Managing Asthma Patients With AMAZE™: A Novel Disease Management Platform: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Managing Asthma Patients With AMAZE™: A Novel Disease Management Platform (NCT04868500), a non-randomized na study. The primary outcome is Number of Days Participants Accessed the AMAZE™ App (Weeks 1 to 4).

2. Clinical Question

3. Trial Design

NCT04868500 is a completed clinical pilot study titled “Managing Asthma Patients With AMAZE™: A Novel Disease Management Platform.” It concerns asthma and lists AstraZeneca as the sponsor. The registry record gives a study start date of 2021-04-27 and a primary completion date of 2021-11-30. Enrollment is listed as 49. The phase is recorded as not applicable.

The design is described as non-randomized, unmasked, and parallel. Participants and clinical site staff at Massachusetts General Hospital (MGH) had different roles. Participants were to use the AMAZE™ application to enter daily asthma symptoms and impact, communicate this information to their healthcare provider, and access educational materials for up to six months. Clinical site staff were to use the AMAZE™ dashboard for six months to assess usability and barriers, benefits, challenges, ease of implementation, and areas for improvement.

These groups do not constitute a like-for-like treatment and control comparison. They used different platform components and contributed different kinds of information. The participant group’s app-use outcome therefore describes use within the implementation study; it is not a randomized estimate of an effect relative to a control group. The registry record does not report a separate control condition or a randomized allocation process.

The primary outcome focuses on participants’ app access during Weeks 1 to 4, while the planned platform use described for participants and staff extends for up to six months. That distinction matters: an early measure of access does not by itself describe use over the full implementation period. The record lists 31 outcome measures but does not report analysis entries. It also does not report a sample-size justification or a detailed statistical analysis plan.

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

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: All eligible participants successfully enrolled in the implementation study were analyzed. Here, 'Number of Participants Analyzed' denotes number of participants who accessed the App for the specified time frame and 'Number Analyzed' denotes number of participants analyzed for the specified parameter.

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: All eligible participants who successfully enrolled in the implementation study were analyzed.

6. Primary Endpoint

The registry lists the primary outcome as Number of Days Participants Accessed the AMAZE™ App (Weeks 1 to 4), measured over Weeks 1 to 4.

The primary endpoint is the number of days participants accessed the AMAZE™ application during Weeks 1 to 4. The registry describes engagement as accessing one or more listed app areas: Home, the daily asthma log, air quality, My plan, Trends, Appointments, educational material, Messages, and Notifications. The measure is expressed in days, with the endpoint type recorded as a mean and its dispersion as a standard deviation.

This measure captures how often participants accessed the application over the specified early period. In an implementation study, observed access can help describe whether participants engaged with a digital platform after enrollment. It is a measure of app use, not a direct measure of asthma symptoms, health status, or clinical benefit. Accessing an app area also does not establish how thoroughly a participant used its content or whether use changed care.

The registry record does not report the primary endpoint’s mean, standard deviation, number analyzed, or number of participants who accessed the app for the specified time frame. Consequently, the observed level and variability of access cannot be described from the record. The endpoint is defined, but its numerical result is not reported in the registry record.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The primary endpoint is a continuous measure: the number of days participants accessed the application during Weeks 1 to 4. The registry describes the planned summary using a mean and standard deviation. A mean describes the average value in the analyzed data, while a standard deviation describes how spread out individual values are around that average. These summaries can make a continuous outcome easier to characterize, but they do not show every participant’s pattern of use.

What does the mean describe?

For this endpoint, the mean would summarize the average number of access days among participants included in the relevant analysis. It would not tell whether access was evenly distributed across participants. A similar mean could arise from relatively consistent use or from a mixture of frequent and infrequent use. The distribution of individual observations and the number analyzed would help readers judge how representative the mean is.

What does the standard deviation add?

The standard deviation describes variability among observed values. A smaller spread would indicate that participants’ access-day counts were more alike; a larger spread would indicate greater variation. It is not the same as the uncertainty in the estimated mean. That uncertainty is commonly described with a confidence interval, which gives a range of values compatible with the data under the assumptions of the analysis. The registry record does not report a confidence interval for this endpoint.

What would a confidence interval mean?

In general, a confidence interval communicates the precision of an estimate. A narrower interval indicates greater precision under the method used, while a wider interval indicates less precision. It does not eliminate uncertainty or guarantee that the true value lies within a particular interval. No interval for the primary endpoint is reported in the registry record, so its precision cannot be evaluated from the posted information.

Why does the analysis population matter?

The endpoint description refers to all eligible participants successfully enrolled as the population analyzed, and also distinguishes the number of participants analyzed from the number who accessed the app during the specified period. Those are important distinctions. The enrolled population, the population with outcome data, and the population meeting an engagement definition need not be identical. The registry record does not report the endpoint-specific counts or explain how participants without recorded access were handled. Enrollment alone cannot establish the denominator for an endpoint analysis.

Why is the design important?

Random allocation can support a comparison by making treatment assignment independent of participant characteristics on average. This study is recorded as non-randomized, and its participant and staff groups have different roles and use different platform components. They therefore cannot serve as an interchangeable intervention and control pair. Descriptive findings about app access can characterize implementation in the study setting, but they do not isolate an app effect from other influences.

What can be learned from a planning illustration?

Sample-size planning uses assumptions about the effect to detect, allocation, significance level, and statistical model to illustrate the amount of information a future study might need. Such a calculation is a planning illustration, not an observed study result and not observed power. The registry record does not report the study’s own sample-size justification. Any planning scenarios associated with the posted results should not be mistaken for evidence about the actual endpoint or the study’s design rationale.

How should multiple outcomes be considered?

When a study measures many outcomes, testing each one can increase the chance of finding an apparently noteworthy result by chance. Multiplicity methods can address that issue, but the appropriate approach depends on the prespecified questions and analysis plan. The record lists 31 outcome measures and no analysis entries; it does not report a multiplicity strategy. Without a documented plan and results, readers cannot determine how outcomes were prioritized or whether statistical testing was adjusted.

Why are missing-data details useful?

Missing outcome data can affect interpretation when participants with and without recorded observations differ in ways related to the outcome. Analyses may use assumptions or methods to address missingness, but those choices should be described. The registry record does not report endpoint-specific missing-data counts, reasons for missingness, or a missing-data method. This prevents assessment of how incomplete observations might influence the reported endpoint—whose numerical result is itself not reported.

10. Multiplicity, Missing Data and Analysis Populations

The registry record lists 31 outcome measures and no analysis entries. It does not report which outcomes, beyond the stated primary endpoint, were prioritized in the analysis, whether additional outcomes were treated as exploratory, or whether any method was used to account for multiple statistical tests. In general, assessing many outcomes can raise the chance of apparently notable findings arising by chance. Prespecified outcome hierarchy and multiplicity procedures help readers understand how results should be interpreted, but the registry record does not describe such a plan.

The primary endpoint description refers to eligible participants successfully enrolled and distinguishes the number analyzed from the number who accessed the app during the specified time frame. The endpoint-specific counts are not reported in the registry record. The record also does not explain how participants with no app access, incomplete records, or other unavailable endpoint data were handled. It does not report reasons for missing data, a missing-data assumption, or a method for addressing missing observations.

These omissions limit evaluation of the analysis population and the potential effect of incomplete data. In general, missingness can affect an estimate if availability of outcome data is related to participants’ app use or other relevant characteristics. The direction and extent of any effect depend on the actual pattern and handling of missing data; they cannot be inferred from the registry record. Enrollment is not a substitute for an endpoint-specific denominator, and the record does not provide enough information to assess whether the endpoint analysis represented all enrolled participants.

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

The registry record defines a practical, descriptive question: how many days participants accessed the AMAZE™ application during Weeks 1 to 4. The measure captures recorded access to app areas, not the quality or depth of engagement with them. It may provide information relevant to implementation, but app access by itself does not demonstrate that the platform was usable, valued by participants, or beneficial in clinical practice.

The record does not report the primary endpoint’s mean, standard deviation, or analysis counts. Readers therefore cannot determine the amount of access observed, how much access varied among participants, or how precise an estimate might be. The record’s completed status and enrollment figure do not fill that gap. Nor does the absence of a numerical result establish that app use was low, high, or absent.

The study’s design also constrains interpretation. It is non-randomized, and the participant and clinical site staff groups had distinct roles and platform components. The study does not provide a like-for-like control comparison in the registry record. Accordingly, the described endpoint cannot be read as a causal estimate of the application’s effect relative to a control condition.

The study’s broader objective includes feasibility, usability, perceived value, and potential benefits. A count of access days addresses only a narrow aspect of engagement and cannot establish all of those broader outcomes. The registry record does not report enough endpoint results or analysis detail to quantify implementation performance or assess a clinical effect. These are limits of what can be concluded from the posted registry information, rather than evidence for a particular outcome.

12. Why This Trial Matters Statistically

Implementation studies ask questions that are not identical to conventional treatment comparisons. A digital platform may be available in a clinical setting, but the practical question includes whether participants and staff engage with it and how it fits into care. This study’s focus on application access and staff use of a dashboard reflects that implementation context. Distinguishing those aims from a causal treatment-effect question helps keep statistical interpretation aligned with the design.

The primary endpoint is a clearly described measure of early app access, expressed as days during Weeks 1 to 4. Such a measure can be useful when evaluating engagement, but its meaning depends on the analysis population, the way access is recorded, and the distribution of use. A mean and standard deviation are intended summaries, yet the registry record does not report their values or the endpoint-specific counts. The absence of those results limits the statistical conclusions readers can draw.

The non-randomized design is also important. Participants and clinical site staff used different tools for different purposes, so their groups should not be treated as comparable arms for estimating a platform effect. This distinction is especially relevant when a study’s objective includes potential benefits: descriptive implementation evidence and causal evidence answer different questions.

Finally, the record lists many outcomes but no analysis entries and does not describe multiplicity or missing-data procedures. Clear reporting of outcome priorities, denominators, uncertainty, and analysis choices would help readers assess the strength and scope of implementation evidence. Without those details, the registry record supports understanding the study’s intended question and design, but not a numerical judgment about the primary endpoint.

13. 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 record does not report numerical results for the primary endpoint. In particular, the mean number of access days, standard deviation, endpoint-specific analysis count, and number of participants accessing the app during Weeks 1 to 4 are not reported in the registry record. This prevents assessment of the observed level and variability of early use.

The design is non-randomized, unmasked, and organized around participant and clinical site staff groups with distinct roles. There is no like-for-like control comparison reported in the registry record. This limits causal interpretation and means that differences between the groups would not provide a direct estimate of the effect of the application or dashboard.

The primary endpoint covers Weeks 1 to 4, while the described participant and staff use extends for up to six months. The early access measure therefore does not, by itself, characterize use throughout the full implementation period. The record does not report a longer-term numerical app-use result in the primary endpoint description.

The registry record lists 31 outcome measures and no analysis entries. It does not report how outcomes were prioritized, whether multiplicity was addressed, or how missing endpoint data were handled. Endpoint-specific denominators and reasons for unavailable data are also not reported. These gaps constrain assessment of precision, analysis-population representativeness, and the possible influence of missingness.

The study’s stated aims include feasibility, usability, perceived value, and potential benefits, but the primary endpoint is app access. Access alone cannot capture all of those concepts. The registry record does not report a sample-size justification or a detailed statistical analysis plan, so the rationale for the planned enrollment and analytical choices cannot be evaluated from this information.

14. Related Tutorials

15. Related Statistical Calculators

16. Sources

• ClinicalTrials.gov: Managing Asthma Patients With AMAZE™: A Novel Disease Management Platform — NCT04868500.
• Registry record last updated 2023-02-08; status last verified 2023-01.
• Results first posted 2023-02-08.
• 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.

17. Record Summary

NCT04868500 is a completed, non-randomized, unmasked parallel clinical pilot study of the AMAZE™ application and dashboard for asthma care. The record lists AstraZeneca as sponsor, enrollment of 49, and MGH participant and clinical site staff groups. Participants used the application to record symptoms and impact, communicate with healthcare providers, and access educational materials; staff used the dashboard in the clinical setting.

The primary endpoint is the number of days participants accessed the application during Weeks 1 to 4, summarized as a mean and standard deviation. The registry record does not report the endpoint result, its analysis counts, or a detailed statistical analysis plan. It lists 31 outcome measures and no analysis entries. Because the groups had different roles and the study was non-randomized, they do not form a like-for-like control comparison. The posted record describes the study question and design, but does not provide the numerical primary result needed to characterize app access.