Adapalene Gel 0.3% Versus Tretinoin 0.05% Emollient Cream for Treatment of Photodamage: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Adapalene Gel 0.3% Versus Tretinoin 0.05% Emollient Cream for Treatment of Photodamage (NCT00647556), a randomized phase 3 study. The primary outcome is Change From Baseline in Overall Integrated Assessment of Photodamage at Week 24.

2. Clinical Question

The clinical question is comparative rather than a test of either intervention against no treatment. The primary measure reduces a graded assessment to whether a participant improved by at least one point. That makes the outcome an event count: participants meeting the improvement definition are counted, and the analysis compares the proportion meeting it in the two groups. The question therefore concerns the frequency of this defined improvement, not the size of each participant’s score change or a complete account of every sign of photodamage.

3. Trial Design

The registry identifies this as a phase 3, randomized, single-masked, parallel-group trial of adapalene gel 0.3% versus tretinoin 0.05% emollient cream for treatment of photodamage. Enrollment was 30, with 15 participants in each arm for the primary outcome. The trial status is completed. The recorded study start is 2008-04 and primary completion is 2010-01.

Randomized allocation means participants were assigned to study arms by a random process, according to the registry’s design classification. The record labels masking as single but does not state which people were masked or describe the masking procedures. The parallel model means the listed interventions were assigned to separate groups rather than being reported as a crossover comparison. Further details of allocation concealment, treatment administration, adherence, and follow-up procedures are not reported in the registry record.

The stated primary objective was to compare efficacy for signs of photodamage, with tolerability as a secondary objective. The registry identifies one primary outcome: the number of participants whose overall integrated assessment improved by at least one point from baseline to week 24. Secondary outcomes include the photonumeric assessment at week 12 and week 24, the number improved on the integrated assessment at week 12, and participant and investigator evaluations of improvement at week 12 and week 24. Although the record lists five outcome measures, it reports no analyses for those measures in the analyses listing. Arm-level results are posted for the primary outcome and for one week-12 secondary outcome.

The registry does not report the original sample-size justification, the trial’s planned statistical analysis, prespecified handling of multiplicity, or whether interim analyses were planned. The sample-size planning illustrations associated with the posted comparison are not the trial’s original design calculations. They should not be used to infer what assumptions shaped enrollment.

4. Participant Flow and Accounting

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

Before assignment: Wash-out period at baseline: 2 wks topical alpha-hydroxy, glycolic, salicylic, lactic, \& beta-hydroxy acids, topical vitamin A, ascorbic acid, vitamin E, corticosteroids on face; 4 wks systemic corticosteroids; 3 mos topical retinoids, superficial chemical peels/exfoliation/microdermabrasion; 6 mos botulinum toxin on the face; 1 yr oral retinoids.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: ITT (Intent to Treat), LOCF (Last Observation Carried Forward)

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 Change From Baseline in Overall Integrated Assessment of Photodamage at Week 24, measured over baseline to week 24.

The primary endpoint is the number of participants who improved in overall integrated assessment of photodamage between baseline and week 24. Improvement is defined as a decrease of at least one point on a scale that runs from 0 to 5: 0 is none, 1 minimal, 2 mild, 3 moderate, 4 severe, and 5 very severe. A lower score is better on this scale. For the primary endpoint, the graded score is converted into a binary outcome: a participant either meets the improvement definition or does not.

This kind of endpoint is used to express how many participants crossed a stated threshold for improvement. It is relatively straightforward to interpret as an event count, but it does not preserve all information about the underlying score. For example, the event definition does not distinguish a one-point decrease from a larger decrease, and the count does not describe changes among participants who did not meet the threshold. The registry posts the number meeting the definition in each arm, along with a comparison of the proportions.

The endpoint is tied to the baseline-to-week-24 timeframe and to the ITT, LOCF analysis population stated in the record. The registry does not provide a separate account of the individual score distributions or the amount of missing data contributing to the LOCF procedure. The endpoint therefore supports interpretation of the posted improvement counts, not a fuller reconstruction of all score changes over follow-up.

7. Results Posted in the Registry

• Tretinoin Emollient Cream: 66.7% (10/15) versus 40.0% (6/15) on control; risk difference 26.7 percentage points (95% CI -7.7 to 61.1), risk ratio 1.67 (0.81–3.41); unadjusted two-proportion z-test p = 0.143.

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.

Number of Participants Who Improved (a Decrease of at Least One Point) in Overall Integrated Assessment of Photodamage From Baseline to Week 12.

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Tretinoin Emollient Cream: 26.7% (4/15) versus 40.0% (6/15) on control; risk difference -13.3 percentage points (95% CI -46.7 to 20.1), risk ratio 0.67 (0.23–1.89); unadjusted two-proportion z-test p = 0.439.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Tretinoin Emollient Cream and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists several secondary outcome concepts: a photonumeric assessment at week 12 and week 24, improvement on the overall integrated assessment at week 12, and participant and investigator evaluations of improvement at week 12 and week 24. The posted arm-level results include the week-12 integrated-assessment improvement outcome, while the other listed secondary results are not reported in the registry record. The range of measures reflects that photodamage and perceived improvement can be assessed in more than one way and at more than one timepoint.

The posted week-12 result does not establish a consistent pattern that resolves the primary week-24 comparison. It is a distinct timepoint and a distinct estimate, and its uncertainty should be considered on its own terms. More generally, secondary outcomes can help describe whether the primary result is accompanied by similar patterns across other measures, but they do not automatically confirm or overturn a primary endpoint result.

Unadjusted secondary results carry less weight when multiple outcomes or timepoints are considered because the chance of at least one apparently notable finding can increase as more comparisons are examined. The registry record does not report a multiplicity plan, so readers cannot determine whether the secondary comparisons were adjusted or how they were prioritized. These results are best treated as descriptive or exploratory rather than as independent confirmatory evidence. The registry also lists no reported analyses, which limits the ability to distinguish prespecified secondary tests from analyses chosen after the data were available.

The absence of posted results for other listed secondary measures does not indicate that no change occurred; it means those results are not reported in the registry record. Taken together, the secondary outcome information offers limited context for the primary result and does not remove the uncertainty in the week-24 comparison.

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

• Photonumeric Scale for the Assessment of Photodamage From Baseline to Week 12 and Baseline to Week 24
• Number of Participants Who Improved (a Decrease of at Least One Point) in Overall Integrated Assessment of Photodamage From Baseline to Week 12.
• Number of Participants in Each Category of the Subject Evaluation of Improvement at Week 12 and Week 24
• Number of Participants in Each Category of the Investigator Evaluation of Global Response (Improvement) at Week 12 and Week 24

9. Statistical Interpretation

10. Statistical Methods Explained

What is being compared? The primary outcome is binary because each participant is classified as improved or not improved according to a decrease of at least one point in the overall integrated assessment. For a binary endpoint, the basic arm-level quantity is the proportion of participants meeting the event definition. The posted counts are 6 of 15 for adapalene and 10 of 15 for tretinoin. The comparison is reported as a risk difference, with tretinoin compared against adapalene.

A risk difference expresses the difference between the event proportions in the two arms. A value above zero in this stated comparison indicates a higher observed improvement proportion in the tretinoin arm; a value below zero indicates a higher observed proportion in the adapalene arm. The estimate of 0.267 is a point estimate: it is the single best estimate produced by the analysis, but it does not by itself express uncertainty. The confidence interval supplies information about that uncertainty.

Why use a confidence interval? A confidence interval gives a range of values compatible with the observed data under the method’s assumptions. It indicates both the direction and the precision of the estimated difference. The interval from -0.077 to 0.611 includes zero, so the data are compatible with no difference as well as with differences in either direction. It is wide enough that the magnitude of any underlying difference remains uncertain. A confidence interval is not a probability statement that the true value lies within the particular calculated interval.

What does the p-value address? The unadjusted p-value of 0.143 describes how unusual data at least as incompatible with a no-difference hypothesis would be if that hypothesis and the test assumptions were correct. It is not the probability that the null hypothesis is true, nor does it measure the size or clinical importance of a difference. The term unadjusted means that the registry’s posted value is not identified as adjusted for multiple comparisons. The statistical plan and multiplicity procedure are not reported in the registry record, so no additional adjustment should be presumed.

Why do small groups matter? The primary outcome includes 15 participants per arm. When groups are small, each participant’s outcome has a comparatively visible influence on the observed proportion, and estimates can vary substantially across samples. This does not invalidate the calculation, but it means the point estimate needs to be read alongside its interval and the number of participants. In this trial the interval is broad, making a precise conclusion about the size of a difference unwarranted.

What does randomization contribute? Random assignment is intended to make comparisons between groups less subject to systematic differences in prognostic characteristics than a nonrandomized comparison. It does not guarantee that the groups are identical, particularly in a small trial, and the registry record does not report enough baseline detail to assess balance. Randomization also does not address every source of uncertainty, such as outcome measurement, missing data, or selective reporting.

What is the role of the analysis population? The primary result is identified as ITT (Intent to Treat), LOCF (Last Observation Carried Forward). ITT generally refers to analyzing participants according to their randomized group, while LOCF is a method that carries a participant’s last observed value forward for a later assessment when data are missing. These are general descriptions of the terms; the registry record does not detail how the method was implemented for this outcome, how many observations were missing, or whether alternative analyses were performed. Such details can matter because carrying an earlier value forward may not represent the participant’s unobserved later status.

Why can over-dispersion matter? General explanation: over-dispersion occurs when variation in event counts exceeds what a statistical model assumes. It can make standard errors too small if the model does not account for the extra variation. The primary outcome is posted as a simple participant count and compared using a risk difference; the registry does not describe a model-based count analysis or report an over-dispersion assessment. This general issue should therefore not be taken as a claim that over-dispersion occurred in this trial.

What can be inferred from the reported analysis listing? The registry lists no reported analyses, while arm-level outcome counts and a comparison are posted for the primary endpoint and one secondary endpoint. The lack of a reported analysis plan means readers cannot confirm from the record which statistical procedures were specified before outcomes were examined. The posted comparison remains interpretable as a numerical estimate with an interval and unadjusted p-value, but it cannot be assumed to reproduce an undocumented prespecified analysis.

How should endpoint selection be understood? The primary outcome uses a threshold on a 0-to-5 assessment scale. Thresholding makes the result easy to express as the number improved, but discards information about the amount of change and the distribution of scores. Other listed outcomes assess photodamage or evaluations of improvement at different timepoints. A single binary endpoint is therefore only one lens on the trial’s measured outcomes and should not be treated as a complete description of all possible responses.

11. Confidence Intervals and Precision

The primary risk-difference estimate is 0.267, with a 95% confidence interval from -0.077 to 0.611. This range is broad relative to the point estimate and spans zero. It therefore leaves uncertainty about whether the underlying difference favors tretinoin, favors adapalene, or is close to no difference. The estimate’s direction should not be mistaken for a precise measurement of a treatment contrast.

Precision depends in part on how much information the data contain. There were 15 participants in each arm for this outcome, with 6 and 10 meeting the improvement definition. Those counts convey the amount of observed outcome information. The confidence interval conveys how uncertain the estimated contrast remains after accounting for sampling variability under the calculation’s assumptions. A point estimate alone would conceal that uncertainty.

The unadjusted p-value was 0.143. It is consistent with the interval’s inclusion of no difference, but the p-value and interval answer related, not identical, questions. The interval emphasizes a range of plausible effect values; the p-value measures compatibility with a specified no-difference hypothesis under a test. Neither establishes clinical importance or equivalence.

Precision is also bounded by what the record reports. The population is identified as ITT with LOCF, but the number and pattern of missing observations and any sensitivity analyses are not reported in the registry record. The original analysis plan and any adjustment for multiple comparisons are also not reported in the registry record. Thus, the interval describes uncertainty for the posted comparison and does not encompass every possible uncertainty arising from outcome selection, missingness, or analytic choices.

12. Planning a Similar Trial: Sample Size

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

The planning figures are participants per arm, not total participants and not total events. They illustrate the group sizes that would be required under the stated planning assumptions if the effect to detect were the stated fraction of the observed risk difference. For planning at 100% of the observed effect, the illustration gives 54 participants per arm for 80% power and 72 participants per arm for 90% power. For planning at 75% of the observed effect, it gives 97 participants per arm for 80% power and 130 participants per arm for 90% power. For planning at 50% of the observed effect, it gives 219 participants per arm for 80% power and 293 participants per arm for 90% power.

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

In plain language, 80% power is the planned chance of detecting an effect of the specified size at the stated significance level if that effect is the true one and the assumptions hold. The 90% column uses a higher target chance of detection, which generally requires a larger group size. The illustrations also show that smaller effects need more participants to detect than larger effects under the same assumptions. These figures are planning illustrations, not observed power, and they do not show that the completed trial had a particular probability of finding a difference.

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

Worked calculation for this trial

1. Control proportion p₀ = 0.400; treatment proportion p₁ = 0.667; average p̄ = 0.533.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.7055 = 1.3828.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6799 = 0.5722.
4. n = (1.3828 + 0.5722)² / (0.2667)² = 53.7, rounded up to 54 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 <- 0.4                          # control proportion
p1 <- 0.666666666666667                          # 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(647556)
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 = 54 (80% power), 72 (90% power)
 75% of observed effect: n per arm = 97 (80% power), 130 (90% power)
 50% of observed effect: n per arm = 219 (80% power), 293 (90% power)
power.prop.test: 53.7 
Simulated power at n = 54 per arm: 0.789 (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.

14. Multiplicity, Missing Data and Analysis Populations

The registry record identifies one primary outcome and several secondary outcomes, including assessments at week 12 and week 24. When multiple outcomes, timepoints, or comparisons are examined, the chance of obtaining at least one apparently notable result by chance can increase. Statistical procedures can address this multiplicity, but no multiplicity adjustment or hierarchy of testing is reported in the registry record. The posted p-value is unadjusted, so it should not be interpreted as accounting for the full set of outcome opportunities.

The record lists no reported analyses. It therefore does not describe the statistical plan in enough detail to establish which comparisons were prespecified, what tests were intended, how results across timepoints were to be handled, or whether any interim analyses were planned. Each of those details is not reported in the registry record. The absence of this information does not prove that no plan existed; it limits what can be verified from the registry entry.

The primary analysis population is described as ITT (Intent to Treat), LOCF (Last Observation Carried Forward). ITT is generally intended to retain participants in their randomized groups for analysis, while LOCF carries a previously observed value forward when a later measurement is missing. The registry does not report the number of missing observations, their distribution by arm, reasons for missingness, or further implementation details. It also does not report sensitivity analyses that would show how the result changes under alternative missing-data assumptions.

Missing outcomes can affect both the event counts and the uncertainty of a comparison, depending on how much information is absent and why. LOCF is an explicit approach, but its use does not eliminate uncertainty about unobserved outcomes. Without details on missingness or sensitivity analyses, the robustness of the posted result to missing-data assumptions cannot be assessed from the registry record.

These reporting gaps are relevant when weighing the findings, especially in a small trial with several listed outcome measures. They do not change the arithmetic of the posted counts or risk difference, but they limit assessment of the broader analysis process and the strength of confirmatory interpretation.

15. Safety Results

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

Other (non-serious) adverse events

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

Most frequent non-serious adverse event terms

The serious adverse event figures report 0 participants affected among 15 at risk in the Differin® Gel, 0.3% arm and 0 participants affected among 15 at risk in the Tretinoin Emollient Cream arm. The record lists no serious adverse event terms. These figures describe what was posted for the trial participants; they do not establish that serious events are impossible or characterize safety beyond the observed trial.

Other adverse events are reported for 7 of 15 participants in the adapalene arm and 14 of 15 in the tretinoin arm. These are counts of participants affected, not counts of all event episodes. The record does not provide details in this summary about event type, severity, timing, attribution, or how many events each affected participant experienced. Death counts are not reported in the registry record.

Because the study enrolled 30 participants, the safety observations are limited in scale. The posted figures should be read as descriptive counts rather than as a precise comparison of risks or evidence about uncommon events. The registry summary identifies tolerability as a secondary objective, but a fuller interpretation would require event definitions and additional clinical context not reported in the registry record.

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

The primary result describes the number of participants who met a specific improvement threshold by week 24. The observed counts were 6 of 15 in the adapalene group and 10 of 15 in the tretinoin group. The estimated risk difference was 0.267 in the direction of more observed improvement in the tretinoin arm, but the confidence interval from -0.077 to 0.611 includes no difference and values in either direction. The unadjusted p-value was 0.143.

This evidence does not establish that tretinoin is better, that adapalene is better, or that the treatments are equivalent. Failure to show a clear difference is not proof that there is no difference. Conversely, a point estimate favoring one arm does not establish an advantage when uncertainty is substantial. The result is most accurately described as an uncertain estimate from a small randomized comparison.

The endpoint captures a decrease of at least one point on an overall integrated scale. It does not show the full distribution of score changes, the magnitude of change among improved participants, or results across every listed measure. It also does not by itself summarize tolerability, participant experience, or the full benefit-risk profile. Secondary measures may add context, but the registry does not report all listed secondary results or a multiplicity plan.

The trial’s scope is limited to the enrolled participants, the specific interventions, and the recorded follow-up assessments. The registry record does not report enough information to establish how broadly the findings apply to other populations or settings. Missing-data details and the original statistical plan are also not reported in the registry record. Those limitations should remain visible when interpreting the estimate, rather than being replaced by a categorical conclusion.

In practical statistical terms, the result is informative about the observed event counts and the range of differences compatible with them, but not decisive about the true comparative effect. It should be read as one piece of evidence whose precision, endpoint definition, and reporting limits all matter.

17. Why This Trial Matters Statistically

This trial is statistically informative because it presents a direct randomized comparison and a clearly defined binary primary endpoint. The registry specifies what counts as improvement, the assessment timeframe, the arm-level participant counts, and a risk-difference estimate with a confidence interval. These details allow readers to distinguish the observed direction from the uncertainty around the comparison.

The small enrollment makes precision especially important. The point estimate alone might suggest a substantial difference in the observed improvement proportions, but the confidence interval is broad and includes zero. Reading the estimate together with its interval prevents a directional result from being mistaken for a definitive finding. The posted unadjusted p-value likewise does not substitute for considering the size and precision of the estimate.

The record also illustrates why endpoint definitions matter. A one-point improvement threshold produces an accessible count, but it compresses a graded scale into a yes-or-no classification. That is useful for one interpretive question while leaving other information about score changes unrepresented. The listed secondary outcomes indicate that different assessments and timepoints were part of the outcome set, yet not all are accompanied by posted results.

Finally, the entry highlights the importance of transparent reporting. The analysis population is identified, but details about missingness, multiplicity, the original sample-size justification, and the statistical plan are not reported in the registry record. These omissions do not erase the posted result; they affect how confidently readers can evaluate its analysis context and robustness. The trial is therefore a useful example of interpreting an observed estimate without overstating what the record can support.

18. 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 based on a threshold of at least a one-point decrease in a 0-to-5 assessment. This binary classification does not reveal the full distribution of score changes, and it treats participants who improve by different amounts as meeting the same event definition. It also does not describe changes that fall short of the threshold.

Enrollment was 30, with 15 participants in each primary-outcome arm. The risk-difference confidence interval is broad, so the comparison is imprecise. The limited number of participants also means that the posted counts represent a small evidence base for assessing variation in outcomes or less common safety events.

The registry identifies the primary analysis population as ITT with LOCF, but does not report the amount or pattern of missing data, the detailed implementation of LOCF, or sensitivity analyses. The original statistical plan, multiplicity handling, interim-analysis plans, and sample-size justification are not reported in the registry record. The analyses listing contains no reported analyses, although primary and one secondary comparison are posted.

Several secondary outcomes are listed, but the registry does not report all of their results. This restricts assessment of consistency across measures and timepoints. The record also does not identify who was masked, describe allocation concealment, or provide further information about baseline characteristics, adherence, or detailed outcome-assessment procedures. These items are not reported in the registry record and should not be inferred from the design labels.

Safety reporting is limited to participant counts for serious and other adverse events in the registry summary. Event details and death counts are not reported in the registry record. Together, these limits mean the entry supports a focused interpretation of the posted outcome counts, not a comprehensive account of every clinical, analytic, or safety consideration.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Adapalene Gel 0.3% Versus Tretinoin 0.05% Emollient Cream for Treatment of Photodamage — NCT00647556.
• Registry record last updated 2022-08-01; status last verified 2012-09.
• Results first posted 2011-02-24.
• 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.

22. Record Summary

The registry describes a completed, randomized, single-masked, parallel phase 3 trial comparing adapalene gel 0.3% with tretinoin 0.05% emollient cream for photodamage. Enrollment was 30, with 15 participants per arm for the primary outcome. The recorded start was 2008-04 and primary completion was 2010-01.

The primary endpoint counted participants with at least a one-point improvement in overall integrated assessment of photodamage from baseline to week 24. The posted counts were 6 of 15 for adapalene and 10 of 15 for tretinoin. The risk difference for tretinoin compared with adapalene was 0.267, with a 95% confidence interval from -0.077 to 0.611 and an unadjusted p-value of 0.143. The interval indicates substantial uncertainty about the direction and size of the comparative effect.

The record also posts week-12 integrated-assessment results and lists additional secondary outcomes. No serious adverse events were reported among the 15 participants at risk in either arm; other adverse events affected 7 participants in the adapalene arm and 14 in the tretinoin arm. The original sample-size justification, statistical plan, multiplicity procedures, and detailed missing-data information are not reported in the registry record.