Emdogain Minimally Invasive Surgical Technique: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Emdogain Minimally Invasive Surgical Technique (NCT02551770), a randomized na study. The primary outcome is Change in Clinical Attachment Levels (CAL).

2. Clinical Question

The clinical question concerns the additional contribution of Emdogain within the described treatment approach, rather than a comparison of surgery with no treatment. Both groups received scaling and root planing; Emdogain distinguishes the test treatment from the control treatment. The primary outcome is a change measure, so the comparison addresses the difference in average change between treatments, not the absolute clinical attachment level at follow-up.

The registry record lists several other outcomes, including gingival margin, pocket probing depth, plaque score, bleeding on probing, root dentin hypersensitivity, and post-surgical pain. Posted numerical comparisons are available for gingival margin and pocket probing depth. The record lists no reported analyses for the other listed secondary outcomes. The primary comparison is therefore the clearest posted statistical result for the principal clinical question; the registry record does not report a broader adjusted analysis incorporating all outcomes.

3. Trial Design

The registry record describes a randomized controlled study and lists 51 participants as enrolled. It names Institut Straumann AG as the sponsor and gives the status as completed. The recorded start is 2015-10, and the primary completion is 2018-06. The phase is listed as NA, which does not establish a drug-development phase for this procedure and device study.

The official title describes a split-mouth design, while the registry model field identifies the study as parallel. Those descriptions are not fully aligned. The record does not explain how randomization was implemented, how treatment sides or teeth were assigned, or how the split-mouth description relates to the parallel model classification. Those design details are not reported in the registry record, so the exact allocation unit and the handling of within-participant correlation cannot be confirmed from the record.

Masking is listed as none. The treatment descriptions distinguish scaling and root planing with Emdogain from scaling and root planing without Emdogain. The primary outcome summaries report 49 observations in each treatment group. These outcome counts are not the same as the enrollment count, and the registry record does not provide a participant flow account explaining all differences between enrollment and endpoint observations.

The primary outcome is described as mean change in clinical attachment levels from baseline measurements at surgery to the 12-month follow-up visit. The reported primary population is the ITT data set with imputation of missing values: five 12-month values were replaced with values from the 9-month follow-up. The record does not describe the original trial sample-size justification, its planned statistical analysis in sufficient detail, or any interim analyses. These design features should not be inferred from the posted comparison or from the separate planning illustrations based on observed effects.

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: Oversight. 1 extra patient was enrolled.

Overall Study

Analysis population for the primary outcome, as defined in the registry: The ITT data set with imputation of missing values (five CAL values were missing at 12 month follow-up and were replaced with values from 9 month follow-up).

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 in Clinical Attachment Levels (CAL), measured over Baseline and 12 Month Follow-Up Visit.

The primary endpoint is change in clinical attachment levels, measured in millimeters. The registry record states that clinical attachment levels were measured on study teeth at 6 locations. The outcome is the mean change from baseline measurements at surgery to the 12-month post-surgery visit, using the deepest pocket of a participant’s test and control teeth measured at baseline. The analysis is described as comparing mean change between the test and control treatments.

In general, a change endpoint expresses how a measured clinical feature differs between baseline and follow-up. Clinical attachment level is used to assess the relationship between the tooth and its supporting periodontal tissues; measuring change allows the comparison to focus on the course of that measure over the follow-up period. The endpoint is continuous, and the registry record describes the arm summaries as means with standard deviations.

The recorded primary population is the ITT data set with imputation for missing values. Specifically, five CAL values missing at the 12-month visit were replaced by values from the 9-month visit. The record does not provide further detail about the imputation procedure or how uncertainty from those substitutions was incorporated into the comparison. This matters when interpreting the endpoint: the posted summaries are not based solely on observed 12-month values, but include the described replacements.

The endpoint is a clinical measure, not a direct measure of every outcome relevant to participants. The registry record separately lists patient-reported outcomes and other clinical measures as secondary outcomes, but it does not report numerical analyses for every listed measure.

7. Results Posted in the Registry

• Test (With Emdogain): mean -2.20 versus -2.10 on control; difference -0.10 (95% CI -0.66 to 0.46), standardized effect d = -0.07; z-test p = 0.724.

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.

Change in Gingival Margin (GM)

• 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 deviations.
• Result:
  • Test (With Emdogain): mean -0.30 versus -0.20 on control; difference -0.10 (95% CI -0.49 to 0.29), standardized effect d = -0.11; z-test p = 0.612.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Test (With Emdogain) and the control. The interval gives the range of effects that remain compatible with the data.

Change in Pocket Probing Depth (PPD)

• 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 deviations.
• Result:
  • Test (With Emdogain): mean -2.40 versus -2.30 on control; difference -0.10 (95% CI -0.61 to 0.41), standardized effect d = -0.08; z-test p = 0.698.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Test (With Emdogain) and the control. The interval gives the range of effects that remain compatible with the data.

The posted numerical secondary comparisons cover change in gingival margin and change in pocket probing depth. In both, the estimated mean differences are small, and the confidence intervals span zero. This broad pattern is consistent with the primary comparison in the limited sense that none of these posted mean contrasts clearly separates the treatment groups. It does not establish that all measured outcomes behave similarly: the registry record lists additional secondary outcomes for which numerical analyses are not reported.

These secondary measures add context because they assess features other than clinical attachment level. They do not replace the primary endpoint, and their estimates should not be treated as independent confirmation of the primary result. Outcomes measured in the same participants may be related, and the record does not describe their correlations or a joint analysis. The registry record lists 7 outcome measures but reports no secondary analyses in its analysis listing, even though numerical comparisons are posted for two secondary measures.

The posted secondary p-values are unadjusted. General statistical explanation: when several outcomes or comparisons are examined, the chance of obtaining a seemingly noteworthy result by chance can rise if each is judged separately without accounting for the set of tests. Multiplicity procedures can address that issue, but the registry record does not report a multiplicity plan or adjusted secondary results. This is why unadjusted secondary findings generally carry less weight than a clearly specified primary comparison, particularly when many outcomes have been considered.

The absence of reported analyses for the remaining listed secondary outcomes should not be interpreted as a finding of no change or no difference. It means the registry record does not provide numerical results for those outcomes. Together, the available secondary comparisons offer descriptive support for understanding the posted primary result, but they cannot establish a consistent treatment effect across all clinical and patient-reported outcomes.

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

• Change in Gingival Margin (GM)
• Change in Pocket Probing Depth (PPD)
• Change in Full Mouth Plaque Score (FMPS)
• Change in Bleeding on Probing (BoP)
• Change in Root Dentin Hypersensitivity
• Change in Post-surgical Pain

9. Statistical Interpretation

10. Statistical Methods Explained

The registry record describes a continuous primary outcome summarized by a mean and standard deviation. General statistical explanation: a mean represents the average observed change in a group, while a standard deviation describes the spread of individual observations around that group average. The standard deviation is not a confidence interval for the mean and does not describe how precisely the treatment difference has been estimated.

What does the mean difference represent?

The reported mean difference compares the test treatment with the control treatment. The posted values are -2.2 mm for the test group and -2.1 mm for the control group, yielding a reported mean difference of -0.1 mm. The sign depends on the comparison order: the test treatment is listed first and control second. A negative value therefore indicates that the test-group mean change is more negative than the control-group mean change under that ordering. It should not be read as an estimate of the absolute change in either group; those group means are reported separately.

General statistical explanation: a difference in means is a direct way to express the contrast for a continuous outcome. It preserves the measurement unit, which in this comparison is millimeters. The contrast is useful for understanding the estimated scale and direction of a group difference, while its uncertainty is conveyed by the confidence interval.

How should the confidence interval be understood?

The confidence interval for the primary mean difference runs from -0.656 to 0.456 mm. General statistical explanation: a confidence interval expresses a range of estimates compatible with the data and the assumptions of the statistical procedure. It describes uncertainty around an estimate; it is not a range containing a known, fixed proportion of individual participant outcomes. Because this interval contains zero and spans negative and positive values, the posted result does not sharply distinguish the direction of the mean difference.

The registry record does not state the confidence level or fully describe the method used to calculate this interval. It is therefore appropriate to refer to it as the posted confidence interval without supplying an unreported confidence level or assuming details of the procedure. The interval’s width reflects the precision of the posted estimate, subject to the assumptions of the calculation and the way the study data were handled.

What does the p-value add?

The unadjusted p-value for the primary comparison is 0.724. General statistical explanation: a p-value measures how unusual the observed data, or data more extreme, would be under a specified null hypothesis and statistical model. It is not the probability that the null hypothesis is true, and it does not measure the size or clinical importance of an effect. The p-value is called unadjusted because the posted value does not account for testing multiple outcomes or comparisons.

The p-value and confidence interval answer related but distinct questions. The p-value summarizes compatibility with a no-difference null model under the test used; the interval displays a range of plausible values on the outcome scale. Neither substitutes for consideration of the estimated difference, its precision, study design, and clinical context. The registry record does not report the full testing procedure, so interpretation of the p-value should remain tied to the result as posted.

Why can over-dispersion and dependence matter?

General statistical explanation: over-dispersion means that observations vary more than a statistical model expects. If a model assumes less variation than is present, standard errors can be too small and intervals can be too narrow. Conversely, a model that accounts for appropriate sources of variation can provide more realistic uncertainty. The registry record reports standard deviations for the continuous outcomes, but it does not state whether over-dispersion was assessed or whether a model-based adjustment was used.

General statistical explanation: observations from the same participant are often correlated rather than independent. In a split-mouth study, treatment sites within one participant may share characteristics. A valid comparison may need to account for that pairing or clustering, depending on the analysis and data structure. The official title identifies a split-mouth design, while the model is listed as parallel. The registry record does not resolve that discrepancy or report whether dependence between teeth or sites was incorporated into the primary comparison. No particular analysis method should be assumed.

How should the reported population and missing values be read?

The primary outcome description identifies an ITT data set and says that five CAL values missing at the 12-month follow-up were replaced with values from the 9-month follow-up. General statistical explanation: an ITT approach aims to retain participants in the groups to which they were assigned, according to the analysis plan. The record does not give enough detail to verify the exact implementation of that principle, including how the treatment groups and missing observations were handled beyond the stated replacements.

Replacing a missing 12-month value with a 9-month value is a specific choice described in the registry record. It is not possible to infer from the record whether additional imputation methods or sensitivity analyses were conducted. The implications depend on how values can change between follow-up visits and on the assumptions used in the analysis. The record does not report those assumptions or a sensitivity analysis.

The posted statistical summary is therefore informative but not a complete account of the inferential procedure. Details not reported in the registry record include the full analysis specification, the confidence-interval method, how any within-participant dependence was handled, and whether results were checked under alternative missing-data assumptions. These omissions do not erase the posted estimate; they define the limits on how thoroughly it can be evaluated.

11. Confidence Intervals and Precision

The primary mean difference is -0.1 mm, and its confidence interval extends from -0.656 to 0.456 mm. The interval includes zero and values on both sides of zero. This means the posted data do not provide a precise direction for the average treatment contrast. The interval is not confined to a narrow range around the estimate, so meaningful uncertainty remains about the size and direction of the difference.

General statistical explanation: precision concerns how narrowly an estimate is determined by the data and the statistical model. A confidence interval is one way to express that precision. A narrower interval gives a more concentrated range of estimates, while a wider interval leaves more uncertainty. Precision is distinct from whether an estimate is clinically important: a precisely estimated small difference could still have limited importance, and an imprecisely estimated difference may leave open possibilities that matter clinically.

The primary arm summaries report 49 observations per treatment group, with standard deviations of 1.5 mm for the test group and 1.3 mm for the control group. The registry record reports that five missing 12-month CAL values were replaced with 9-month values. The record does not explain how those replacements affect the confidence interval, nor does it state whether the interval accounts for the study’s split-mouth description or possible within-participant dependence.

The confidence interval should not be interpreted as proof of no treatment difference. It also should not be treated as evidence that every difference inside the interval is equally likely or clinically important. The registry record does not report a threshold for clinical importance, so the statistical interval cannot by itself determine whether its possible values would matter to patients or clinicians. It describes uncertainty in the estimated mean contrast under the posted analysis, with the methods-reporting limitations noted above.

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 translate the observed treatment difference into planning scenarios. The figures are participants per arm, not total events. The planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each scenario uses the stated fraction of the observed effect as the effect to detect. The original trial’s own sample-size assumptions and justification are not reported in the registry record.

The 80% power column gives the planned number of participants per arm for a hypothetical future study to have an 80% chance of detecting the specified effect under the planning assumptions, if that effect were the true effect and the assumptions held. The 90% power column gives the corresponding planning count for a 90% chance. These are planning targets, not descriptions of what happened in the completed study. They are not observed power.

The illustrations consider planning for 100% of the observed effect, planning for 75% of the observed effect, and planning for 50% of the observed effect. A smaller target effect requires more participants to distinguish it from random variation at the same significance level and power target. The table and curve should therefore be read as conditional planning tools: the required number depends on the effect chosen and on the listed statistical assumptions. They do not establish that the original study was designed around those assumptions or that its observed result has a particular probability of being true.

The observed effect is especially small in the primary comparison, so the resulting planning counts are large. That pattern follows from the planning calculation and should not be mistaken for a recommendation about the size of any future study. The registry record does not report the trial’s original power target, significance level, target effect, or planned enrollment rationale.

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 = -0.100; pooled standard deviation σ = 1.404.
2. n = 2 × (1.96 + 0.842)² × 1.404² / -0.100² = 3,092.5, rounded up to 3,093 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 <- -0.1                      # observed difference in means
sigma <- 1.40356688476182                     # 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(2551770)
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 = 3,093 (80% power), 4,140 (90% power)
 75% of observed effect: n per arm = 5,498 (80% power), 7,360 (90% power)
 50% of observed effect: n per arm = 12,370 (80% power), 16,560 (90% power)
power.t.test: 3093.4 
Simulated power at n = 3,093 per arm: 0.798 (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. Multiplicity, Missing Data and Analysis Populations

The registry record lists a primary outcome and several secondary outcomes, including changes in gingival margin, pocket probing depth, plaque score, bleeding on probing, root dentin hypersensitivity, and post-surgical pain. It lists 7 outcome measures overall. Numerical comparisons are posted for the primary outcome and two secondary outcomes, while the record reports no analyses in the analysis listing and does not provide numerical results for every listed outcome.

Multiplicity concerns arise when several outcomes or statistical comparisons are examined. General statistical explanation: if each test is interpreted separately, the chance of at least one apparently unusual result can increase across the set. An analysis plan may specify which outcome is primary and whether secondary tests will be adjusted or treated as exploratory. The registry record does not report a multiplicity adjustment, a hierarchy for secondary outcomes, or a detailed plan for interpreting multiple tests. The posted secondary p-values are unadjusted and should be treated cautiously in that context.

Missing data are relevant to the primary endpoint. The registry record identifies the primary population as the ITT data set with imputation and states that five CAL values missing at the 12-month follow-up were replaced with values from the 9-month follow-up. It does not report why those values were missing, whether missingness differed by treatment, whether additional imputation approaches were used, or whether sensitivity analyses tested the effect of the replacements. Those details are not reported in the registry record.

The design description also leaves a question about the analysis population and dependence structure. The official title identifies a split-mouth design, while the model is listed as parallel. The record does not explain how randomization was carried out or whether analyses accounted for paired measurements within participants. It also does not report the full analysis plan, interim analyses, or an original sample-size justification. These omissions limit assessment of the analysis but do not alter the numerical values posted for the primary comparison.

15. 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: breast cancer diagnosis (2.0%).

The adverse-event summary is grouped under all participants. It reports 1 serious adverse event among 51 participants at risk, 15 other adverse events among 51 participants at risk, and 0 deaths. The most frequently listed serious-event term is Breast Cancer diagnosis, reported as 2.0%. These are registry counts and a listed event term; they do not by themselves explain when events occurred or whether they were considered related to either treatment.

The record does not present these adverse-event figures separately for the test and control treatments. It also does not report the event details, severity grading beyond the serious-event classification, duration, outcome, or an attribution assessment in the information summarized. The serious-event count should therefore be read as an overall safety-reporting total, not as a comparison of treatment-specific risks. The “other adverse events” count is separate from the serious-event count in the record, but the available summary does not give a breakdown of those other events.

General statistical explanation: safety counts describe observed events in the reported group and should be interpreted in light of the number at risk, follow-up, event definitions, and how events were collected. The registry record gives the at-risk counts but does not provide enough detail to assess comparative safety or causality. These figures do not establish that an event was caused by a treatment or that no unlisted event occurred.

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

The primary result describes a small observed difference in mean change in clinical attachment levels between the treatment groups, with a confidence interval that includes zero and extends in both directions. The unadjusted p-value is 0.724. Together, these statistics indicate that the posted comparison does not precisely determine a difference between treatments. They do not establish that the treatments are equivalent, and they do not show that every potentially important difference has been ruled out.

General statistical explanation: evidence of no statistically clear difference is not the same as evidence that two treatments have identical effects. Demonstrating equivalence or non-inferiority usually requires a prespecified margin and an analysis designed for that question. The registry record does not report such a margin or state that equivalence was the trial objective. The results should therefore be described as an estimate with uncertainty, not as proof of sameness.

The record’s endpoint is a clinical measure over the specified follow-up period, and the primary comparison uses the described ITT data set with five missing 12-month values replaced by 9-month values. The result does not address outcomes beyond those measured and reported. Several secondary outcomes are listed, but numerical results are not reported for all of them. Nor do the adverse-event totals provide a treatment-specific comparison.

The interpretation is also limited by reporting gaps. The official title describes a split-mouth design, while the model field says parallel, and the registry record does not explain whether within-participant dependence was accounted for. The exact primary analysis method, confidence-interval method, multiplicity strategy, and original sample-size rationale are not reported. These limitations make it inappropriate to read the posted p-value as a complete evaluation of the study’s statistical evidence.

In practical terms, the registry record supports a description of the observed group means and their uncertainty. It does not support a claim that Emdogain is beneficial or ineffective, that the treatments are equivalent, or that the result applies beyond the participants and follow-up described. Judging clinical importance would require an appropriate clinical threshold and a fuller understanding of the study methods, neither of which is reported in the registry record.

17. Why This Trial Matters Statistically

This trial illustrates why an estimated treatment difference should be read together with its uncertainty. The primary mean difference is reported in the original clinical unit, millimeters, while the confidence interval conveys how much uncertainty surrounds that estimate. A p-value alone would not show the range of effects compatible with the posted comparison or distinguish statistical evidence from clinical importance.

It also illustrates the importance of study structure. The official title identifies a split-mouth design, but the registry model is parallel. In general, paired measurements from the same participant can carry different information from measurements in independent groups because observations within a participant may be related. When the design description and analysis details are unclear, readers cannot fully evaluate whether the estimated uncertainty reflects the structure of the data.

The record also shows why missing-data reporting matters. The primary population uses an ITT data set and includes five 12-month CAL values replaced with values from the 9-month visit. Reporting the replacement is useful, but without further details or sensitivity analyses, readers cannot assess how robust the primary result is to alternative assumptions about missing values.

Finally, the planning illustrations demonstrate that sample-size calculations depend on the effect a future study aims to detect. Smaller target effects require more participants under the stated assumptions. These illustrations are separate from the trial’s original design rationale, which is not reported in the registry record. Taken together, the study emphasizes careful separation of observed estimates, uncertainty, design assumptions, missing-data handling, and planning scenarios.

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.

Several limitations are specific to the available record for this study. The design description is internally unclear: the official title identifies a split-mouth design, whereas the model is listed as parallel. The registry record does not explain the allocation unit, how treatment sites or teeth were assigned, or how any within-participant correlation was handled. This makes it difficult to assess whether the reported comparison reflects the study structure.

The primary outcome population includes five CAL values missing at the 12-month visit that were replaced with values from 9-month follow-up. The record does not state why the values were missing, how missingness was distributed across treatment groups, or whether alternative imputation and sensitivity analyses were performed. The posted outcome counts are 49 in each group, while total enrollment is 51; the registry record does not provide a full participant-flow account that reconciles those figures.

The record does not report the original sample-size justification, the full prespecified statistical analysis plan, interim analyses, a multiplicity strategy, or the detailed methods used to calculate the confidence interval and p-value. It also does not give a clinical-importance threshold for CAL change. These omissions limit appraisal of the precision, robustness, and clinical meaning of the primary result.

Numerical results are not reported for every listed secondary outcome, and the adverse-event summary is not split by treatment group. Follow-up results are presented at the 12-month visit for the primary and posted secondary comparisons; longer-term outcomes are not reported in the information available. These limits should be considered when interpreting the study’s scope and the conclusions that can be drawn from the registry record.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Emdogain Minimally Invasive Surgical Technique — NCT02551770.
• Registry record last updated 2019-10-17; status last verified 2019-10.
• Results first posted 2019-10-17.
• 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 record describes a completed randomized controlled study of scaling and root planing with Emdogain versus scaling and root planing without Emdogain for periodontitis. Enrollment was 51. The official title describes a split-mouth design, although the model is listed as parallel, and masking is listed as none.

The primary outcome was mean change in clinical attachment levels at the 12-month follow-up. The posted mean difference was -0.1 mm, with a confidence interval from -0.656 to 0.456 mm and an unadjusted p-value of 0.724. Five missing 12-month CAL values were replaced with values from 9-month follow-up.

Numerical secondary comparisons are posted for gingival margin and pocket probing depth. The record lists additional secondary outcomes without numerical results in the reported analyses. Overall adverse-event counts are given for all participants, without treatment-specific breakdowns. The original sample-size rationale, detailed analysis plan, multiplicity approach, and handling of possible within-participant dependence are not reported in the registry record.