Monitoring Anti-Dementia Drugs by Serum Levels: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Monitoring Anti-Dementia Drugs by Serum Levels (NCT04117178), a randomized phase 4 study. The primary outcome is Change of Mini Mental State Examination (MMSE) Test Result.

2. Clinical Question

3. Trial Design

MONANTI (NCT04117178) is recorded as a completed, randomized, parallel-group, single-masked phase 4 study sponsored by Zealand University Hospital. The registry lists enrollment of 132. The study dates recorded are a start date of 2020-02-04 and a primary completion date of 2023-02-16. Those dates and the completed status describe the registry record; they do not provide details about recruitment pace, follow-up completeness, or whether every participant completed the planned assessments.

The clinical strategy under study was to use measured serum concentrations to inform anti-dementia medication management, with donepezil and memantine named in the study description. The intervention arm was asked to report side effects up to 2 months after prescription, with treatment adjustment according to serum level if side effects occurred. The standard-care arm followed usual outpatient dementia clinic routines and was requested to have a serum-level measurement after 12 months. The registry also says CYP2D6, BcHE K, and APOe4 status would be determined after 12 months in that arm. The description of the intervention arm is incomplete in the registry record, so the exact management pathway for all participants is not fully specified.

Single masking is recorded, but the identity of the masked parties is not reported in the registry record. Details of sequence generation, allocation concealment, protocol deviations, adherence to assigned management, and any crossover between approaches are also not reported. The trial’s original sample-size justification and its planned statistical analysis are not reported in the registry record. These omissions limit how fully the design and risk of bias can be assessed from the registry information alone.

The primary endpoint was change in MMSE score at the 1-year follow-up. The posted primary results include group means and standard deviations for 49 participants in standard care and 58 in the intervention arm. The relation of these outcome denominators to the registry enrollment figure, including why they differ, is not reported in the registry record. The registry lists secondary outcomes concerning clinical global impression, depressive symptoms, disability, neuropsychiatric symptoms, and genetic or phenotype measures.

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 Change of Mini Mental State Examination (MMSE) Test Result, measured over 1 year (enrollment in study and at 1-year follow-up).

The primary endpoint is change in Mini Mental State Examination (MMSE) score between enrollment and the 1-year follow-up. The MMSE is a widely used brief clinical assessment of cognitive function. The registry describes its total score as ranging from 0, worst, to 30, best. The posted outcome is expressed as a mean change in MMSE units, with a standard deviation describing the spread of individual changes within each arm.

Change scores address how the measured score moved over the follow-up period, rather than simply comparing group averages at one visit. The randomized comparison then focuses on the difference between the average changes in the two arms. In this study, the posted mean change was -0.27 in standard care and -0.9 in the intervention arm, giving an estimated mean difference of -0.63 for intervention relative to standard care.

MMSE is used as a brief, standardized measure of cognitive function, making it a way to quantify one aspect of the study’s intended clinical question. It does not capture every dimension of dementia or everyday functioning. The registry includes other outcomes, such as disability and clinical global impression, that address related but distinct domains. The registry record does not report a clinically important difference threshold for MMSE, nor does it explain how the endpoint was selected as primary or how change was analyzed beyond posting means and standard deviations.

7. Results Posted in the Registry

• Intervention Arm: mean -0.90 versus -0.27 on control; difference -0.63 (95% CI -1.91 to 0.65), standardized effect d = -0.19; z-test p = 0.335.

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 of Clinical Global Impression (CGI) Score Result

• 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:
  • Intervention Arm: mean 4.62 versus 4.68 on control; difference -0.06 (95% CI -0.44 to 0.32), standardized effect d = -0.06; z-test p = 0.760.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Intervention Arm and the control. The interval gives the range of effects that remain compatible with the data.

Change in Geriatric Depression Scale (GDS) Symptoms Score

• 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:
  • Intervention Arm: mean 0.79 versus -0.57 on control; difference 1.36 (95% CI 0.41 to 2.31), standardized effect d = 0.54; z-test p = 0.005.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Intervention Arm than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change of Disability Assessment for Dementia (DAD) Score Result

• 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:
  • Intervention Arm: mean -0.10 versus -0.07 on control; difference -0.03 (95% CI -0.08 to 0.02), standardized effect d = -0.20; z-test p = 0.285.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Intervention Arm and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes broaden the clinical picture beyond cognitive test performance. They address clinical global impression, depressive symptoms, disability, neuropsychiatric symptoms, and genetic or phenotype measures. Numeric arm-level results are posted for clinical global impression, Geriatric Depression Scale symptoms, and Disability Assessment for Dementia. The registry lists six secondary outcomes in all, but numeric results for the remaining listed outcomes are not reported in the registry record.

Across the outcomes with numeric summaries, the pattern is not uniform. The comparisons differ in direction, size, and uncertainty. This means the secondary results do not form a single consistent signal that can simply be combined with the primary MMSE result. They instead describe distinct outcome domains, each with its own scale and measurement properties. A result on a depression symptom scale, for example, is not a direct substitute for a cognitive test result or a disability measure.

The primary MMSE comparison remains the main randomized endpoint, and its interval includes zero. Secondary outcomes can add context, but they do not change the interpretation of the primary estimate or establish an effect on the primary endpoint. One secondary comparison has a low unadjusted p value, but a nominal result should not be treated as independently confirmatory without knowing how many outcomes and analyses were considered and whether a multiplicity approach was planned.

Multiplicity arises when many outcomes or comparisons are tested: even if there are no real effects, the chance of at least one apparently unusual result can increase. The registry does not report adjustment for multiple comparisons, a hierarchy among secondary endpoints, or a prespecified strategy for interpreting them. Accordingly, unadjusted secondary results carry less weight than a prespecified primary comparison, particularly when results across domains are mixed and some listed outcomes lack posted numerical results.

The record also does not give enough information to assess whether these outcomes were measured and analyzed for all participants or how missing assessments were handled. Secondary findings should therefore be viewed as descriptive and hypothesis-generating in this registry record, rather than as a definitive account of every potential benefit or harm relevant to the study question.

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

• Change of Clinical Global Impression (CGI) Score Result
• Change in Geriatric Depression Scale (GDS) Symptoms Score
• Change of Disability Assessment for Dementia (DAD) Score Result
• Change of Neuropsychiatric Inventory Questionnaire (NPI-Q) Score Result
• C2D6 Phenotype
• Genetic Test for BcHE K Variant

9. Statistical Interpretation

10. Statistical Methods Explained

General statistical explanation: A mean summarizes the average value in a group. For a change outcome, it represents the average change recorded among the participants included in that group’s posted summary. A standard deviation describes how dispersed individual observations are around that mean; it is not the same thing as uncertainty in the mean or uncertainty in the between-group comparison. The MMSE standard deviations were 3.19 in standard care and 3.56 in the intervention arm.

The comparison of interest is the difference between the arm means, expressed as intervention minus standard care. For MMSE, the posted estimate is -0.63. A negative estimate means the intervention arm’s average change was lower on the recorded change scale than the standard-care arm’s average change. This direction alone does not establish an important clinical effect: interpretation also depends on uncertainty, endpoint meaning, and a clinically meaningful threshold, which is not reported in the registry record.

General statistical explanation: A confidence interval presents a range of values compatible with the estimate under the assumptions of the method used. It communicates uncertainty about the estimated group difference; it is not a range containing a stated proportion of individual participants’ outcomes. For MMSE, the posted interval includes zero. Thus, the data do not rule out no average difference, and they are also compatible with effects in either direction. The confidence level and exact method used to form the posted interval are not reported in the registry record.

The posted unadjusted p value for MMSE is 0.335. A p value describes how unusual data at least as incompatible with a null hypothesis would be under that hypothesis and the assumptions of the analysis. It is not the probability that the null hypothesis is true, and it does not measure the size or clinical importance of an effect. Because the registry does not report the investigators’ analysis, this p value should be read as an unadjusted result associated with the posted summary comparison, not as evidence that a particular prespecified model was used.

General statistical explanation: Adjustment can account for prespecified covariates or design features, while an unadjusted comparison uses the observed group summaries without such modeling. The record does not provide adjusted comparisons, covariate choices, or a description of the primary analysis. It therefore does not show whether adjustment would materially change the estimate or its uncertainty. Randomization is intended to support a fair comparison of assigned groups, but it does not remove the importance of understanding missing outcomes, adherence, and the actual analysis population.

Standard deviations are reported for each arm, and the posted comparison also includes a pooled standard deviation of 3.396. Pooling is a way of summarizing within-group variability across groups for a standardized comparison. The record also posts a standardized effect estimate, d, of -0.185. This expresses the estimated difference in units of pooled variability, rather than in MMSE points. Such standardized measures can aid comparisons across scales, but they do not replace the original-scale estimate or establish clinical importance.

General statistical explanation: Over-dispersion matters when the variability in observed data is greater than an analysis model assumes. If variability is underestimated, standard errors may be too small and intervals too narrow; if it is modeled appropriately, uncertainty can be better represented. The primary endpoint is continuous and the registry reports means and standard deviations. It does not report diagnostics for distributional assumptions, an assessment of outliers, or a model addressing non-normality. No claim about whether over-dispersion was present can be made from the posted summaries.

The registry’s record of zero reported analyses means there is no investigator-reported analysis description attached to the posted outcome information. Details such as whether the main comparison was adjusted, how baseline scores were handled, how missing follow-up scores were treated, and which participants were included in each analysis are not reported in the registry record. These matters can affect the interpretation of change scores and the uncertainty around group contrasts.

Secondary outcomes include continuous measures with posted group means, standard deviations, mean differences, intervals, and unadjusted p values for some measures. The same basic reading applies: a mean difference gives the scale-specific direction and magnitude; its interval conveys uncertainty; and the p value is not a measure of clinical importance. The record lists six secondary outcome names, but numeric group summaries are posted for only three of them. The analysis approach and any prespecified hierarchy among these outcomes are not reported.

The study is randomized, but the registry does not report the randomization method, concealment details, or identity of the masked party. Nor does it report whether there were interim analyses or stopping rules. Those features should not be inferred from the randomized, single-masked, parallel design labels. Similarly, the reported comparisons should not be assumed to have been prespecified exactly as recalculated from the posted summaries.

11. Confidence Intervals and Precision

The primary MMSE estimate is -0.63 units. Its posted interval runs from -1.91 to a value above zero, so the interval crosses the null value of zero. This is an important precision feature: the estimate alone points in one direction, but the interval indicates that the data do not pin down the true average difference closely enough to exclude no difference. The upper endpoint is positive, while the lower endpoint is negative.

The interval is also relevant to the possible size of the effect. It includes values more negative than the point estimate as well as values on the other side of zero. That breadth means the posted result remains compatible with uncertainty about both direction and magnitude. The registry does not provide a clinically important MMSE difference threshold, so it is not possible to determine from the interval whether all values it covers would be clinically negligible or important.

The standard deviations of the observed changes were 3.19 for standard care and 3.56 for the intervention arm. These describe variability among observations, while the confidence interval concerns uncertainty in the between-group estimate. Confusing these quantities can make a result appear more or less precise than it is. The group summaries report 49 participants for standard care and 58 for the intervention arm, but the registry does not explain the relation of these outcome denominators to enrollment or report how missing outcomes were handled.

The p value of 0.335 is consistent with the interval’s inclusion of zero, but the interval offers more information about plausible effect sizes than a threshold-based reading of the p value alone. The confidence level, interval method, and investigator-reported inferential analysis are not reported in the registry record. The interval should therefore be interpreted as the posted uncertainty summary, without assuming additional methodological details.

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 figures are planning illustrations based on the observed effect, not the trial’s original design calculation. The registry’s original sample-size assumptions and justification are not reported in the registry record. For these illustrations, 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 set to the stated fraction of the observed effect. The figures are participants per arm, not total participants or total events.

The 80% power column describes the planned number of participants in each arm for a hypothetical study to have an 80% chance of detecting the specified effect under the planning assumptions, if that effect were the true one. The 90% power column uses a higher chance of detecting that same effect and therefore requires more participants per arm. These are design calculations, not a report of what happened in MONANTI.

Rows for planning for 100%, 75%, and 50% of the observed effect illustrate how the target effect changes the required enrollment. A smaller target effect is harder to distinguish from random variation, so the calculation calls for more participants per arm to reach the same planned power. For the MMSE comparison, the displayed figures are 457 and 611 participants per arm when planning for 100% of the observed effect; 811 and 1,086 when planning for 75%; and 1,825 and 2,443 when planning for 50%. In each pair, the first figure is for 80% power and the second for 90% power.

These calculations use the effect estimated from the posted results, which is uncertain and may not represent the effect that a future study should target. They are not observed power: they do not describe the probability that the completed trial detected its true effect. They are prospective illustrations under stated assumptions, and do not establish that the completed study was designed using those assumptions.

13. How the Sample Size Is Derived

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

Formula

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

Worked calculation for this trial

1. Observed difference Δ = -0.630; pooled standard deviation σ = 3.396.
2. n = 2 × (1.96 + 0.842)² × 3.396² / -0.630² = 456.1, rounded up to 457 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 <- -0.63                      # observed difference in means
sigma <- 3.39586302937644                     # 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(4117178)
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 = 457 (80% power), 611 (90% power)
 75% of observed effect: n per arm = 811 (80% power), 1,086 (90% power)
 50% of observed effect: n per arm = 1,825 (80% power), 2,443 (90% power)
power.t.test: 457.1 
Simulated power at n = 457 per arm: 0.795 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Multiplicity, Missing Data and Analysis Populations

The registry lists a primary endpoint and multiple secondary outcomes, but it does not report a multiplicity plan. In particular, it does not state whether the investigators adjusted for testing multiple outcomes, used a hierarchy, or designated some secondary results as exploratory. This matters because repeated testing can increase the chance that at least one result appears statistically notable by chance. The unadjusted p values should therefore not be interpreted as if they came from a single isolated test unless the analysis plan establishes that context.

There are also important gaps concerning missing data. The registry does not report how incomplete follow-up was handled, whether analyses used complete cases or another approach, how many participants lacked each outcome, or whether sensitivity analyses were conducted. It does not provide reasons for missing outcome assessments. Since the posted MMSE summaries include 49 participants in standard care and 58 in the intervention arm, while enrollment is recorded as 132, the registry information does not explain the difference between enrollment and the outcome denominators. No inference about the cause of that difference is warranted.

The analysis population is not described. The record does not say whether the reported summaries correspond to an intention-to-treat population, a per-protocol population, or another defined group. It also does not report how participants who did not follow their assigned management were treated analytically. Without this information, it is difficult to assess how well the posted comparison preserves the randomized allocation or how sensitive it might be to exclusions and nonadherence.

The record lists no reported statistical analyses. Details of covariate adjustment, baseline-score handling, model choice, assumption checks, confidence-interval construction, and prespecified contrasts are not reported. Interim analyses, stopping rules, and any changes to the analysis plan are also not reported in the registry record. These are reporting limitations; they do not demonstrate that the study lacked such procedures, only that they are not documented in the registry information available.

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: psychosis (1.5%), death (1.5%), donepezil overdose (1.5%), hospitalization due to headache (1.5%), death due to lung cancer with metastases (1.5%).

The registry reports serious adverse event figures separately for standard care and the intervention arm. The at-risk counts are 65 and 67, respectively; the reported serious adverse event counts are 6 and 7, and deaths are recorded as 2 in each arm. Other adverse event counts are 42 and 46, respectively. These are descriptive registry figures and should be read with their reported at-risk groups, rather than interpreted as a comparative safety analysis.

The record lists serious event terms including psychosis, death, donepezil overdose, hospitalization due to headache, death due to lung cancer with metastases, and antebrachium fracture. Each listed term is shown as 1.5%. The record does not provide enough detail to determine from these figures whether terms refer to unique participants, repeated events, or overlapping categories. It also does not report an adjusted comparison, exposure-time analysis, or an assessment of whether events were caused by study management.

Counts alone do not establish that one arm was safer than the other. Interpretation depends on the definition and collection of events, follow-up and exposure, participant characteristics, and a prespecified comparative analysis. Those details are not reported in the registry record. The figures describe recorded adverse events; they are not, by themselves, evidence of a causal safety difference.

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

The primary result describes average MMSE change in the two randomized arms over the stated follow-up. The estimated difference was -0.63 units for intervention relative to standard care, and the interval includes zero. This supports a cautious reading: the posted summaries do not establish a clear average difference in MMSE change. The result should not be converted into a claim that the approaches are identical, because no difference and equivalence are different statistical questions.

The result also does not establish whether a difference, if present, would matter to patients. The registry describes the MMSE scale but does not report a threshold for clinical importance. A statistical estimate in scale units needs clinical context to judge importance, and that context cannot be inferred from the point estimate or p value alone.

The study rationale includes serum concentrations, treatment adjustment, side effects, compliance, medication interactions, and clinical outcomes. The posted MMSE comparison addresses only one outcome dimension. The registry record does not provide complete numerical results for all listed secondary outcomes or enough detail to assess each part of the rationale. The posted adverse event counts likewise do not demonstrate a causal safety difference.

Randomization is an important feature for comparing assigned groups, but the available registry information does not describe the analysis population, missing-data methods, adherence, or adjustment. These omissions limit how strongly the outcome summaries can be interpreted as causal estimates of the full management strategy. The result is best understood as the recorded arm-level comparison, with uncertainty and reporting limitations made explicit.

Nothing in these registry results should be read as medical advice or as proof that serum-level monitoring should or should not guide an individual’s treatment. The study record provides a statistical description of a particular randomized comparison. Decisions about care require clinical judgment and evidence beyond the numerical summaries in this record.

17. Why This Trial Matters Statistically

This trial is statistically relevant because it evaluates a management strategy rather than only comparing two drug products. The intervention uses measured serum concentrations to inform decisions, while the comparator is usual outpatient clinic care with a serum measurement requested after 12 months. Such a strategy raises several connected questions: whether measurements change management, whether treatment changes affect clinical outcomes, and whether any differences can be distinguished from random variation.

The primary result illustrates why an estimate should be read alongside its uncertainty. The point estimate is negative, but the interval includes zero, and the unadjusted p value is 0.335. Reporting only the direction of the group means would omit the central issue: the observed comparison is not precise enough to establish a clear difference. Conversely, the result does not prove that no meaningful difference exists.

The secondary outcome pattern also makes the study a useful example of multiplicity. Several clinical domains are listed, while only some have numeric summaries, and a secondary comparison has an unadjusted p value of 0.005. Without a documented plan for handling multiple outcomes, an isolated low p value warrants caution. A sound interpretation considers the full outcome set, the prespecified role of each measure, and uncertainty rather than emphasizing a single result.

The registry record also demonstrates the importance of transparent methods reporting. It records randomization and masking labels and provides group summaries, but does not report the analysis population, missing-data approach, original sample-size justification, or detailed analysis plan. Those omissions matter because they affect the assessment of precision, bias, and the strength of conclusions that can be drawn from posted results.

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 registry description of the intervention arm is incomplete: its text ends while describing participants who did not experience side effects. As a result, the full management protocol cannot be reconstructed from the registry record. The record also does not identify who was masked, or give details of randomization and allocation concealment. These gaps make it harder to judge how consistently the intervention was delivered and how expectations might have affected assessments.

The study spans different dementia conditions, including Alzheimer disease, dementia with Lewy bodies, and dementia in Parkinson’s disease, but detailed eligibility criteria and participant characteristics are not reported in the registry record. It is therefore not possible to assess how the enrolled population was distributed across diagnoses or how broadly the posted result applies across those groups. The drug names are stated in the study rationale, but arm-level drug use and results by medication are not reported.

The primary outcome summaries include 49 participants in standard care and 58 in the intervention arm, whereas enrollment is recorded as 132. The registry record does not explain this difference or provide outcome-specific missingness, reasons for attrition, or the analysis population. It also does not report adherence, treatment changes, or whether participants crossed between management approaches. These unknowns limit assessment of selection effects and the interpretation of the randomized comparison.

Finally, the registry lists six secondary outcomes but posts numeric arm-level summaries for only three, and it provides no reported analyses. The original sample-size calculation, multiplicity strategy, and clinically important threshold for MMSE are not reported. These limitations leave uncertainty about both the robustness of the findings and how the observed magnitudes should be judged clinically.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Monitoring Anti-Dementia Drugs by Serum Levels — NCT04117178.
• Registry record last updated 2025-02-10; status last verified 2023-07.
• Results first posted 2025-02-10.
• 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

MONANTI (NCT04117178) is recorded as a completed, randomized, single-masked, parallel-group phase 4 study with enrollment of 132. It compared serum-level-informed anti-dementia drug management with standard outpatient dementia care. The primary endpoint was change in MMSE score at the 1-year follow-up.

The posted MMSE mean difference was -0.63 units for intervention relative to standard care, with an interval that includes zero and an unadjusted p value of 0.335. This does not establish a clear difference in average change. The registry lists secondary outcomes and adverse event counts, but analysis details, missing-data handling, and the original sample-size justification are not reported in the registry record.