Effectiveness of the Quotient® ADHD Assessment in a System of Care: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Effectiveness of the Quotient® ADHD Assessment in a System of Care (NCT02094612), a randomized na study. The primary outcome is Number of Participants With 25% Reduction in SNAP Scores.

2. Clinical Question

3. Trial Design

The registry describes a randomized, parallel-group study with no masking. One arm received usual clinic ADHD care, and the other received usual clinic ADHD care plus the Quotient® assessment. The study was sponsored by Kaiser Permanente and listed as terminated. The recorded start was 2014-03, and primary completion was 2015-08. Phase was listed as NA.

The registry lists enrollment as 207, but the primary outcome population description says 58 participants completed the study, defined there as having a six month follow-up appointment, when the study was terminated. The posted primary outcome counts are 29 of 33 for Usual Care and 23 of 25 for Usual Care Plus Assessment. These arm-specific outcome figures describe the participants represented in the posted results; the registry record does not explain the relationship between enrollment, completion, and the outcome denominators.

The stated study goal was to examine whether use of the Quotient® was related to improved outcomes among pediatric patients assessed and treated for ADHD. The record lists secondary areas including ADHD symptomatology, academic performance, persistence in care, medication adherence, satisfaction with care, and other health services use. Six secondary outcomes are marked as posted, while outcome-specific summaries are present for persistence in care, medication adherence, and satisfaction with care. The registry record does not report the original design assumptions or explain why the study was terminated.

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: Fifty eight (58) participants completed the study (i.e., had their 6 month follow up appointment) when the study was terminated.

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: The population under study consists of children under age 18 who presented at 4 clinics in Northern California Kaiser Permanente for ADHD assessment. The study baseline population consists of 207 potentially eligible participants who enrolled and signed consent for the study.

6. Primary Endpoint

The registry lists the primary outcome as Number of Participants With 25% Reduction in SNAP Scores, measured over One month, 3 month and six month follow ups.

The primary endpoint counts participants with at least one 25% reduction in SNAP between visits. The assessment was planned for one month, three month, and six month follow-ups. SNAP is described as an itemized rating scale, based on DSM IV criteria, that measures ADHD symptoms and severity on a 4 point scale. The record describes it as designed to measure ADHD and oppositional defiant disorder symptoms in children and young adults ages 6-18.

The endpoint description says that a 25% reduction in SNAP IV score between consecutive clinic visits defines a therapeutic dose in ADHD treatment. In this trial, the reported outcome is the number of participants who met that reduction criterion at least once between visits; it is not a continuous summary of symptom scores or a measure of the size of each participant’s change. It therefore conveys how many participants crossed the stated threshold, but not the distribution of individual SNAP changes or when, among the follow-ups, a qualifying reduction occurred.

A threshold-based participant count can be clinically interpretable because it describes how often a prespecified level of change was reached. At the same time, converting a scale into a yes-or-no outcome discards information about changes that fall short of or exceed the threshold. The registry record does not report the underlying SNAP scores or a more detailed account of changes across visits.

7. Results Posted in the Registry

• Usual Care Plus Assessment: 92.0% (23/25) versus 87.9% (29/33) on control; risk difference 4.1 percentage points (95% CI -11.3 to 19.5), risk ratio 1.05 (0.88–1.24); unadjusted two-proportion z-test p = 0.610.

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.

Persistence in Care

• 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:
  • Usual Care Plus Assessment: 100.0% (25/25) versus 90.9% (30/33) on control; risk difference 9.1 percentage points (95% CI -0.7 to 18.9), risk ratio 1.10 (0.99–1.23); unadjusted two-proportion z-test p = 0.122.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Usual Care Plus Assessment and the control. The interval gives the range of effects that remain compatible with the data.

Medication Adherence

• 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:
  • Usual Care Plus Assessment: 68.0% (17/25) versus 54.5% (18/33) on control; risk difference 13.5 percentage points (95% CI -11.5 to 38.4), risk ratio 1.25 (0.83–1.88); unadjusted two-proportion z-test p = 0.300.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Usual Care Plus Assessment and the control. The interval gives the range of effects that remain compatible with the data.

Satisfaction With Care

• 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:
  • Usual Care Plus Assessment: 80.0% (20/25) versus 84.8% (28/33) on control; risk difference -4.8 percentage points (95% CI -24.7 to 15.0), risk ratio 0.94 (0.74–1.20); unadjusted two-proportion z-test p = 0.628.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Usual Care Plus Assessment and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes broaden the assessment beyond the primary SNAP threshold. The registry lists ADHD symptomatology, academic performance, persistence in care, medication adherence, satisfaction with care, and other health services use as secondary areas. Six secondary outcomes are marked as posted, but outcome-specific results in the record cover persistence in care, medication adherence, and satisfaction with care.

Across those posted secondary comparisons, the observed directions are not uniform, and their confidence intervals include no difference. This pattern does not provide a consistent, precise secondary signal that changes the interpretation of the primary result. Nor should it be used to claim that all aspects of care were alike: several listed areas do not have outcome-specific summaries in the registry record, and the reported comparisons remain uncertain.

Secondary outcomes can be useful for understanding whether a primary result sits alongside changes in related aspects of care. They generally carry less weight when multiple outcomes are examined without a reported multiplicity plan. Testing many outcomes raises the possibility that some may appear notable by chance. The registry record does not report a multiplicity adjustment or a prespecified hierarchy for interpreting these outcomes.

The secondary results should therefore be treated as exploratory context rather than as separate confirmatory evidence. Their interpretation is also limited by the small posted arm denominators and by the absence of reported analysis entries. They neither establish a broad pattern of benefit nor negate the uncertainty in the primary comparison.

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

• ADHD Symptomatology
• Academic Performance
• Persistence in Care
• Medication Adherence
• Satisfaction With Care
• Other Health Services Use

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is binary: each participant is counted according to whether at least one qualifying SNAP reduction was reported. For a binary outcome, the arm-specific counts describe how many participants met the criterion out of those represented in that arm. A risk difference expresses the contrast between the proportions in the two arms. A positive estimate in this comparison indicates a higher observed proportion in Usual Care Plus Assessment; the estimate is not, by itself, evidence that the difference is reliable.

What does the confidence interval describe?

A confidence interval gives a range of effect estimates compatible with the observed data under the method used to construct it. It conveys precision as well as direction: a narrow interval indicates less uncertainty about the estimate, while a wide interval leaves more possible effects compatible with the data. For the primary comparison, the interval crosses no difference, extending toward both a lower and a higher proportion in the assessment arm. This means the posted result does not isolate a single direction of effect with much precision.

How should the p-value be read?

The registry comparison gives an unadjusted p-value. A p-value measures how unusual the observed data, or data more extreme, would be under a model in which there is no difference between arms. It does not give the probability that the null hypothesis is true, and it does not measure the size or importance of an effect. The primary p-value does not provide strong evidence against no difference under conventional testing, but it cannot show that the arms are equivalent. Equivalence requires a margin and an analysis designed for that question; the registry record does not report either.

The risk difference is one scale for expressing a binary contrast. Other scales, such as a risk ratio or odds ratio, can express the same arm comparison differently, and each has its own interpretation. The record includes additional comparison measures for some outcomes, but those measures should not be treated as independent replications: they are alternate summaries of the same underlying arm data. A difference in how a result appears across scales does not substitute for careful attention to the endpoint, interval, and analysis population.

Why can small outcome groups yield uncertain estimates?

General statistical explanation: estimates based on fewer observed outcomes tend to vary more from one sample to another. This sampling variability is reflected in a wider confidence interval. Random allocation supports a comparison between assigned groups, but it does not eliminate uncertainty, incomplete follow-up, or possible differences between the randomized population and the participants represented in an outcome analysis. Here, the registry identifies 58 participants as completing the study, while the posted arm denominators for the primary result are 33 and 25. The record does not provide a full account of missing outcomes or the analysis population at each follow-up.

The comparison is unadjusted in the sense that the posted estimates are not accompanied by a reported covariate-adjusted model. Unadjusted comparisons can be useful descriptive summaries of randomized arms. However, the registry record does not report an analysis plan, model specification, or analysis entries that would allow readers to assess whether other planned methods were used. Randomization is a design feature, not a substitute for knowing how missing measurements and repeated follow-ups were handled.

There were repeated assessment points in the primary endpoint description: one month, three month, and six month follow-ups. The endpoint combines those visits into a count of participants with at least one qualifying reduction between visits. That summary does not indicate whether the same pattern occurred at each follow-up or whether a participant’s qualifying reduction persisted. The registry record does not report a visit-specific breakdown or explain how multiple observations per participant were handled in analyses.

The trial is described as randomized and parallel, but masking is listed as none. In general, lack of masking can matter for outcomes involving clinical assessments, care processes, adherence, or satisfaction because participants and care providers may know which approach was assigned. This is a general design consideration, not evidence that a particular bias occurred in this study. The record does not report methods used to reduce or evaluate such risks.

The safety results are counts of reported events in specified groups at risk, not estimates of treatment effect on the primary endpoint. Safety denominators differ from the primary outcome denominators. They should be read within their own outcome-specific reporting context, rather than combined with effectiveness counts or used to infer unreported events.

11. Confidence Intervals and Precision

The primary risk-difference interval crosses no difference and extends in both directions. That breadth indicates that the posted data do not pinpoint the size of the contrast precisely. The point estimate is positive, but plausible values represented by the interval include a lower proportion in the assessment arm as well as a higher proportion. The interval therefore cautions against treating the direction of the point estimate as a settled finding.

Precision is especially important when outcome groups are limited. The record describes 58 participants as completing the study and posts arm denominators of 33 and 25 for the primary outcome. These figures provide the context for the amount of information behind the comparison, but the registry record does not report a detailed account of how participants without completed follow-up were handled. It also does not provide estimates by follow-up visit, which could reveal whether the overall endpoint masks variation over time.

The unadjusted p-value of 0.61 is consistent with substantial uncertainty, but the confidence interval is more informative about the range of effect sizes compatible with the observed data. Neither the p-value nor the interval proves that the approaches are equal. A claim of equivalence would require a prespecified margin and an appropriate analysis, neither of which is reported in the registry record.

Precision should also be distinguished from clinical importance. The threshold-based outcome identifies participants with at least one 25% SNAP reduction, but the record does not report a threshold for a clinically important between-arm difference. It therefore describes the observed comparison and its uncertainty without establishing how large a difference would matter to patients or clinicians.

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 participants per arm, not total events. The primary-outcome planning illustration lists 836 participants per arm for 80% power and 1,118 participants per arm for 90% power when planning for 100% of the observed effect. For 75% of the observed effect, the figures are 1,553 and 2,079 participants per arm; for 50% of the observed effect, they are 3,645 and 4,879 participants per arm.

Power is the chance that a planned study will detect an effect of the specified size under the assumptions used, if that effect is present. The 80% power column represents a design targeting an 80% chance of detecting that effect, and the 90% column targets a 90% chance. These are planning quantities, not a measure of whether the completed trial had a particular probability of success. This is not observed power.

The calculation assumptions listed for these illustrations 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. Smaller effects require more participants to detect under these assumptions, which is why the figures increase when planning for a smaller fraction. The illustrations are based on the observed effect and are not the trial’s original design calculation. The registry record does not report the trial’s own original sample-size assumptions or justification.

These figures should be read as hypothetical planning guidance rather than as a recommendation or a statement about the trial’s intended enrollment. They do not resolve the difference between the enrollment entry and the completion information, and they do not account for any design or analysis features not listed in the planning assumptions.

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 = 0.879; treatment proportion p₁ = 0.920; average p̄ = 0.899.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.4254 = 0.8338.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.4244 = 0.3572.
4. n = (0.8338 + 0.3572)² / (0.0412)² = 835.1, rounded up to 836 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 <- 0.878787878787879                          # control proportion
p1 <- 0.92                          # 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(2094612)
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 = 836 (80% power), 1,118 (90% power)
 75% of observed effect: n per arm = 1,553 (80% power), 2,079 (90% power)
 50% of observed effect: n per arm = 3,645 (80% power), 4,879 (90% power)
power.prop.test: 835.1 
Simulated power at n = 836 per arm: 0.801 (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 registry lists several secondary outcome areas and reports repeated follow-up timing for the primary endpoint. Examining multiple outcomes or time points can increase the chance of finding an apparently unusual result even when no real effect is present. Statistical methods can address this multiplicity, for example through a prespecified ordering of outcomes or an adjustment to the testing procedure. The registry record does not report whether such methods were planned or used, so the secondary p-values should be read as unadjusted comparisons rather than as a family-wise confirmatory assessment.

The registry reports zero analysis entries. This does not mean no calculations or comparisons are available in the posted results; it means the record does not include analysis entries describing a fuller inferential plan. The registry record does not report the original statistical analysis plan, the model used for repeated follow-ups, or whether interim analyses were conducted. These details should not be inferred from the reported arm summaries.

Missing data are particularly relevant because the primary outcome description identifies 58 participants as having completed the six month follow-up when the study was terminated, while enrollment is recorded as 207. The posted outcome denominators are provided by arm, but the registry record does not explain all non-completion, the availability of measurements at each visit, or how incomplete outcomes were handled. It also does not report whether the analysis followed an intention-to-treat population, a completer population, or another defined group. The term “completed” in the outcome description should not be assumed to define the analysis population for every posted outcome.

Without these details, the reader cannot assess whether missingness was related to assignment or outcome, or how sensitive the estimates are to different assumptions about missing observations. The registry record also does not report a protocol-based reason for termination, interim monitoring, or the decision process around stopping. These unreported features limit assessment of the analysis and its susceptibility to selection or multiplicity concerns.

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

Serious events with the highest arm-level rate: ashthma (0.9%).

The registry reports serious adverse event figures separately from the effectiveness outcomes. For Usual Care, 112 were listed at risk for serious events and 1 was affected; for Usual Care Plus Assessment, 95 were listed at risk and 0 were affected. The serious-event listing names “Ashthma” and reports 0.9%. No deaths were reported in either group.

For other adverse events, the record lists 112 at risk in each group and 0 affected in each. These safety denominators differ from the primary outcome denominators, so the figures should not be combined or treated as if they describe the same analysis population. The registry record does not explain the differing at-risk counts or provide further detail on event timing, severity beyond the serious-event classification, or relatedness to the intervention.

These are descriptive registry counts. With few reported events, they do not establish that the approaches have the same safety profile, nor do they quantify a precise between-arm safety effect. They should be interpreted only as the event figures recorded for the specified groups.

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

The posted primary data describe the number of participants who had at least one 25% SNAP reduction between visits. More participants in each arm met this threshold than did not, and the reported comparison has a positive point estimate for Usual Care Plus Assessment. However, the confidence interval includes no difference and effects in either direction, and the unadjusted p-value is 0.61. The result is therefore uncertain rather than a clear demonstration of a between-arm difference.

That interpretation is specific to the recorded endpoint and analysis information. The primary result does not describe average symptom change, the duration of a reduction, or whether the change occurred at a particular follow-up. It also does not establish the effect of the assessment on outcomes that are not reported in detail. The record’s listed secondary domains should not be treated as fully evaluated when outcome-specific results are absent.

The findings do not show that the two care approaches are equivalent. A lack of strong evidence against no difference is not the same as evidence that any difference is small enough to be unimportant. The registry record does not report an equivalence margin, a noninferiority objective, or an analysis designed to establish equivalence.

Likewise, the posted counts do not establish that adding the Quotient® caused a change. Randomization is a strength of the design, but interpretation also depends on how outcomes, missing follow-up, and analyses were handled. The registry record does not provide a full analysis plan or an account sufficient to reconcile enrollment with completion. The appropriate conclusion is limited to the posted descriptive comparison and its uncertainty; stronger claims about effectiveness, equivalence, or the experience of all enrolled participants are not supported by the registry information alone.

17. Why This Trial Matters Statistically

This trial illustrates how the choice of endpoint shapes the question answered by a clinical study. A threshold response count is easy to describe, but it does not retain the full information contained in repeated SNAP scores. The result answers how many participants crossed the stated threshold at least once, not how much symptoms changed on average or whether improvement persisted.

It also demonstrates why point estimates should be read together with their confidence intervals. The primary estimate has a direction, but the interval spans no difference and reaches both sides of it. A single point estimate can therefore give a misleading impression of certainty if its precision is ignored. The p-value is not a substitute for the interval or for a clinically meaningful threshold between arms.

The record further highlights the distinction between enrollment, completion, and outcome-specific denominators. Enrollment is listed as 207, while the primary outcome description says 58 participants completed the six month follow-up, and the posted primary arm denominators are smaller still. Without a clear account of the analysis population and missing data, readers cannot fully judge how well the observed results represent those enrolled or how follow-up may affect the comparison.

Finally, the planning illustrations show how assumptions about the effect size and desired power influence the scale of a future study. They are not a reconstruction of the original design. Separating those planning calculations from the observed comparison helps prevent a common error: treating a sample-size scenario as evidence about the probability that the completed study detected an effect.

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.

Several trial-specific limitations affect interpretation. The study is listed as terminated, and the primary outcome description says termination occurred when 58 participants had completed the six month follow-up. The registry does not report why the study was terminated or how that decision related to the original plan. The enrollment entry is 207, but the record does not explain the difference between that entry and the completed-outcome population.

The primary endpoint is a threshold-based count at one month, three month, and six month follow-ups. The registry does not provide visit-specific results, individual SNAP changes, or information about whether qualifying reductions were sustained. This limits assessment of the time course and magnitude of changes. The record also does not report all outcome-level analysis populations or how incomplete measurements were handled.

Although the design is randomized, masking is listed as none. Knowledge of assignment may be relevant to assessments and care-related outcomes, although the record does not establish that bias occurred. The registry does not describe procedures intended to reduce or evaluate that risk. It also does not report the original sample-size justification, a detailed analysis plan, interim analyses, or multiplicity procedures. No analysis entries are reported.

The record lists six secondary outcomes as posted but includes detailed outcome summaries for only three of them. As a result, the secondary information is incomplete for assessing the full set of listed domains. The unadjusted comparisons and the uncertainty around them should not be interpreted as confirmatory evidence across multiple outcomes.

Finally, the planning illustrations use the observed effect and stated general assumptions; they are not evidence of the original design rationale. The registry record does not provide enough information to determine how the termination, follow-up, or reporting of outcomes influenced the estimates.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Effectiveness of the Quotient® ADHD Assessment in a System of Care — NCT02094612.
• Registry record last updated 2017-07-17; status last verified 2017-06.
• Results first posted 2017-07-17.
• 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

NCT02094612 is a randomized, parallel-group study with no masking, comparing usual clinic ADHD care with usual care plus the Quotient® assessment. It was sponsored by Kaiser Permanente, listed as terminated, and recorded as starting in 2014-03 with primary completion in 2015-08. Enrollment is listed as 207.

The primary outcome counts participants with at least one 25% SNAP reduction between visits. The posted counts are 29 of 33 for Usual Care and 23 of 25 for Usual Care Plus Assessment. The primary comparison is imprecise, its confidence interval includes no difference, and the unadjusted p-value is 0.61. The outcome description says 58 participants completed the six month follow-up when the study was terminated.

Secondary results are available for persistence in care, medication adherence, and satisfaction with care; the record lists six secondary outcomes as posted. The registry does not report a full statistical analysis plan, analysis entries, or a detailed account of missing outcomes and the relation between enrollment and completion. The posted findings should be interpreted as an uncertain comparison of the reported outcomes.