CONSISTENT 1: Metabolic and Safety Outcomes of Hylenex Recombinant (Hyaluronidase Human Injection) Preadministered at CSII Infusion Site in Participants With Type 1 Diabetes Mellitus (T1DM): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for CONSISTENT 1: Metabolic and Safety Outcomes of Hylenex Recombinant (Hyaluronidase Human Injection) Preadministered at CSII Infusion Site in Participants With Type 1 Diabetes Mellitus (T1DM) (NCT01848990), a randomized phase 4 study. The primary outcome is Change From Baseline to 6 Months in Glycosylated Hemoglobin (HbA1c).

2. Clinical Question

3. Trial Design

CONSISTENT 1 was a Phase 4, randomized, unmasked trial with a factorial model, according to the registry record. It studied Hylenex recombinant pretreatment at the CSII infusion site in participants with type 1 diabetes. The registry records an enrollment of 456, a start date of 2013-03, primary completion in 2014-02, and a completed status. The sponsor was Halozyme Therapeutics.

The arms included commercial Hylenex recombinant (Formulation 1), precommercial Hylenex recombinant (Formulation 2), and standard rapid-acting insulin CSII. The descriptions say participants in the formulation arms continued their regular rapid-acting CSII and received a pretreatment during the six-month treatment period; the standard arm continued regular rapid-acting CSII. The primary comparison pooled participants receiving either Hylenex formulation and compared them with the standard CSII arm. A formulation-to-formulation comparison is mentioned in the registry description, but further details of that comparison are not reported in the registry record.

Randomization means treatment assignment was made by chance, which can help balance measured and unmeasured characteristics on average. The trial was unmasked, so participants and study personnel were not blinded to assignment, as indicated by the registry. The registry labels the model factorial, but the factors, their levels, and the allocation scheme are not reported in the registry record. The protocol’s original sample-size justification, planned analysis details beyond the posted results, and any interim-analysis plan are also not reported in the registry record. The primary endpoint was assessed at six months, while several listed secondary outcomes cover measurements through Month 12.

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: Participants who received at least one dose of study drug and had evaluable HbA1c data. Comparisons were made by pooling all of the rHuPH20 pretreatment participants (including both Formulations 1 and 2) and comparing against the standard CSII treatment arm. Formulation 1 versus Formulation 2 was compared as a supportive analysis.

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 participants who received at least one dose of study drug.

6. Primary Endpoint

The registry lists the primary outcome as Change From Baseline to 6 Months in Glycosylated Hemoglobin (HbA1c), measured over Baseline; 6 Months.

The primary endpoint was change in glycosylated hemoglobin (HbA1c) from baseline to six months, expressed as a percentage of HbA1c. The registry defines change as the post-baseline value minus the baseline value. Thus, a negative group mean indicates that the measured HbA1c value at follow-up was lower on average than at baseline; it is not itself a between-group comparison.

HbA1c is a continuous measure used to summarize glycemic exposure over time. As a general statistical explanation, continuous measures preserve information about the range of measured values, allowing investigators to compare group averages rather than reducing outcomes to categories. The primary comparison asks whether the mean change differs between the pooled Hylenex recombinant groups and standard CSII.

The posted arm means were -0.14 for Hylenex recombinant and -0.18 for standard CSII, with standard deviations of 0.521 and 0.687, respectively. The reported registry analysis used an analysis of variance (ANOVA) and described its estimate as a least-squares mean treatment difference. It reported a difference of 0.05 with a 95% confidence interval from -0.08 to 0.18. The registry categorizes this analysis as non-inferiority or equivalence, but the margin and the details of that interpretation are not reported in the registry record. A mean change is a group-level summary; it does not describe the distribution of individual changes or establish that all participants changed in the same direction.

7. Results Posted in the Registry

• Hylenex Recombinant: mean -0.14 versus -0.18 on control; difference 0.04 (95% CI -0.11 to 0.19), standardized effect d = 0.07; z-test p = 0.590.

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.

Standard Deviation of Self-Monitoring Blood Glucose Values at 6 Months

• 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 errors.
• Result:
  • Hylenex Recombinant: mean 70.90 versus 72.20 on control; difference -1.30 (95% CI -5.53 to 2.93), standardized effect d = -0.09; z-test p = 0.547.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Hylenex Recombinant and the control. The interval gives the range of effects that remain compatible with the data.

Standard Deviation of Self-Monitoring Blood Glucose Values at 12 Months

• 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 errors.
• Result:
  • Hylenex Recombinant: mean 72.90 versus 72.40 on control; difference 0.50 (95% CI -3.66 to 4.66), standardized effect d = 0.03; z-test p = 0.814.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Hylenex Recombinant and the control. The interval gives the range of effects that remain compatible with the data.

Average Carbohydrate Factor (CarbF) Values

• 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 errors.
• Result:
  • Hylenex Recombinant: mean 11.10 versus 11.00 on control; difference 0.10 (95% CI -0.94 to 1.14), standardized effect d = 0.02; z-test p = 0.850.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Hylenex Recombinant and the control. The interval gives the range of effects that remain compatible with the data.

The posted secondary outcomes cover glucose variability, hypoglycemia and hyperglycemia event rates, mean glucose excursions, and average carbohydrate factor values. The reported continuous comparisons available in the record show estimates near zero relative to their uncertainty, and their confidence intervals include zero. Across these measures, the broad pattern is not one of a consistent, clearly separated group-average signal. These results add context to the primary HbA1c comparison, but they do not independently establish the primary endpoint’s interpretation or resolve its uncertainty.

Secondary endpoints address related but distinct aspects of glycemic outcomes and treatment experience. A glucose variability measure, an event rate, and HbA1c are not interchangeable outcomes; a result for one cannot stand in for the others. The registry lists 27 outcome measures and 69 analyses, and 25 secondary outcomes are posted. When many outcomes or analyses are examined, the chance of seeing an apparently notable result by chance can increase. Unless multiplicity is addressed in a prespecified way, isolated secondary findings deserve less weight than the primary comparison.

The registry record does not report whether secondary analyses were prespecified as confirmatory, how multiplicity was handled, or whether analyses were adjusted for other factors. It also does not provide enough information to establish that every listed secondary measure was analyzed in the same population. Accordingly, the secondary results are best treated as supportive or exploratory context, not as a set of independent confirmations. They should be interpreted in light of their confidence intervals, analysis populations, and the full number of outcomes examined.

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

• Rates of Hypoglycemia Events (HE) to Month 6
• Rates of HEs to Month 12
• Rates of Hyperglycemia Events to Month 6
• Rates of Hyperglycemia Events to Month 12
• Mean Glucose Excursions at 6 Months
• Mean Glucose Excursions at 12 Months
• Standard Deviation of Self-Monitoring Blood Glucose Values at 6 Months
• Standard Deviation of Self-Monitoring Blood Glucose Values at 12 Months

9. Statistical Interpretation

10. Statistical Methods Explained

What does the mean difference represent?

A mean is the arithmetic average of the observations included in an analysis. For this primary endpoint, each participant’s outcome is the change in HbA1c from baseline to six months, and the group means summarize those changes. A between-group mean difference compares the average change in the Hylenex recombinant group with the average change in standard CSII. A value near zero indicates that the estimated group averages are close; it does not mean every participant had the same outcome.

The posted arm summaries give means and standard deviations. Standard deviation describes the spread of individual observations around a group mean. It is distinct from the standard error, which describes uncertainty in an estimated mean. The primary endpoint’s arm summaries report standard deviations, while some secondary summaries report least-squares means and standard errors. These quantities should not be treated as interchangeable.

What is the role of the confidence interval?

A confidence interval describes statistical uncertainty around an estimate under the analysis assumptions. In general, a 95% confidence interval is produced by a procedure that, over repeated comparable studies, would cover the underlying parameter in 95% of those studies. It is not a range containing 95% of individual participant outcomes, nor is it a guarantee that the true value lies within a particular interval. The primary reported interval ranges from -0.08 to 0.18. Because it includes zero, the result is compatible with a range of possible group differences, including no difference under the model. The interval’s width also matters: values on either side of zero remain compatible with the estimate.

Why distinguish the sponsor model from a recalculation?

The registry reports an ANOVA estimate described as a least-squares mean treatment difference. Least-squares means are model-based adjusted group means. The registry record does not state all model terms or covariates, so further details cannot be inferred. The simple recalculation uses posted group means and standard deviations to estimate an unadjusted contrast. It is useful as a check on the general scale and direction of the posted result, but it is not a reproduction of the sponsor’s model. The recalculation’s p-value is also unadjusted. The registry does not flag a discrepancy between the posted and recalculated primary estimates.

ANOVA is a general method for comparing means across groups using a model for the outcome. In this trial’s reported primary result, the sponsor presents a treatment difference and confidence interval from ANOVA. The registry labels the analysis as non-inferiority or equivalence, but the non-inferiority margin, model specifications, and criteria used to reach that classification are not reported in the registry record. It would therefore be inappropriate to reconstruct those choices.

What does a p-value say?

A p-value measures how incompatible the observed data, or data more extreme, are with a specified null hypothesis under the statistical model. It is not the probability that the null hypothesis is true, and it does not measure the size or clinical importance of an effect. The unadjusted recalculated primary p-value is 0.59. That value does not establish equivalence, absence of an effect, or safety. Interpretation also depends on the estimate, its confidence interval, the study design, and the endpoint’s context.

For the primary comparison, the reported confidence interval and estimate are more informative about the range of effects compatible with the model than a binary significant/not-significant label alone. The posted results concern an average contrast in a specified analysis population. They do not provide participant-level outcome distributions or establish what would happen for a particular person.

Why can over-dispersion matter?

Over-dispersion is a general statistical concern for outcomes such as event counts or rates when observed variability exceeds what a simple model assumes. If the variability is underestimated, standard errors can be too small and confidence intervals too narrow; if the model is unsuitable, inference may also be distorted. The registry lists rates of hypoglycemia and hyperglycemia as outcomes, but the event-rate analysis details and any over-dispersion assessment are not reported in the registry record. It is therefore possible to explain why model choice matters in general, but not to say whether over-dispersion was present or how it was handled in this trial.

For continuous measures, the primary analysis reports means and standard deviations, while the secondary outcomes include least-squares means and standard errors. These summaries describe different aspects of the data. In particular, standard errors quantify the precision of estimated means rather than the spread of individual values. The registry’s stated population for the primary outcome—participants who received at least one dose and had evaluable HbA1c data—also means the analysis is not simply an analysis of everyone enrolled. The methods used to address missing outcomes are not reported in the registry record.

11. Confidence Intervals and Precision

The primary sponsor estimate is a least-squares mean treatment difference of 0.05, with a 95% confidence interval from -0.08 to 0.18. The interval includes zero and spans values on either side of it. This means the posted data do not pinpoint the direction of the group contrast with high certainty. The estimate is close to zero, but the interval should be considered alongside the endpoint scale and the analysis population. The registry record does not report a threshold for a clinically important difference or a non-inferiority margin, so the interval cannot be judged against such a threshold from the available information.

Precision is not the same as statistical significance. A confidence interval can include zero while still excluding some possible effects, and a narrow interval can still cover effects that matter in context. Here, the sponsor-reported interval is the primary basis for describing uncertainty. The unadjusted recalculation gives a mean difference of 0.04 and a confidence interval that also includes zero. The two estimates are similar in scale, but the recalculation does not account for the sponsor model and should not replace it.

For the primary group summaries, the standard deviations were 0.521 and 0.687. These values describe variation among the analyzed HbA1c changes, not uncertainty in the treatment difference. The number of participants with evaluable data is reflected in the reported analysis summaries, but the registry does not report further detail about missing primary outcomes or the effect of missingness on precision. Thus, the confidence interval communicates model-based uncertainty for the reported analysis, while uncertainties related to missing data and unreported modeling choices remain unresolved.

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 figures are illustrative, not the trial’s original design calculations. They use a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The assumed effect is a stated fraction of the observed effect. The figures are participants per arm for continuous outcomes; there are no time-to-event figures in the outcomes that should be read as total event counts.

The 80% power column represents the planned number of participants per arm for a design that would have an 80% chance of detecting the assumed effect under those planning assumptions, if that effect and model assumptions were correct. The 90% power column describes the corresponding planning target for a 90% chance. These are design probabilities conditional on the assumptions, not guarantees about the result of a future study. They do not indicate the probability that a treatment effect exists.

Rows based on 100%, 75%, and 50% of the observed effect illustrate how planning changes when the target effect is reduced. Smaller effects need more participants for the same target power, which is why the planning figures increase as the assumed fraction decreases. For example, planning for 100% of the observed primary effect gives 3,169 participants per arm for 80% power and 4,242 for 90% power; planning for 50% gives 12,675 and 16,968, respectively. These figures are not observed power. The trial’s own original sample-size assumptions and justification are not reported in the registry record.

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 = 0.040; pooled standard deviation σ = 0.568.
2. n = 2 × (1.96 + 0.842)² × 0.568² / 0.040² = 3,168.6, rounded up to 3,169 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 <- 0.04                      # observed difference in means
sigma <- 0.568297499430485                     # 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(1848990)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 3,169 (80% power), 4,242 (90% power)
 75% of observed effect: n per arm = 5,634 (80% power), 7,542 (90% power)
 50% of observed effect: n per arm = 12,675 (80% power), 16,968 (90% power)
power.t.test: 3169.6 
Simulated power at n = 3,169 per arm: 0.799 (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. Analyses Reported by the Sponsor

The sponsor’s primary analysis is the registry-reported ANOVA comparison of pooled Hylenex recombinant pretreatment with standard CSII. It reports a least-squares mean treatment difference of 0.05 and a 95% confidence interval from -0.08 to 0.18. The sponsor analysis is the primary reported result and should be distinguished from a recalculation using only posted group summary statistics.

The simple unadjusted recalculation gives a mean difference of 0.04 and an unadjusted p-value of 0.59. The estimate is close to the sponsor’s 0.05 estimate, and the confidence intervals from both approaches include zero. This broad agreement supports the conclusion that the two calculations give a similar overall picture, but it does not make the methods interchangeable. The recalculation does not reproduce the sponsor’s ANOVA or any model adjustments that may have been used. The registry record does not flag a discrepancy. The registry’s non-inferiority or equivalence categorization should be read with the limitation that the margin and detailed decision rules are not reported in the registry record.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists 27 outcome measures and 69 analyses, including the primary endpoint and multiple secondary outcomes. Examining many outcomes can increase the probability that at least one estimate appears unusual by chance, even if each individual analysis uses a conventional significance threshold. Multiplicity procedures, such as an adjustment to control the overall error rate or a prespecified hierarchy for testing endpoints, are not reported in the registry record. The status of secondary analyses as confirmatory or exploratory is also not reported. This limits how strongly isolated secondary p-values can be interpreted.

The primary analysis population is described as participants who received at least one dose of study drug and had evaluable HbA1c data. This is an analysis population based on treatment exposure and availability of endpoint data, rather than simply all enrolled participants. The registry record does not report the number of participants excluded from the primary endpoint analysis for missing or unevaluable HbA1c, the reasons for missingness, or whether missing values were imputed. It also does not report sensitivity analyses examining how missing outcomes might affect the result.

The registry’s general study description identifies randomization and an unmasked design, but further statistical-plan details are not reported in the registry record. In particular, the protocol’s original sample-size justification, interim-analysis plan, model covariates, and detailed handling of missing data are not reported. The factorial label is present, but the factors and their planned role in the analysis are not reported either. These gaps do not negate the posted estimates; they define what can and cannot be assessed from the registry results. Conclusions should therefore stay close to the reported analysis population and endpoints rather than assume unreported adjustment or testing procedures.

16. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

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: coronary artery disease (2.7%), hypoglycaemia (1.8%), diabetic ketoacidosis (1.7%), non-cardiac chest pain (1.7%), menometrorrhagia (1.6%).

The registry reports serious adverse-event counts separately for the commercial Hylenex formulation, the precommercial formulation, and standard rapid-acting insulin CSII. For Formulation 1, 11 of 227 participants at risk were reported as affected; for Formulation 2, 10 of 115 were affected; and for standard CSII, 13 of 113 were affected. These are group-specific counts and denominators, not a direct estimate that treatment caused an event. The record does not report deaths in these groups; death counts are not reported in the registry record.

The registry also lists serious adverse-event terms with percentages, including coronary artery disease at 2.7%, hypoglycaemia at 1.8%, diabetic ketoacidosis at 1.7%, non-cardiac chest pain at 1.7%, menometrorrhagia at 1.6%, and angina pectoris at 0.9%. These entries describe reported terms and their posted percentages. The registry record does not provide enough detail to infer event attribution, comparative risk, or the exposure time underlying these figures. Serious and other adverse events should not be interpreted as proof of causation from counts alone.

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

The results describe a randomized comparison of pooled Hylenex recombinant pretreatment with standard CSII among participants with type 1 diabetes. For the primary outcome, the sponsor reported a small mean difference in change in HbA1c at Month 6, with a 95% confidence interval that includes zero. The unadjusted recalculation is similar in scale and also does not distinguish the group means from zero. These findings mean that the posted analyses do not establish a clear between-group difference in the average change; they do not prove that the treatments are equivalent or that no effect exists.

Equivalence and non-inferiority require a prespecified margin and a suitable decision framework. Although the registry categorizes the primary analysis as non-inferiority or equivalence, the margin and detailed criteria are not reported in the registry record. Without those details, the category cannot be independently evaluated from the posted estimate alone. A confidence interval that includes zero is not, by itself, evidence of equivalence.

The primary result concerns an average in the specified analysis population: participants who received at least one dose and had evaluable HbA1c data. It does not show how every participant’s HbA1c changed, nor does it describe outcomes for people outside the trial population. Secondary outcomes and safety summaries add information about other measured outcomes and reported events, but multiple analyses and incomplete reporting limit the weight that can be placed on isolated findings. Missing-data methods, multiplicity procedures, and key details of the original statistical plan are not reported in the registry record. The appropriate reading is therefore bounded: the record documents estimates and uncertainty for the analyses posted, but does not settle every question about treatment effects, clinical importance, or generalizability.

18. Why This Trial Matters Statistically

This trial is statistically informative because it illustrates the distinction between a small estimated group difference and a definitive claim of equivalence. The primary estimate is close to zero, and the sponsor’s confidence interval includes zero, but a non-inferiority or equivalence conclusion depends on a margin and analysis rules. Those details are not reported in the registry record. A label attached to an analysis should not substitute for examining its estimate, interval, and decision criteria.

The study also highlights the difference between a sponsor-reported model and a simple unadjusted recalculation. The recalculation from posted means and standard deviations gives a similar estimate, which is a useful descriptive check, but it does not reproduce the ANOVA. Researchers should identify the analysis that answers the trial’s stated primary question and keep independent summary calculations in their proper role.

Finally, the record demonstrates why outcomes, analysis populations, and multiplicity matter together. The primary result concerns participants with evaluable HbA1c data, while multiple secondary measures and analyses are listed. Without reported missing-data and multiplicity procedures, secondary findings carry less confirmatory weight. These are general lessons for reading clinical trial records: use the endpoint definition, population, model, and uncertainty interval to understand the evidence, and distinguish what the posted results show from what remains unreported.

19. 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 trial arise from the registry record. The study was unmasked, so participants and study personnel were not blinded to assignment. The record does not report whether or how this may have affected outcome measurement or other aspects of conduct. The primary analysis included participants with at least one dose and evaluable HbA1c data; the number and characteristics of participants without evaluable outcomes, and the missing-data methods, are not reported in the registry record.

The primary comparison pooled both Hylenex formulations. This addresses the stated pooled comparison against standard CSII, but it does not by itself show whether the formulations had similar effects. Although a Formulation 1 versus Formulation 2 comparison is mentioned, its details are not reported in the registry record. The factorial label also appears without details about factors or their analysis. The registry categorizes the primary test as non-inferiority or equivalence, but does not report the margin or full decision rules, limiting independent assessment of that claim.

The record lists many outcomes and analyses, while multiplicity handling and the confirmatory status of secondary results are not reported. The trial’s own sample-size assumptions and justification, interim analyses, and detailed model specifications are also not reported. Safety counts and listed event terms do not establish causation; further attribution and exposure details are not reported in the registry record. These limits mean that interpretation should stay within the observed, posted comparisons and avoid treating missing methodological detail as evidence that a particular procedure was or was not used.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: CONSISTENT 1: Metabolic and Safety Outcomes of Hylenex Recombinant (Hyaluronidase Human Injection) Preadministered at CSII Infusion Site in Participants With Type 1 Diabetes Mellitus (T1DM) — NCT01848990.
• Registry record last updated 2018-11-07; status last verified 2018-10.
• Results first posted 2014-10-29.
• 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.

23. Record Summary

CONSISTENT 1 was a completed, randomized, unmasked Phase 4 trial sponsored by Halozyme Therapeutics. It studied Hylenex recombinant pretreatment at the CSII infusion site in participants with type 1 diabetes. The registry records enrollment of 456 and identifies the study model as factorial.

The primary endpoint was change in HbA1c from baseline to Month 6. The primary comparison pooled the two Hylenex formulations and compared them with standard rapid-acting insulin CSII. The sponsor-reported ANOVA estimate was 0.05, with a 95% confidence interval from -0.08 to 0.18. A simple unadjusted recalculation was similar in scale. The registry also posts secondary glucose-related outcomes and adverse-event summaries.

The interval includes zero, while the non-inferiority or equivalence margin, missing-data methods, multiplicity procedures, and further details of the statistical plan are not reported in the registry record. The results therefore describe the posted estimates and their uncertainty without resolving those unreported design and analysis questions.