Somatuline Autogel Preference and Health Economy Study: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Somatuline Autogel Preference and Health Economy Study (NCT00681187), a randomized phase 4 study. The primary outcome is Subject Preference for Self or Partner Administration.

2. Clinical Question

3. Trial Design

NCT00681187, titled Somatuline Autogel Preference and Health Economy Study, was a Phase IV, international, open-label, randomized crossover study of lanreotide Autogel in patients with neuroendocrine tumours. The record lists Ipsen as the sponsor, an enrollment of 26, and a completed study. The recorded start was 2008-06 and primary completion was 2010-08.

The study compared two administration practices for the same named drug formulation: self- or partner-administered injections and injections administered by a healthcare professional. Participants were assigned to one of two sequences. Group 1 had self or partner administration first and healthcare professional administration next; Group 2 had healthcare professional administration first and self or partner administration next. The record identifies the model as crossover, but details of the crossover schedule, any washout, and the timing of every administration are not reported in the registry record.

Because the study was open-label, participants and healthcare professionals were not masked to the administration method. The primary preference assessment was scheduled between week 30 to 34. Secondary outcomes covered injection interference with daily activities and psychological wellbeing, sick leave, visits to a healthcare professional for carcinoid symptoms, perceived control of flushing and diarrhoea, and biomarker levels. The registry record describes additional aims involving resource use, costs, and healthcare-provider experience, but detailed numerical results for those aims are not reported in the registry record.

The posted primary outcome uses participants in an intention-to-treat population defined as randomized participants with at least one dose of study medication and a recorded preference assessment. The record does not provide the original sample-size rationale or fuller details of the analysis protocol.

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: Analysis was performed on Intention to Treat population defined as all randomised subjects with ≥ 1 dose of study medication and with a preference assessment recorded

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 Subject Preference for Self or Partner Administration, measured over Between week 30 to 34.

The primary endpoint was subject preference for self or partner administration, assessed between week 30 to 34. Participants were asked which administration method they would choose for regular use: a healthcare professional-administered injection or an injection administered by themselves or a partner. The outcome is reported as a number of participants, with the primary analysis population defined as randomized participants who received at least one dose and had a preference assessment recorded.

This endpoint is useful for describing acceptability from the participant’s perspective. A preference question can capture practical experience that may not be reflected in a laboratory measure or a symptom count. It addresses a direct choice between the administration methods under study, rather than asking participants to estimate clinical efficacy.

Preference is not interchangeable with symptom control, safety, or treatment effectiveness. A stated choice can reflect the overall experience of each administration practice, but the registry record does not report how participants weighed convenience, confidence, injection experience, or other possible considerations when answering. The record also does not report whether the preference question was validated or how missing assessments were handled beyond defining the primary analysis population as those with a recorded assessment. Interpretation should therefore stay close to the stated endpoint: which method participants said they would choose for regular use.

7. Results Posted in the Registry

• Group 2 HCP Then Self or Partner Administration: 85.7% (12/14) versus 90.9% (10/11) on control; risk difference -5.2 percentage points (95% CI -30.2 to 19.8), risk ratio 0.94 (0.71–1.25); unadjusted two-proportion z-test p = 0.692.

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.

Number of Patients Stating at Least One Injection Interfered With Daily Activities

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Self or Partner Administration: 8.0% (2/25) versus 24.0% (6/25) on control; risk difference -16.0 percentage points (95% CI -35.8 to 3.8), risk ratio 0.33 (0.07–1.50); unadjusted two-proportion z-test p = 0.123.
  • HCP Administration: 24.0% (6/25) versus 24.0% (6/25) on control; risk difference 0.0 percentage points (95% CI -23.7 to 23.7), risk ratio 1.00 (0.37–2.68); unadjusted two-proportion z-test p = 1.000.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Self or Partner Administration 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 HCP Administration and the control. The interval gives the range of effects that remain compatible with the data.

Number of Patients Stating at Least One Injection Negatively Interfered With Psychological Wellbeing

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Self or Partner Administration: 8.0% (2/25) versus 16.0% (4/25) on control; risk difference -8.0 percentage points (95% CI -25.9 to 9.9), risk ratio 0.50 (0.10–2.49); unadjusted two-proportion z-test p = 0.384.
  • HCP Administration: 4.0% (1/25) versus 16.0% (4/25) on control; risk difference -12.0 percentage points (95% CI -28.3 to 4.3), risk ratio 0.25 (0.03–2.08); unadjusted two-proportion z-test p = 0.157.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Self or Partner Administration 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 HCP Administration and the control. The interval gives the range of effects that remain compatible with the data.

Chromogranin A Levels

• 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:
  • After Self or Partner Administration: mean 47.85 versus 37.48 on control; difference 10.37 (95% CI -29.30 to 50.04), standardized effect d = 0.15; z-test p = 0.608.
  • Before HCP Administration: mean 42.05 versus 37.48 on control; difference 4.57 (95% CI -33.75 to 42.89), standardized effect d = 0.07; z-test p = 0.815.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between After Self or Partner Administration 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 Before HCP Administration and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes broaden the study beyond stated preference. They cover the practical experience of injections, psychological wellbeing, sick leave and healthcare contacts, perceived control of flushing and diarrhoea, and biomarker measurements. This range is relevant to the study’s stated interest in experience and resource use, but the registry record does not contain numerical results for every outcome listed in the record.

The posted numerical summaries do not form a consistent, precise pattern that can independently settle the primary preference question. The patient-experience measures are based on relatively small denominators, while the biomarker comparisons have substantial uncertainty. In general, secondary outcomes can help characterize a study, but they do not substitute for the primary endpoint or resolve the uncertainty around it. Nor do they establish that one administration practice has equivalent symptom control or safety.

The relationship to the primary result is therefore contextual rather than confirmatory. Preference is an acceptability outcome; daily activity, psychological wellbeing, symptom control, and biomarker levels describe different aspects of experience or clinical status. Agreement or disagreement across such outcomes does not automatically validate the preference finding, particularly when the comparisons are unadjusted and the record does not report a prespecified hierarchy.

The secondary p-values are unadjusted, and the registry record reports no secondary analyses. When many outcomes are examined, the chance of seeing a nominally unusual result can increase. As a general statistical principle, adjustment or a prespecified testing strategy can help control the interpretation of multiple comparisons. Neither is reported in the registry record. Secondary results should accordingly be treated as exploratory descriptions, not as a collection of independent confirmatory tests.

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

• Number of Patients Stating at Least One Injection Interfered With Daily Activities
• Number of Patients Stating at Least One Injection Negatively Interfered With Psychological Wellbeing
• Days Sick Leave
• Total Number of Visits to HCP Due to Carcinoid Symptoms
• Perceived Symptom Control Evaluation in Respect to Episodes of Flushing
• Perceived Symptom Control Evaluation in Respect to Episodes of Diarrhoea
• Chromogranin A Levels
• 5-hydroxyindoleacetic Acid (5-HIAA) Levels

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is binary at the participant level: the recorded preference falls into one of the administration choices. The registry reports participant counts by randomized sequence and a risk difference comparing Group 2 with Group 1. A risk difference expresses the difference between the groups’ proportions for the event being counted. In general, a value near zero indicates similar observed proportions; the sign indicates which group has the larger proportion according to the comparison’s direction.

The posted risk difference is -0.052. Its confidence interval extends from -0.302 to 0.198. Because the interval includes zero, values consistent with the data include no difference as well as differences in either direction. The interval is a measure of uncertainty in the estimated difference, not a range containing every individual participant’s outcome. The registry record does not identify the specific confidence-interval method used.

The unadjusted p-value for the primary comparison is 0.692. As a general statistical explanation, a p-value measures how compatible the observed data are with a specified null model, assuming that model and the analysis assumptions hold. It is not the probability that the null hypothesis is true, and it does not measure the size or practical importance of an effect. Since the reported value is unadjusted, it does not account for any broader set of outcomes or comparisons.

The study is described as randomized and crossover. Randomization assigns participants to a sequence, while a crossover design exposes participants to more than one study condition over time. In general, this design can allow within-participant comparisons, but period effects, sequence effects, and correlations between repeated observations can matter. The record gives the sequence labels and the primary group comparison; it does not report whether the sponsor’s analysis modeled within-participant correlation, period, or sequence. It would be inappropriate to assume a particular crossover model from the design label alone.

The comparison also gives relative measures: a risk ratio of 0.943 with interval 0.710 to 1.253, and an odds ratio of 0.6 with interval 0.047 to 7.63. These express the same binary outcome using different scales. In general, a risk ratio compares proportions directly, while an odds ratio compares odds; the two measures are not interchangeable, especially when an outcome is common. Their broad intervals indicate substantial uncertainty in these relative estimates. The registry record reports the risk difference as the comparison metric, so it is the most direct scale for describing the absolute contrast in this result.

Several secondary outcomes are also binary counts, including whether at least one injection interfered with daily activities or negatively affected psychological wellbeing. Their posted comparisons include risk differences, relative measures, and unadjusted p-values. The counts are modest, so estimates can move appreciably when only a small number of participant outcomes differ. As a general statistical point, small samples commonly produce imprecise estimates, particularly for uncommon outcomes.

Chromogranin A is reported as a continuous outcome in nmol/l, with means and standard deviations. The posted comparisons are mean differences with confidence intervals and unadjusted p-values. A mean difference describes the contrast in group averages; the standard deviation describes variability among observed values, not uncertainty in the mean difference. The record supplies standard errors for the reported means, but does not report the statistical model or any adjustment for repeated measurements. The posted periods include measurements before and after administration practices, so the values should not be treated as a fully specified longitudinal analysis.

For binary outcomes, over-dispersion is not the central issue in the same way it can be for count models. In general, over-dispersion means that observed variability exceeds what a model assumes, which can make model-based uncertainty too small if not addressed. Repeated outcomes and correlation may nevertheless affect uncertainty in crossover or longitudinal data. The registry record does not describe a model for these features.

The record lists no reported analyses for the secondary outcomes. It also does not report a multiplicity adjustment, a prespecified hierarchy for secondary hypotheses, or a statistical analysis plan. Consequently, the posted secondary p-values are descriptive, unadjusted comparisons and should not be treated as confirmatory evidence across a family of outcomes. Details such as covariate adjustment, missing-data methods, and sensitivity analyses are not reported in the registry record.

11. Confidence Intervals and Precision

The primary risk-difference estimate is -0.052, with a confidence interval from -0.302 to 0.198. This interval is broad relative to the point estimate and includes zero. It therefore reflects substantial uncertainty about both the direction and size of the group difference. The point estimate alone should not be read as a precise estimate of the underlying preference contrast.

For the two sequence groups, the recorded primary counts were 10 of 11 and 12 of 14. The small denominators mean that each participant represents a meaningful part of the observed group proportion. The confidence interval for the between-group contrast communicates that the available data are compatible with a range of possible group differences; it does not establish equivalence. No equivalence margin is reported in the registry record.

Confidence intervals are a general statistical tool for expressing sampling uncertainty. A confidence interval describes the range of estimates compatible with the data under the method’s assumptions; it does not guarantee that the true value lies in the interval. The registry record does not identify the interval method or provide enough detail to assess its assumptions independently.

Precision is also limited for secondary outcomes. The binary secondary measures have denominators of 25, while the chromogranin A summaries use 22 participants in each reported category. Their intervals are broad in several comparisons. These estimates can help describe the posted results, but they do not support fine-grained distinctions among small effects. Reasons for the differing denominators, and the handling of missing observations, are not reported in the registry record.

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 illustrations based on the observed effect, not the trial’s original design calculation. The original sample-size assumptions are not reported in the registry record. For the binary preference comparison, the listed figures are participants per arm. For the other displayed planning comparisons, the figures likewise refer to participants per arm; these are not total event counts. The general sample-size note distinguishes time-to-event outcomes, which would use total events, but no such planning comparison is included in these results.

The planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set to the stated fraction of the observed effect. The 80% power column describes the planned number of participants per arm for a design with an 80% chance of detecting that assumed effect under those assumptions, if the effect and model assumptions are correct. The 90% power column describes the corresponding target for a 90% chance.

Rows planning for 100% of the observed effect use the full observed estimate as the assumed effect; rows using 75% or 50% of the observed effect assume smaller differences. Smaller effects need more participants to detect with the same target power, which is why the listed requirements increase as the assumed effect is reduced.

These figures are planning illustrations, not observed power. They do not show the probability that the completed study’s result is true or the probability that it would reach a particular conclusion. They are especially sensitive to the observed effect, which can be unstable in a small study. The registry record does not report the sponsor’s original sample-size justification, so these illustrations should not be mistaken for the enrollment target used to design the trial.

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, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.909; treatment proportion p₁ = 0.857; average p̄ = 0.883.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.4544 = 0.8905.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.4529 = 0.3811.
4. n = (0.8905 + 0.3811)² / (-0.0519)² = 599.3, rounded up to 600 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
p0 <- 0.909090909090909                          # control proportion
p1 <- 0.857142857142857                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^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 (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(681187)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 600 (80% power), 802 (90% power)
 75% of observed effect: n per arm = 1,015 (80% power), 1,358 (90% power)
 50% of observed effect: n per arm = 2,166 (80% power), 2,898 (90% power)
power.prop.test: 599.3 
Simulated power at n = 600 per arm: 0.803 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-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 primary analysis population is defined in the registry record as all randomized participants with at least one dose of study medication and a recorded preference assessment. This definition is more specific than an unrestricted intention-to-treat population because it requires both exposure and an observed preference assessment. The record does not explain how participants without a recorded assessment were handled or provide the number excluded for that reason.

Enrollment was 26. The primary group summaries use 11 participants in Group 1 and 14 in Group 2. Secondary binary summaries use 25 participants in each listed group, and the chromogranin A summaries use 22. Reasons for the varying denominators, including whether they reflect missing measurements, eligibility for particular assessments, or another cause, are not reported in the registry record. The extent and pattern of missing data are therefore unclear.

The registry record lists ten outcome measures and nine posted secondary outcomes. It does not report a multiplicity adjustment, a hierarchy of hypotheses, or a plan identifying which secondary tests were intended to be confirmatory. The secondary comparisons have unadjusted p-values, and no reported analyses are listed for the secondary outcome records. In general, testing multiple outcomes without an adjustment can increase the chance that at least one result appears noteworthy by chance. That concern limits the weight placed on isolated secondary findings.

The statistical analysis plan, interim-analysis procedures, missing-data methods, and sensitivity analyses are not reported in the registry record. The original sample-size justification is also not reported. These omissions prevent assessment of whether the posted analysis fully matches a prespecified plan, how incomplete assessments may have influenced estimates, and whether alternative reasonable analyses would yield similar conclusions. The available result can still be described, but those unanswered methodological questions should remain part of its interpretation.

15. 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 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: ileus (7.7%), abdominal pain (3.8%), atrial fibrillation (3.8%), biliary tract infection (3.8%), cholangitis (3.8%).

The registry record lists serious and other adverse-event counts for the training period, self or partner administration, and healthcare professional administration. Each group lists 26 participants at risk. The serious adverse-event counts are 4 during the training period, 4 during self or partner administration, and 3 during healthcare professional administration. The counts for other adverse events are 7, 4, and 7, respectively.

These are descriptive group-period figures. The record does not report a statistical comparison of safety between administration practices, and the crossover structure means the group-period counts should not be treated as independent parallel-arm results. The record does not specify whether repeated events in a participant are counted once or how event duration or severity beyond the serious classification was handled.

The serious-event terms listed include Ileus at 7.7%, and Abdominal pain, Atrial fibrillation, Biliary tract infection, Cholangitis, and Death at 3.8% each. The deaths fields for the three adverse-event groups are not reported in the registry record. The listed Death term should therefore be distinguished from a reported group-level deaths count. These figures describe what the record lists; they do not establish a comparative safety conclusion.

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

The primary result describes participants’ stated preference after experiencing the administration practices in the randomized sequences. The recorded counts were 10 of 11 in Group 1 and 12 of 14 in Group 2. The estimated risk difference for Group 2 relative to Group 1 was -0.052, with a confidence interval from -0.302 to 0.198 and an unadjusted p-value of 0.692. The estimate is close to zero, but the interval is wide and includes differences in both directions.

This does not establish that the administration practices are equivalent or that patients have no preference. The study was small, and the primary estimate is imprecise. A failure to identify a clear group difference is not the same as demonstrating that any difference is too small to matter. The registry record does not report an equivalence or non-inferiority margin against which such a conclusion could be assessed.

The outcome also does not directly answer whether symptom control, efficacy, or safety is maintained. Those issues were among the study’s stated aims, and secondary outcomes included perceived symptom control and biomarker levels, but the primary preference question is not a clinical efficacy endpoint. The posted secondary results are limited and unadjusted, and the record does not provide numerical results for all listed outcomes.

Nor does the result quantify the effect of administration practice on costs or overall resource use. Although resource use and costs were study aims, detailed numerical findings for them are not reported in the registry record. The result is best interpreted narrowly: the posted data provide a small-study estimate of preference between randomized sequences, with considerable uncertainty and no basis for broad clinical conclusions.

17. Why This Trial Matters Statistically

This trial is statistically interesting because it uses a randomized crossover design to study an outcome that is inherently patient-reported: which administration method participants would choose for regular use. The question differs from a conventional efficacy comparison. It focuses on acceptability and experience while the study also records selected measures related to symptoms, wellbeing, resource use, and biomarkers.

The crossover structure raises analytic considerations that are important even when the endpoint is a single preference response. Participants experienced administration practices in different sequences, so the final choice may reflect both methods and their order. The registry record identifies the sequences but does not describe an analysis accounting for sequence, period, or within-participant dependence. This illustrates why a design label alone does not tell the reader how repeated experience was incorporated into the analysis.

The primary estimate also illustrates the difference between a point estimate and precision. Its value is near zero, but the confidence interval is broad. Without adequate precision, a modest-looking point estimate cannot establish equivalence or rule out meaningful differences. Reporting both the estimate and its uncertainty is essential to a statistically responsible reading.

Finally, the record includes several secondary outcomes and unadjusted comparisons, while no multiplicity strategy is reported. That combination makes it important to separate descriptive signals from confirmatory evidence. The trial’s registry results can inform how preference and related outcomes were measured, but they offer limited precision for drawing firm comparative conclusions.

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 analysis includes small sequence groups, with 11 participants in Group 1 and 14 in Group 2. The resulting primary confidence interval is broad, limiting precision. The registry record does not report an equivalence margin, so the result cannot be interpreted as evidence of equivalence.

The study was open-label, and the endpoint asked participants to state a preference. Awareness of the administration method is inherent to the comparison, but the record does not report whether the question was validated or how the response was elicited beyond its global wording. Preference may describe acceptability, but it does not measure clinical efficacy directly.

Although the design is identified as crossover, analysis details for period, sequence, and within-participant dependence are not reported in the registry record. The primary comparison is presented between sequence groups. The record also does not report washout details, timing details beyond the stated endpoint timeframe, or sensitivity analyses that could help assess crossover-specific concerns.

Denominators differ across the posted outcomes, and reasons for those differences are not reported. Missing-data handling, the full statistical analysis plan, and multiplicity procedures are also not reported in the registry record. In addition, numerical results are not reported for every listed outcome or for the stated resource-use and cost aims. These limits constrain interpretation of the overall study, particularly for secondary and safety comparisons.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Somatuline Autogel Preference and Health Economy Study — NCT00681187.
• Registry record last updated 2019-11-22; status last verified 2019-11.
• Results first posted 2012-03-13.
• 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

NCT00681187 was a completed Phase IV, international, open-label, randomized crossover study sponsored by Ipsen, with 26 participants enrolled. It compared sequences of self- or partner-administered lanreotide Autogel and healthcare professional administration in patients with neuroendocrine tumours with carcinoid symptoms.

The primary endpoint was stated preference for regular administration between week 30 to 34. The posted comparison estimated a risk difference of -0.052 for Group 2 relative to Group 1, with a confidence interval from -0.302 to 0.198 and an unadjusted p-value of 0.692. The estimate is imprecise and does not establish equivalence. Secondary outcomes cover patient experience, symptoms, and biomarkers, but the record does not report all planned numerical results or key analysis details.