Participant-Reported Outcomes With the Accu-Chek® Solo Micropump System: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Participant-Reported Outcomes With the Accu-Chek® Solo Micropump System (NCT03478969), a randomized na study. The primary outcome is Treatment Satisfaction: Accu-Chek® Micropump System vs. MDI, Measured by the Difference in the Diabetes Technology Questionnaire (DTQ) Total Change Score.

2. Clinical Question

The DTQ asks about diabetes technology and treatment experience. Its total change score ranges from 30 to 150; higher scores represent lower impairment and improved outcomes. This makes the primary measure a report of participants’ perceived treatment experience, rather than a direct measure of glucose control or a clinical event.

The study also included secondary measures, including diabetes-related emotional distress, device satisfaction and treatment preference, glycated hemoglobin, body mass index, weight, glycemic index, and therapy parameters. Those outcomes address related but distinct questions. The registry record does not report a primary DTQ comparison between Solo and OmniPod.

3. Trial Design

This was a randomized, open-label, parallel-group interventional device study in people with type 1 diabetes. The registry lists the phase as not applicable. The sponsor was Hoffmann-La Roche. The study began on 2018-05-17, reached primary completion on 2020-05-18, and has completed status in the registry record. Enrollment was 181.

During the initial 26 weeks, Group A used the Solo micropump, Group B used multiple daily injections, and Group C used the mylife™ OmniPod® system. At Week 26, all groups moved to Solo for continuous subcutaneous insulin infusion through Week 39. The primary DTQ outcome was assessed at 26 weeks, corresponding to the end of the initial treatment period before the shared Solo phase.

The registry describes the main objective as comparing MDI with Solo and says the third arm was included for data collection in comparison with a similar product. Randomization helps create groups for comparison, but the record does not report the randomization sequence method or allocation concealment. Masking is listed as none, which is relevant because participants knew which treatment they were using while reporting their experience.

The record gives arm-level participant counts for the primary comparison: 62 in Group A and 61 in Group B. It also reports 58 in Group C for the secondary SMBG measure. The registry record does not report the trial’s original sample-size justification, its detailed statistical analysis plan, or the basis for its chosen enrollment target.

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: A total of 187 participants were screened into this study, of whom 6 participants were screen failures meaning that a total of 181 participants were randomised into this study.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: The Full Analysis Set was defined as all eligible participants who were randomized to one of the three treatment arms.

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 Treatment Satisfaction: Accu-Chek® Micropump System vs. MDI, Measured by the Difference in the Diabetes Technology Questionnaire (DTQ) Total Change Score, measured over 26 weeks.

The primary endpoint is treatment satisfaction assessed using the change in the total score on the Diabetes Technology Questionnaire. The registry describes a 30-question instrument. Individual change scores range from 1 to 5, with 1 representing much worse and 5 representing much better; the total change score ranges from 30 to 150. Higher total scores represent lower impairment and improved outcomes.

A participant-reported measure is useful for questions about how treatment is experienced. Satisfaction and perceived burden can capture aspects of care that are not conveyed by a laboratory measure alone. In this study, the endpoint therefore addresses whether reported experience changed differently between the device and injection groups over the initial treatment period.

The primary result is not, by itself, a measure of glycemic control, safety, or long-term health. The registry lists separate secondary outcomes concerning glycated hemoglobin, distress, weight, and other therapy parameters. Those outcomes may provide complementary information, but they do not change what the DTQ endpoint measures.

The registry identifies the primary parameter as a least-squares mean and gives standard errors for the arm summaries. The exact model specification and the covariates used to obtain those least-squares means are not reported in the registry record.

7. Results Posted in the Registry

• Group B: MDI, Then Accu-Chek® Solo: mean 94.80 versus 105.90 on control; difference -11.10 (95% CI -18.43 to -3.77), standardized effect d = -0.54; z-test p = 0.003.

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 Therapy Parameters Based on Average Number of Self Monitoring of Blood Glucose (SMBGs) Per Day

• 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:
  • Group B: MDI, Then Accu-Chek® Solo: mean 3.40 versus 3.20 on control; difference 0.20 (95% CI -1.01 to 1.41), standardized effect d = 0.06; z-test p = 0.746.
  • Group C: Mylife™ OmniPod®, Then Accu-Chek® Solo: mean 2.50 versus 3.20 on control; difference -0.70 (95% CI -1.79 to 0.39), standardized effect d = -0.23; z-test p = 0.209.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Group B: MDI, Then Accu-Chek® Solo and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Group C: Mylife™ OmniPod®, Then Accu-Chek® Solo and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists a broad set of secondary outcomes, covering distress, treatment preferences, glycemic measures, body measurements, and therapy parameters. The numerical secondary comparison available in the record concerns average self-monitoring of blood glucose per day. Its two group comparisons have unadjusted p-values of 0.746 and 0.209, and both recalculated confidence intervals include zero. Those results do not provide clear evidence of a difference in the reported mean under the unadjusted comparisons.

These secondary measures address questions that are related to, but distinct from, participant-reported DTQ treatment satisfaction. A measure of self-monitoring frequency is not interchangeable with a satisfaction score, and neither alone establishes an effect on every other listed outcome. The secondary data therefore offer context about the range of outcomes studied, rather than a direct confirmation or refutation of the primary participant-reported contrast.

Secondary results generally carry less weight than a prespecified primary result because they may involve multiple outcomes and comparisons. In general, testing many outcomes increases the chance of finding an apparently notable result by chance if no multiplicity strategy is applied. The registry describes a hierarchy for the primary comparisons, but does not report a complete multiplicity plan for the secondary outcomes. The secondary p-values are unadjusted, so they should be interpreted cautiously and not treated as confirmatory evidence without further analysis details.

The registry indicates that 19 secondary outcomes were posted, but the numerical information in the record is limited. Results for the other listed secondary outcomes are not reported in the registry record. Their absence prevents an overall assessment of whether the various secondary measures point in a consistent direction. It also means that no broad conclusion about all secondary outcomes can be drawn from the SMBG results alone.

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

• Diabetes-Related Emotional Distress Assessed by Problem Areas in Diabetes Scale (PAID)-5
• Device Satisfaction and Treatment Preference
• Therapy Success Confirmed by Glycated Hemoglobin (Hb1Ac) Levels
• Therapy Success Indicated by Change in Body Mass Index (BMI)
• Therapy Success Indicated by Change in Weight
• Change in Glycemic Index
• Number of Participants With Therapy Parameters Indicated by Commencement of Continuous Subcutaneous Insulin Infusion (CSII)
• Change in Therapy Parameters Based on Type of Insulin Used

9. Statistical Interpretation

10. Statistical Methods Explained

The reported primary measure is continuous: each participant contributes a score on a numerical scale, and the arm summaries describe average scores. A mean difference expresses how far apart two group averages are in the stated comparison direction. Here, the comparison is MDI minus Solo, so a negative estimate means the MDI average is lower than the Solo average. Because higher DTQ scores represent lower impairment and improved outcomes, the direction of that contrast can be read alongside the score definition.

What does a least-squares mean represent?

In general, a least-squares mean is an average estimated from a statistical model rather than necessarily the simple arithmetic average of every observed value. Such means can account for variables included in the model. The registry identifies the primary parameter as a least-squares mean but does not report the model formula, included covariates, or how baseline measurements were incorporated. The numerical arm values should therefore be read as the registry’s reported summaries, without assuming an undocumented adjustment.

How should the standard errors be read?

In general, a standard error describes the precision of an estimated mean: it reflects how much the estimate would vary across repeated samples under the analysis assumptions. It is not a description of the spread of individual participants’ scores. The primary arm summaries give standard errors of 2.66 for Solo and 2.63 for MDI. Those values are distinct from the pooled standard deviation used in the simple recalculation of the comparison.

For the recalculated comparison, the pooled standard deviation is 20.75 and is marked as approximate. In general, a standard deviation describes participant-to-participant spread, while a standard error describes uncertainty in an estimated average. The available recalculation uses the reported arm standard errors to approximate the standard deviations needed for an unadjusted comparison. It is not a replacement for a fully specified model-based analysis, and the registry record does not supply enough information to reproduce the sponsor’s full analysis.

What does the unadjusted comparison tell us?

In general, an unadjusted comparison evaluates the observed difference between groups without applying an adjustment for multiple comparisons or other model-based features not specified in the calculation. The recalculated mean difference is -11.1, and its confidence interval ranges from -18.43 to -3.768. The unadjusted p-value is 0.003. These quantities describe the comparison under the assumptions of the recalculation. They do not, on their own, confirm how the trial’s stated hierarchical procedure was implemented or what adjusted inference was reported by the sponsor.

In general, a confidence interval combines an estimated contrast with its uncertainty. It is useful to examine both the estimate and the interval: the estimate indicates the observed direction and scale, while the interval indicates the range of values compatible with the calculation. The interval does not describe the distribution of individual DTQ scores. It also does not resolve limitations from an open-label design, missing outcome data, or incomplete reporting of the analysis model.

Why can over-dispersion matter?

In general, over-dispersion occurs when the observed variation in data is greater than a statistical model assumes. If a model understates that variation, its standard errors may be too small and its intervals too narrow. This concern is especially relevant to count outcomes or other measures whose variation does not fit a simple model. The posted secondary SMBG summaries have standard deviations of 3.0, 3.8, and 3.1 across the three groups, but the registry record does not identify an over-dispersion assessment or a model for that endpoint. It would not be appropriate to infer a particular count model from the summaries alone.

The methods used to analyze the questionnaire scores are not described in enough detail to determine whether they addressed distributional features, baseline score, or other potential sources of variation. General statistical principles can explain why these choices matter, but the record does not establish which specific methods were used beyond identifying least-squares means and standard errors for the primary measure.

What does the hierarchy add?

In general, a hierarchical testing procedure orders statistical comparisons so that a later test is conditional on the result of an earlier test. The stated order was Solo versus MDI first, followed by Solo versus OmniPod only if the first null hypothesis could be rejected. This can limit the interpretation of later comparisons, but the record does not report a complete multiplicity plan, a sponsor-reported adjusted p-value, or the primary OmniPod result. The displayed unadjusted comparison should therefore be distinguished from a documented conclusion under the full hierarchy.

Randomization and the parallel-group structure support comparison of the assigned groups during the initial treatment period. The study was not masked, and satisfaction was reported by participants aware of treatment assignment. General statistical adjustment cannot remove every possible influence of treatment expectations or reporting behavior. The record also does not report how adherence, withdrawals, or missing questionnaires were incorporated into the primary analysis.

Finally, an analysis population definition matters because it specifies which randomized participants contribute to an estimate. The registry defines the Full Analysis Set as all eligible participants randomized to one of the three treatment arms. It does not report additional detail about eligibility for the analysis set, the number with usable DTQ outcomes, or a separate per-protocol analysis. These omissions leave uncertainty about the relationship between the randomized population and the analyzed observations.

11. Confidence Intervals and Precision

The primary arm summaries are 105.9 for Solo and 94.8 for MDI. The recalculated difference, expressed as MDI minus Solo, is -11.1, with a 95% confidence interval from -18.43 to -3.768. The interval represents uncertainty around the estimated difference under the assumptions used in the unadjusted recalculation. It is not an interval containing a specified proportion of individual participants’ scores.

In general, a confidence interval is a method for expressing estimation uncertainty. A narrower interval indicates greater precision under the statistical model; a wider interval indicates less precision. Its interpretation depends on the analysis assumptions and the quality of the underlying data. Here, the comparison is based on the reported group summaries, and the pooled standard deviation used in the recalculation is approximate. The registry’s detailed model specification and missing-data handling are not reported.

The interval does not include zero, while the posted unadjusted p-value is 0.003. These are related descriptions of the recalculated contrast, not separate proof that the result is important to participants or that the difference arose from treatment alone. The reported arm standard errors quantify uncertainty in the arm means; they should not be mistaken for the spread of participant scores. The recalculated pooled standard deviation of 20.75 describes a different aspect of variation.

Precision is also specific to the Solo-versus-MDI contrast. It cannot be transferred to the primary comparison with OmniPod, which is not reported in the registry record. Nor does the interval resolve potential bias associated with an open-label, participant-reported endpoint or uncertainty about the analysis population.

12. Planning a Similar Trial: Sample Size

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

The planning illustrations express required enrollment as participants per arm, not as a total number of events. They are based on the observed primary effect and show scenarios for detecting 100%, 75%, or 50% of that observed effect. The listed assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is the stated fraction of the observed effect.

The 80% power column describes the planned number of participants per arm for a design that would have an 80% chance of detecting the specified effect if that effect were the true one and the assumptions held. The 90% power column describes the corresponding planning target for a 90% chance. These are design probabilities under assumptions, not guarantees about what a future study will find. The figures are planning illustrations, not observed power.

As the target effect becomes smaller, more participants are generally needed to distinguish it from random variation. The scenarios therefore help show how strongly planned enrollment depends on the effect size chosen for planning. The illustrated values are derived from the observed effect in this study; they are not evidence that the original trial was designed using that effect or those assumptions.

The registry record does not report the trial’s original sample-size assumptions or sample-size justification. The planning assumptions listed for these illustrations should not be attributed to the trial’s protocol. The trial enrolled 181 participants, but that enrollment figure alone does not establish the power or precision the investigators intended, nor does it determine the performance of a different study design.

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 = -11.100; pooled standard deviation σ = 20.746.
2. n = 2 × (1.96 + 0.842)² × 20.746² / -11.100² = 54.8, rounded up to 55 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 <- -11.1                      # observed difference in means
sigma <- 20.7455607518594                     # 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(3478969)
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 = 55 (80% power), 74 (90% power)
 75% of observed effect: n per arm = 98 (80% power), 131 (90% power)
 50% of observed effect: n per arm = 220 (80% power), 294 (90% power)
power.t.test: 55.8 
Simulated power at n = 55 per arm: 0.791 (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 describes a hierarchical procedure for the primary comparisons: Solo versus MDI is tested first, and the Solo-versus-OmniPod comparison is conditional on rejection of the first null hypothesis. This is relevant because a sequence of comparisons requires a plan for interpreting the full set of tests. However, the registry does not report the detailed testing thresholds, whether or how the p-value was adjusted, or the sponsor’s full inferential result under the hierarchy. The posted unadjusted p-value should not be treated as a substitute for those missing details.

The primary numerical result available in the record is for Solo versus MDI. The primary DTQ result for Solo versus OmniPod is not reported in the registry record. Without that result, the full stated primary comparison sequence cannot be assessed from the registry information. The record also does not explain how the secondary outcomes were handled for multiplicity, even though it lists a range of secondary measures.

Missing-data methods are not reported in the registry record. The record does not state how many participants had a DTQ measurement at 26 weeks, how incomplete questionnaires were handled, or what assumptions were made about missing outcomes. It also does not report whether sensitivity analyses were conducted to examine the effect of missing data. These details matter because the estimated group contrast depends on which observations contribute and on the method used to address incomplete outcomes.

The Full Analysis Set is defined as all eligible participants randomized to one of the three treatment arms. The registry does not give further detail about eligibility criteria for that set, the number included in the primary analysis, or whether other analysis populations were used. It does not report an interim analysis plan or results. The original sample-size justification and detailed statistical analysis plan are also not reported in the registry record.

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 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: hypoglycaemia (4.8%), vomiting (1.7%), anaphylactic shock (1.7%), osteomyelitis (1.7%), arthropod bite (1.7%).

During the parallel phase, the registry reports serious adverse events for 6 of 62 participants in the Solo group, 1 of 61 in the MDI group, and 5 of 58 in the OmniPod group. During the later Solo phase, it reports serious adverse events for 4 of 165 participants across the groups. The later phase follows the switch to Solo and should be read separately from the initial parallel comparison; the exposure periods and group arrangements differ.

No deaths are reported in any of these groups. The registry lists hypoglycaemia at 4.8% among the leading serious adverse event terms. It also lists vomiting, anaphylactic shock, osteomyelitis, arthropod bite, and lower limb fracture, each at 1.7%. These are event-term percentages reported in the registry, not a complete description of every event or a basis for comparing risk without additional context.

Serious adverse event counts are descriptive. They do not establish that a treatment caused an event, and the registry record does not provide enough detail to assess event timing, exposure-adjusted rates, or a formal between-group safety analysis. Differences in the phase structure should be considered when reading the group counts.

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

The primary result describes participant-reported treatment satisfaction at 26 weeks. The posted arm summaries place the Solo group’s DTQ score above the MDI group’s score, and the recalculated difference is -11.1 when expressed as MDI minus Solo. The scale definition indicates that higher scores represent lower impairment and improved outcomes. This is a finding about the questionnaire score in the studied groups and time period.

It does not establish that Solo improves every aspect of diabetes management, nor does a treatment satisfaction measure establish a change in glycated hemoglobin, weight, safety, or other clinical outcomes. Those topics appear as separate secondary outcomes, and most of their numerical results are not reported in the registry record. The primary result also does not answer the primary Solo-versus-OmniPod question, for which the DTQ comparison is not reported.

The unadjusted p-value and recalculated confidence interval express statistical uncertainty under the available summary-statistic calculation. They do not describe the probability that the treatment is beneficial, the probability that the result will repeat, or the practical value of the difference to an individual participant. A group average does not imply that every participant experienced a change of the same size or direction.

The open-label design is relevant to a participant-reported endpoint: participants knew their treatment, and the record does not report masking. The registry also does not report enough information about missing questionnaires or the model specification to evaluate all sources of uncertainty. The stated hierarchy makes the complete primary inference depend on more than the unadjusted Solo-versus-MDI result alone.

Accordingly, the result is best read as a comparison of reported DTQ scores between randomized groups during the initial treatment period. It should not be extended to unreported outcomes, later follow-up comparisons, other populations, or treatment decisions. The registry record does not establish those broader conclusions.

17. Why This Trial Matters Statistically

This trial illustrates why the endpoint definition matters. A participant-reported satisfaction score captures treatment experience, while laboratory measures and event outcomes address different questions. Keeping those outcomes distinct helps prevent an appealing result on one measure from being interpreted as evidence about outcomes the measure does not assess.

It also illustrates the difference between an estimated group contrast and its precision. The mean difference, confidence interval, standard errors, and unadjusted p-value each describe a different feature of the comparison. Reading them together is more informative than relying on a p-value alone. The approximate nature of the recalculated pooled standard deviation and the absence of a detailed model specification are important context for that reading.

The stated hierarchy makes the order of primary comparisons part of the design’s inferential structure. A result for the first comparison cannot be assumed to answer the second, particularly when the second primary result is not reported. This is a practical example of why full reporting of prespecified comparisons and multiplicity procedures matters.

The open-label format is especially relevant when the outcome is reported by participants. Awareness of treatment does not automatically invalidate a questionnaire result, but it is a possible influence that should be considered alongside randomization and the score’s meaning. The shared Solo phase after Week 26 also distinguishes the initial comparison from later follow-up, when the original groups no longer remained on separate assigned treatments.

Finally, planning scenarios based on an observed effect can show how sample-size needs change when a study aims to detect a smaller effect. They are not a substitute for the original design rationale, which is not reported. Together, these features make the record useful for understanding the relationship among endpoint choice, comparison structure, precision, multiplicity, and transparent reporting.

18. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

The primary endpoint is participant-reported, and the study was not masked. Participants’ knowledge of their assigned treatment could influence responses about satisfaction or perceived treatment experience. The registry record does not report procedures intended to assess or address such influence.

The primary numerical comparison available is Solo versus MDI. Although the study included an OmniPod group and the primary description specifies a conditional comparison with that group, the primary DTQ result for Solo versus OmniPod is not reported in the registry record. This limits interpretation of the stated three-group objective.

The study’s initial comparison period lasted 26 weeks. After that point, all groups used Solo through Week 39, so later observations do not represent continued parallel use of the original treatments. The primary endpoint’s 26-week timing is aligned with the initial treatment period, but later outcomes require attention to this shared treatment phase.

The registry record does not report the sample-size justification, full statistical analysis plan, detailed model specification, missing-data methods, or number of participants with complete primary outcome data. It also does not provide a sponsor-reported adjusted result for the hierarchical procedure. These reporting gaps limit independent evaluation of the analysis and its assumptions.

Numerical secondary results are limited in the record, despite multiple secondary outcomes being listed. That makes it difficult to assess consistency across outcomes or to understand the full set of findings. The available summaries also do not provide individual participant distributions, so the extent of variation in treatment experiences cannot be assessed from group averages alone.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Participant-Reported Outcomes With the Accu-Chek® Solo Micropump System — NCT03478969.
• Registry record last updated 2021-08-20; status last verified 2021-08.
• Results first posted 2021-08-16.
• 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

NCT03478969 is a completed, randomized, open-label, parallel-group device study sponsored by Hoffmann-La Roche. It enrolled 181 participants with type 1 diabetes. The initial 26-week groups used Solo, MDI, or mylife™ OmniPod®; all groups then used Solo from Week 26 through Week 39.

The primary endpoint was change in DTQ total score at 26 weeks, with higher scores representing lower impairment and improved outcomes. The posted primary comparison was Solo versus MDI. The recalculated difference was -11.1 for MDI minus Solo, with a 95% confidence interval from -18.43 to -3.768 and an unadjusted p-value of 0.003. The primary Solo-versus-OmniPod result is not reported in the registry record.

The registry describes hierarchical testing, but does not report the full adjusted inference, detailed analysis plan, missing-data methods, or original sample-size justification. Numerical secondary information is limited. Safety counts are reported separately for the parallel and later Solo phases, with no deaths reported.