New Patient Support Program in Type 2 Diabetes: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for New Patient Support Program in Type 2 Diabetes (NCT03752567), a registered phase not stated study. The primary outcome is Percent of Participants With Adherence to the PDTA.

2. Clinical Question

The study focuses on a service-delivery model rather than a randomized assignment to competing treatments. The intervention description places the community pharmacist in a case-management role and mentions telemedicine procedures, including ecg, fundus oculi, and ankle arm index, as well as self-analysis including glycated hemoglobin, lipid profile, and uric acid. These details describe activities, not evidence that each participant completed each activity.

The central statistical challenge is that the primary question invokes a historical comparison while the registry record does not supply the historical cohort details or outcome values. Without those data, the size and precision of any difference cannot be assessed, and observed change cannot be attributed to case management alone. The record lists secondary outcomes concerning waiting time, arterial pressure, HbA1c, LDL-cholesterol, and economic impact, but does not report their results.

3. Trial Design

The registry describes a completed, non-profit observational study of community-pharmacist case management for people with type 2 diabetes. The sponsor is Farmacia La Regina s.r.l. The listed study start date is 2018-11-01, and the primary completion date is 2019-10-31. Enrollment is recorded as 40. The listed intervention is “Follow up,” classified as “OTHER.”

The study group is described as receiving follow-up for 12 months from a community pharmacist acting as case manager. The description refers to activities in an individual assistance plan, with checks available through telemedicine and self-analysis. It names ecg, fundus oculi, ankle arm index, glycated hemoglobin, lipid profile, and uric acid. The registry description ends during its account of these activities, so details beyond the recorded text are not reported in the registry record.

The primary outcome is framed as a comparison with a historical cohort. The study is not described as randomized, and allocation is not stated. The historical cohort's enrollment, selection, follow-up, and measurement procedures are not reported in the registry record. As a result, this design does not offer the like-for-like control comparison that randomized allocation is intended to support. Differences between the study group and a historical cohort could reflect differences in populations, care practices, or measurement, as well as the case-management model.

The record lists 6 outcome measures and 0 analysis entries. Those registry fields do not establish whether analyses were conducted outside the record; they indicate that outcome analysis results are not posted as registry analysis entries. The study is marked COMPLETED, but that status alone does not show that every participant completed follow-up or that every planned assessment was available.

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: None of the enrolled patients were excluded from the ongoing trial. All patients completed the entire observation period.

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.

Population: Study participants were assigned the whole study group.

6. Primary Endpoint

The registry lists the primary outcome as Percent of Participants With Adherence to the PDTA, measured over 12 months.

The primary endpoint is the percentage of participants with adherence to the PDTA. The description defines adherence in terms of patients who performed the checks scheduled at 3, 6, and 12 months, divided by the total number of enrolled patients and expressed as a percentage. The endpoint is assessed at 12 months and is intended to measure variation compared with a historical cohort.

In general, a percentage endpoint can make completion of a planned care pathway easier to interpret than a count alone, because it relates the number meeting the definition to the enrolled population. Here, the chosen endpoint represents whether scheduled checks were performed; it is not itself a direct measure of glycemic control, cardiovascular risk, quality of life, or clinical events. The record lists HbA1c, arterial pressure, and LDL-cholesterol among secondary outcomes, but does not report their results.

Adherence measures can be useful for evaluating whether a service model is associated with delivery of planned monitoring. Their interpretation depends on a clear definition of the eligible denominator, how missed or unavailable assessments are handled, and whether the same rules are applied to the historical cohort. Those details, along with the observed adherence percentage and historical comparison, are not reported in the registry record. Therefore, the stated endpoint identifies the question being asked, but does not establish the outcome observed.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

Statistical methods matter because they determine how an observed outcome is summarized, compared, and interpreted. In this study, the record gives a definition for the primary endpoint but does not report an analysis method or analysis result. The following concepts explain what would ordinarily be relevant to an adherence comparison; they are general statistical explanations, not claims about methods used in this study.

What does the adherence percentage represent?

A percentage is a proportion expressed on a percentage scale. Its interpretation depends on defining who is counted as adherent and who is included in the denominator. The primary outcome description refers to participants who performed checks scheduled at 3, 6, and 12 months, relative to all enrolled patients. It does not clarify whether adherence requires completing every scheduled check, whether completion of any one check qualifies, or how missed assessments are classified. Those operational rules are not reported in the registry record.

For a percentage to be comparable across cohorts, the definition and data-collection process need to be consistent. If one cohort has more complete records, or uses a different definition of a completed check, its apparent adherence can differ for measurement reasons. The record does not report how the historical cohort was assembled or whether its ascertainment matched that of the study group.

Why does a historical comparison need caution?

A historical cohort is observed in an earlier period rather than recruited and followed concurrently under randomized assignment. General statistical reasoning therefore treats such comparisons as vulnerable to differences in case mix, background care, access, documentation, and other changes over time. These differences can influence the outcome and may be difficult to separate from the service model's association with adherence.

Randomization, when used, aims to balance measured and unmeasured characteristics between groups on average. This study is described as observational, and allocation is not stated. The record does not report adjustment variables, matching, stratification, or other approaches that might address differences between the study group and the historical cohort. It would be inappropriate to assume that any such method was used.

What does uncertainty add?

An estimate describes the result in the observed data. A confidence interval expresses statistical uncertainty around that estimate under the chosen model and its assumptions. A narrow interval generally indicates greater precision, while a wide interval indicates that a broader range of effects remains compatible with the data. An interval is not a guarantee that the true effect lies within it, and it does not resolve bias from a non-comparable historical cohort.

The registry record does not report an adherence estimate, a confidence interval, or a statistical test for the primary comparison. Accordingly, neither the direction nor the precision of the comparison can be assessed. A p-value, if available, would address compatibility with a specified statistical null model; it would not by itself convey the size, practical importance, or causal credibility of a difference.

What does over-dispersion mean in general?

Over-dispersion occurs when observed variability is greater than a statistical model assumes. It can arise when participants differ more than expected, when outcomes cluster, or when the model omits relevant structure. If over-dispersion is ignored in an analysis that assumes less variability, uncertainty may be understated. This is a general consideration for modelling proportions or counts; the registry record does not report a model or an over-dispersion assessment for this study.

How should planning illustrations be read?

The planning assumptions describe an illustration based on the observed effect, using a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation; the effect to detect is described as a stated fraction of the observed effect. These are assumptions for a planning illustration, not evidence that the trial was designed or conducted using that plan. The record does not report that this observational study used equal allocation or had two randomized arms.

Sample-size calculations are planning tools: they show how a proposed design might perform under specified assumptions. They are not “observed power,” and they do not demonstrate that a result is reliable. Their relevance depends on the effect size, outcome variability, allocation, analysis method, and other assumptions being appropriate. In this case, the record identifies the illustration's general assumptions but does not report the trial's own statistical plan or a primary-outcome estimate in the analysis entries. The illustration therefore cannot replace an estimate with uncertainty from the study itself.

More broadly, statistical methods can quantify sampling uncertainty, but they cannot repair missing outcome information or remove all limitations of a historical comparison. Interpretation needs the endpoint definition, observed data, analytic approach, and an assessment of cohort comparability. Much of that information is not reported in the registry record.

10. Multiplicity, Missing Data and Analysis Populations

The registry lists 6 outcome measures. The primary measure concerns adherence to the PDTA; secondary outcomes concern waiting time, arterial pressure, HbA1c, LDL-cholesterol, and economic impact. The record does not report results for these outcomes or an analysis plan specifying which comparisons were confirmatory, how multiple outcomes were handled, or whether any adjustment for multiplicity was planned. These details are not reported in the registry record.

In general, examining many outcomes or comparisons creates more opportunities for apparently notable findings to arise by chance. Statistical approaches to multiplicity can control error rates or otherwise make the interpretation of a family of tests more cautious. The appropriate approach depends on the study's aims and prespecified analysis plan. No approach should be attributed to this study from the outcome list alone.

The record lists 0 analysis entries. That is a statement about analyses posted in the registry, not proof that investigators conducted no analyses. The study's statistical analysis plan, outcome-specific denominators, and any adjustment methods are not reported in the registry record.

Missing data are also important for an adherence endpoint. Participants may have incomplete records or may not have completed each scheduled check. General approaches include defining how missing assessments affect the endpoint and examining whether conclusions change under plausible assumptions. The registry record does not describe missing-data rules, follow-up completeness, or sensitivity analyses. It also does not define analysis populations, such as whether the primary calculation uses everyone enrolled or only those with recorded follow-up. Although the endpoint description refers to the total number enrolled, the actual denominator and treatment of missing observations are not reported.

Without these details, readers cannot determine how incomplete assessments were handled, whether the analysis population differed from enrollment, or how multiplicity may affect interpretation of any unposted results.

11. 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: description (0.0%).

The serious adverse event record lists 40 participants at risk in the study group and 0 with a serious adverse event. It also lists 40 at risk for the “other” adverse-event category and 0 affected. Deaths are recorded as 0, and the top serious-event terms entry is 0.0%.

These are the registry's recorded counts for the categories shown. They should not be interpreted as proof that no adverse events of any kind occurred. The figures concern serious adverse events and the separately listed “other” category, and the record does not provide event descriptions beyond the displayed summary. It also does not report the method used to collect or verify events, the completeness of reporting, or whether events were assessed as related to the intervention.

A zero recorded count does not establish that the underlying risk is zero. In general, event counts are interpreted in light of the number observed, follow-up, and how completely events were ascertained. The record's 12-month follow-up description does not establish that every participant contributed complete safety follow-up. No further safety interpretation is possible from the posted figures alone, and the counts do not determine whether the case-management model is safe or unsafe.

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

The record describes a community-pharmacist case-management study in people with type 2 diabetes and identifies adherence to scheduled checks as its primary endpoint. The endpoint is intended to be compared with a historical cohort, with follow-up described over 12 months. The record also names several secondary outcomes and reports a completed study status.

What the record does not establish is the observed adherence percentage, the historical cohort's percentage, or the difference between them. It therefore does not show whether adherence was higher, lower, or similar in the study group, nor how precise a comparison might be. Results for the secondary outcomes are also not reported in the registry record. The listed safety counts describe recorded serious events and deaths, but do not by themselves establish the completeness of safety surveillance or the overall safety profile.

In general, observational findings can identify patterns and support evaluation of service delivery, but a historical comparison is susceptible to changes in participants, care, and measurement over time. A numerical association, if reported, would not automatically demonstrate that case management caused the difference. Statistical adjustment may address some measured differences, but the registry record does not report an analysis plan or adjustment methods.

The primary endpoint is a measure of completion of planned checks, not a direct measure of disease control or patient health. Although HbA1c, arterial pressure, and LDL-cholesterol are listed as secondary outcomes, their results are absent. Thus the record does not establish effects on these measures, on economic impact, or on clinical outcomes.

The defensible interpretation is that the registry documents a service model and its intended evaluation question, but lacks the outcome analyses needed to answer that question. The absence of posted results is not evidence that the intervention had no effect; it means that the direction, magnitude, precision, and practical importance of any effect cannot be evaluated from the registry record.

13. Why This Trial Matters Statistically

This study raises an important statistical distinction between evaluating whether a care process was completed and evaluating whether health outcomes changed. The primary endpoint focuses on adherence to scheduled checks. Such a process measure can help describe how a service model is delivered, but it does not by itself establish improvement in disease control or other health outcomes.

The historical-cohort framing also highlights the role of the comparison group. A percentage can be calculated clearly, yet its interpretation depends on whether the cohorts were comparable and whether the endpoint was measured in the same way. Observational comparisons can be informative, but differences over time and between populations complicate causal interpretation. The registry record does not provide enough information to assess those issues or quantify the comparison.

The listed secondary outcomes broaden the evaluation to waiting time, arterial pressure, HbA1c, LDL-cholesterol, and economic impact. Considering several domains can be useful, while also making a prespecified analysis plan and transparent reporting important. The registry record lists these outcomes but does not report their analyses or results.

Finally, the record illustrates why study status and enrollment alone are not substitutes for statistical results. A completed study with a defined endpoint still requires reported estimates, denominators, uncertainty, and analysis methods for readers to judge what the data indicate. With 0 analysis entries, the registry record documents the question and design description but leaves the principal statistical comparison unanswered.

14. 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 specific to this record restrict interpretation. First, the study is observational, with allocation not stated and no randomized comparison described. The primary endpoint invokes a historical cohort, but information about that cohort's size, selection, characteristics, time period, and measurement procedures is not reported in the registry record. Comparability therefore cannot be assessed.

Second, the registry does not report the observed primary adherence percentage, the historical comparison value, an effect estimate, a confidence interval, or a test result. Secondary outcome results are also not reported. The record lists 0 analysis entries, so the posted information does not permit evaluation of statistical significance, precision, or outcome-specific findings.

Third, the endpoint's description does not fully clarify how adherence was classified when some scheduled checks were completed but others were missed. Rules for incomplete assessments, missing data, and the analysis population are not reported in the registry record. These details can affect both the denominator and the interpretation of the adherence percentage.

Fourth, the record does not report a statistical analysis plan, methods for addressing differences between cohorts, handling of multiple outcomes, or sensitivity analyses. These omissions leave uncertainty about how the intended comparison would be estimated and how robust any result might be.

Finally, the registry describes a 12-month follow-up and lists an enrollment of 40, but does not report participant characteristics, follow-up completeness, or endpoint-specific denominators. The listed safety counts are not accompanied by details on event ascertainment. The study's COMPLETED status does not resolve these limitations or supply the missing outcome results.

15. Related Tutorials

16. Related Statistical Calculators

17. Sources

• ClinicalTrials.gov: New Patient Support Program in Type 2 Diabetes — NCT03752567.
• Registry record last updated 2020-02-12; status last verified 2020-02.
• Results first posted 2020-02-12.
• 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.

18. Record Summary

NCT03752567 is a completed, non-profit observational study titled “New Patient Support Program in Type 2 Diabetes.” It lists Farmacia La Regina s.r.l. as sponsor, enrollment of 40, and study dates from 2018-11-01 to primary completion on 2019-10-31.

The study describes community-pharmacist follow-up for 12 months, with the pharmacist acting as case manager. Its primary outcome is the percentage of participants adhering to the PDTA, compared with a historical cohort. The record lists secondary outcomes for waiting time, arterial pressure, HbA1c, LDL-cholesterol, and economic impact.

The registry reports 0 analysis entries and does not report the primary or secondary outcome results. It records 0 serious adverse events and 0 deaths in the study group. The posted information describes the study question and service model, but does not provide the numerical analyses needed to evaluate outcome differences or their precision.