpoint can be reduced to a binary outcome for group comparison. The measurement begins as an anterior chamber cell assessment, with counts or ranges recorded, and the primary analysis classifies each participant according to whether the observed count was 0 or 1 or more. That choice simplifies interpretation but removes information about the degree of cell presence among participants above the threshold.

The record also illustrates the distinction between absolute and relative effect measures. Risk differences describe separation on an absolute probability scale, while risk ratios and odds ratios express relative contrasts using different scales. Reporting more than one measure can help readers understand the comparison, but those measures do not answer identical questions. Their interpretation depends on the underlying outcome frequency and on clear identification of the reference arm.

Two active schedules are compared with one vehicle schedule, while the trial summary names dosing frequency as an objective. This makes it important to distinguish the posted active-versus-vehicle comparisons from a direct QD-versus-BID comparison, which is not reported. The unadjusted p-values also illustrate why the analysis plan matters when there are multiple comparisons: the record does not say whether a multiplicity strategy was prespecified or used.

Finally, the registry contains useful arm counts and uncertainty estimates, but important analytic details are absent. The record does not report the missing-data approach, analysis populations, or original design assumptions. Statistical interpretation therefore depends not only on the numerical estimates but also on recognizing what the registry record does not describe.

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 primary endpoint is a thresholded result at Day 15 (visit 6). It distinguishes a count of 0 from any count of 1 or more, grouping together all positive counts and grades for analysis. This means the endpoint does not show the distribution of cell counts among participants with cells present. The registry does not report why this threshold or assessment visit was selected.

The posted efficacy comparisons are unadjusted contrasts of each OCS-01 schedule against vehicle. A direct comparison of the two OCS-01 schedules is not reported, despite the stated objective of evaluating dosing frequency. The registry lists zero posted secondary outcome results, so the primary endpoint results do not provide a posted assessment of the pain objective or other secondary outcomes.

Detailed analysis information is absent: the analysis populations, missing-data handling, multiplicity procedures, and full statistical methods are not reported in the registry record. The original sample-size justification and any interim analyses are also not reported. These gaps limit evaluation of how the posted analyses relate to the trial's planned analyses and whether missing observations or multiple testing affected interpretation.

The record reports 153 enrolled participants, with 51 participants in each arm for the primary results. It does not provide additional information in the material about eligibility, adherence, follow-up completeness, or the representativeness of participants. Safety summaries are counts and do not include the contextual details needed to attribute events or fully characterize their timing and severity.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: OCS-01 in Treating Inflammation and Pain in Post-cataract Patients — NCT04130802.
• Registry record last updated 2025-09-10; status last verified 2025-08.
• Results first posted 2022-03-15.
• 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

NCT04130802 is a completed, randomized, double-masked, parallel-group, vehicle-controlled phase 2 study sponsored by Oculis. It evaluated OCS-01 1.5% mg/mL eye drops given QD or BID against vehicle BID following cataract surgery. Enrollment was 153, with 51 participants per arm in the posted primary outcome results.

The primary outcome was the number of participants without anterior chamber cells at Day 15 (visit 6). The registry reports counts of 26 for QD, 34 for BID, and 10 for vehicle. Each OCS-01 arm was compared with vehicle using posted unadjusted comparisons. The record also reports serious adverse event and death counts.

The registry does not report a direct QD-versus-BID analysis, posted secondary outcome results, the original sample-size justification, or detailed information on missing data, analysis populations, and multiplicity handling.