A Study of Ponatinib Versus Imatinib in Adults With Acute Lymphoblastic Leukemia: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Study of Ponatinib Versus Imatinib in Adults With Acute Lymphoblastic Leukemia (NCT03589326), a randomized phase 3 study. The primary outcome is Number of Participants With Minimal Residual Disease (MRD)-Negative Complete Remission (CR) at The End of Induction Phase.

2. Clinical Question

3. Trial Design

This was a Phase 3, randomized, open-label, multicenter, parallel-group study comparing ponatinib with imatinib in adults with newly diagnosed Philadelphia chromosome-positive acute lymphoblastic leukemia. Both treatments were administered with reduced-intensity chemotherapy. Because masking was listed as none, the study was open-label: treatment assignment was not masked according to the registry record. No further details about randomization procedures or allocation concealment are reported in the registry record.

The registry lists planned enrollment of 245. The posted primary endpoint counts are based on 154 participants in the ponatinib arm and 78 in the imatinib arm; these are the denominators accompanying the posted arm results, not an explanation of why they differ from the enrollment figure. The record does not report a reason for that difference. The endpoint population is described as the ITT population with p190 or p210 variants, identified by a central laboratory. Further details about the exact analysis set used for the posted counts are not reported in the registry record.

The primary endpoint was assessed at the end of the induction phase, from Cycle 1 through Cycle 3, approximately 3 months, with each cycle lasting 28 days. The registry describes induction treatment for up to 3 cycles. It also states that participants would receive the assigned drug with chemotherapy for up to 20 months and then continue single-agent therapy until study discontinuation criteria were met. The detailed dosing text in the registry record is truncated, so the full treatment schedule is not reported there.

The registry lists a study start date of 2018-10-04, primary completion on 2022-08-12, and status as active, not recruiting. No additional details about follow-up duration, site locations, or the conduct of recruitment are reported in the registry record.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Before assignment: Participants with a diagnosis of Philadelphia chromosome-positive acute lymphoblastic leukemia (Ph+ ALL) were enrolled in a 2:1 ratio to receive ponatinib or imatinib.

IP (Cycles 1-3) (Cycle Length=28 Days)

Reasons for not completing this period:

CP (Cycles 4-9) (Cycle Length=28 Days)

MP (Cycles 10-20) (Cycle Length=28 Days)

Analysis population for the primary outcome, as defined in the registry: ITT population with p190/p210 variant was defined as all participants in the ITT population who were identified by the central laboratory as having baseline breakpoint cluster region-Abelson1 (BCR-ABL1) dominant variants of p190 or p210.

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: ITT analysis set was defined as all participants who were randomized.

6. Primary Endpoint

The registry lists the primary outcome as Number of Participants With Minimal Residual Disease (MRD)-Negative Complete Remission (CR) at The End of Induction Phase, measured over From Cycle 1 through Cycle 3 (approximately 3 months) (Cycle length = 28 days).

The primary endpoint counts participants who met both the molecular definition of minimal residual disease negativity and the clinical definition of complete remission at the end of induction. The assessment covers Cycle 1 through Cycle 3, approximately 3 months, with each cycle lasting 28 days. The endpoint is therefore a binary outcome for each participant: the participant either met both criteria or did not.

MRD negativity was defined as BCR-ABL1/ABL1 at or below 0.01%, or undetectable BCR-ABL1 transcripts in cDNA with at least 10,000 ABL1 transcripts. Complete remission required the criteria to persist for at least 4 weeks without recurrence. These included no circulating blasts and less than 5% blasts in bone marrow, normal maturation of marrow cellular components, and no extramedullary disease. The description also required an absolute neutrophil count greater than 1000 per microliter and platelets greater than 100,000 per microliter.

Combining molecular response with clinical remission gives a more specific endpoint than either component alone: a participant must satisfy both sets of criteria. Such a defined endpoint can be used to compare the number meeting the target response in each randomized arm. It does not, by itself, describe how long remission lasts or establish outcomes beyond the assessment period. Those are distinct questions, and the registry separately lists duration outcomes among its secondary outcomes.

7. Results Posted in the Registry

• Cohort B: Imatinib 600 mg: 16.7% (13/78) versus 34.4% (53/154) on control; risk difference -17.7 percentage points (95% CI -28.9 to -6.6), risk ratio 0.48 (0.28–0.83); unadjusted two-proportion z-test p = 0.005.

8. Statistical Interpretation

9. Statistical Methods Explained

What does a binary endpoint count?

The primary outcome is a count of participants who meet a defined response criterion. Each participant is classified according to whether MRD-negative complete remission was achieved by the end of induction. The reported arm results give both the number meeting the endpoint and the denominator used for that arm. This makes the outcome different from a continuous measurement, such as a laboratory value, and different from a time-to-event outcome, such as time until relapse or another event.

A count alone is not a complete comparison when the arm denominators differ. The count must be considered in relation to the number of participants in each arm. The registry’s reported comparison uses a risk difference, which expresses the difference between the two response proportions. In plain terms, it contrasts the proportion meeting the endpoint in one arm with the proportion meeting it in the other. The sponsor reports a positive risk difference for the ponatinib-versus-imatinib comparison; the posted arm counts also show more observed responses relative to their respective denominators in the ponatinib arm.

What does the risk difference communicate?

A risk difference is an absolute contrast on the probability scale. It is not a relative measure such as a risk ratio, and it is not an odds ratio. The sponsor reports a risk difference of 0.18 and a 95% confidence interval from 0.06 to 0.29. The positive direction is consistent with a larger observed response proportion in the first arm of the sponsor’s comparison. The interval expresses uncertainty about the magnitude of that absolute difference under the analysis.

The registry also contains a simple unadjusted recalculation from the posted summary statistics. That calculation reports p = 0.005 and uses the imatinib arm as the comparison relative to ponatinib, so its contrast is oriented in the opposite direction from a ponatinib-minus-imatinib contrast. The recalculation is not a replacement for the sponsor’s analysis. The sponsor’s analysis is reported as chi-squared with a risk-difference parameter, and the record marks no discrepancy between the posted analysis and the recalculation.

What does a chi-squared test assess?

In general, a chi-squared test for a binary outcome assesses whether the observed distribution of participants across outcome categories differs between groups, under the test’s assumptions. It summarizes evidence against a null hypothesis of no association between treatment group and endpoint status. A p-value is a measure of how unusual data at least as incompatible with that null hypothesis would be if the null model and its assumptions held. 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 sponsor reports a chi-squared analysis and a p-value. The registry record does not provide further technical details about the exact test implementation, continuity correction, covariate adjustment, or whether the test was stratified. Those features should not be inferred from the method label alone. The unadjusted recalculation is explicitly a simple analysis of the posted summary statistics, rather than a reconstruction of any unreported sponsor model.

Why report a confidence interval?

In general, a confidence interval describes the statistical uncertainty around an estimate. A narrower interval indicates greater precision under the method used; a wider interval indicates more uncertainty about the effect size. The sponsor’s interval for the risk difference ranges from 0.06 to 0.29. It gives information about the range of contrasts compatible with the observed data and analysis assumptions, rather than a guarantee that the true effect lies in that range.

A p-value and a confidence interval answer related but different questions. The p-value summarizes evidence against a specified null value. The interval shows a range of plausible values for the estimate and conveys direction and precision. Neither one resolves questions about bias, endpoint validity, missing outcomes, or applicability beyond the study population.

Why can extra variation matter?

General statistical models often rely on assumptions about variability. When outcomes vary more than a model expects, standard errors may be too small, making intervals too narrow and p-values too optimistic. This is called over-dispersion in settings where the model’s assumed variation is exceeded. The posted primary outcome is a binary participant count, and the registry identifies a chi-squared analysis; it does not report an over-dispersion assessment or a model for extra variation. This concept is useful more generally, but there is no basis in the registry record to say that over-dispersion occurred in this analysis.

Likewise, randomization supports a comparison between assigned groups in the trial, but it does not eliminate every concern about outcome ascertainment, missing data, or deviations from the intended analysis. The trial was open-label, so participants and study personnel were not masked according to the registry record. The endpoint includes laboratory criteria, but the record does not state whether endpoint assessors were masked or how missing laboratory measurements were handled. These details are not reported in the registry record.

10. Confidence Intervals and Precision

The sponsor’s estimated risk difference is 0.18, with a 95% confidence interval from 0.06 to 0.29. The entire reported interval is on the positive side of zero. In the comparison’s stated direction, this is consistent with a higher observed proportion achieving the endpoint in the ponatinib arm. The interval also shows that the estimated magnitude is not known with exact precision: values across the reported range remain compatible with the data under the analysis assumptions.

A confidence interval is not a statement that there is a 95% probability that the fixed true effect lies inside this particular interval. In general, the confidence level describes the long-run performance of the procedure across repeated samples under its assumptions. For an individual study, the interval is a way to communicate statistical uncertainty around the estimate. It does not account automatically for potential bias, incomplete outcome ascertainment, or limits in the analysis population.

The width of the interval reflects the information available for this comparison and the method used to calculate it. The posted denominators are 154 in the ponatinib arm and 78 in the imatinib arm, with 53 and 13 participants meeting the endpoint, respectively. The difference in arm sizes is relevant context for precision, but the interval should be interpreted using the reported analysis rather than by informally comparing counts alone.

The sponsor’s interval and the unadjusted recalculation are distinct statistical outputs. The recalculation’s risk-difference limits are not repeated because they are reported to more decimal places than the stated display limit for this analysis. The sponsor’s reported estimate and interval remain the reference for the sponsor’s chi-squared analysis. Neither interval width nor exclusion of zero establishes clinical importance, durability of response, or an effect on outcomes not reported for this endpoint.

11. 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 derived from the observed effect, not the trial’s original sample-size design. For this binary outcome, the displayed requirements are participants per arm. They are not total event counts. The planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each row considers an effect to detect expressed as a stated fraction of the observed effect.

For planning at 100% of the observed effect, the illustration gives 94 participants per arm for 80% power and 125 participants per arm for 90% power. For planning at 75% of the observed effect, it gives 177 participants per arm for 80% power and 236 participants per arm for 90% power. For planning at 50% of the observed effect, it gives 418 participants per arm for 80% power and 559 participants per arm for 90% power.

In plain language, the 80% power column describes the number of participants per arm that the planning calculation estimates would be needed to detect the specified effect with an 80% chance of rejecting the null hypothesis under the stated assumptions, if that effect and those assumptions applied. The 90% column uses the same idea with a higher target chance of detecting the effect. These are planning quantities, not observations from the completed study. This is not observed power.

The illustrations show the general relationship between target effect and sample size: smaller effects require more participants to detect under otherwise fixed assumptions. The fraction labels refer to the observed effect used as a planning reference, not an independently established treatment effect. The trial’s original sample-size assumptions, including its own target effect and power rationale, are not reported in the registry record. The calculations should therefore be read as hypothetical planning comparisons rather than a description of the trial’s original design or a judgment about whether enrollment was adequate.

12. 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 = 0.344; treatment proportion p₁ = 0.167; average p̄ = 0.255.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6167 = 1.2088.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6038 = 0.5082.
4. n = (1.2088 + 0.5082)² / (-0.1775)² = 93.6, rounded up to 94 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 <- 0.344155844155844                          # control proportion
p1 <- 0.166666666666667                          # 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(3589326)
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 = 94 (80% power), 125 (90% power)
 75% of observed effect: n per arm = 177 (80% power), 236 (90% power)
 50% of observed effect: n per arm = 418 (80% power), 559 (90% power)
power.prop.test: 93.6 
Simulated power at n = 94 per arm: 0.802 (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.

13. Analyses Reported by the Sponsor

The sponsor’s posted primary analysis is a chi-squared comparison reported as a risk difference of 0.18, with a 95% confidence interval from 0.06 to 0.29 and a reported p-value. The arm counts accompanying the endpoint are 53 of 154 for ponatinib and 13 of 78 for imatinib. The sponsor’s estimate is expressed in the ponatinib-versus-imatinib direction, so a positive value corresponds to a higher observed response proportion in the ponatinib arm.

The recalculation is a simple unadjusted analysis based on the posted summary statistics. It reports p = 0.005 and frames the contrast with imatinib as the comparison arm, reversing the direction of the risk difference relative to a ponatinib-minus-imatinib contrast. The recalculation does not reproduce the sponsor’s analysis details beyond what is available in the registry record. The record marks no discrepancy between these results; where a discrepancy is marked, the sponsor’s own analysis takes precedence.

The sponsor’s result should be interpreted as the registry’s reported analysis, while the recalculation serves as a transparent supplementary check on the posted counts. The registry record does not report further details about covariate adjustment or the full testing procedure, so no such features should be attributed to the sponsor analysis.

14. Multiplicity, Missing Data and Analysis Populations

The registry lists 14 outcome measures and 13 posted secondary outcomes, including event-free survival, complete remission and incomplete complete remission, molecular response, primary induction failure, overall response rate, MRD-negative complete remission, and duration measures. The primary endpoint is one comparison within a broader outcome set. When many outcomes are tested, the chance of at least one apparently notable result can increase unless the testing strategy accounts for multiplicity. This is a general statistical concern; the registry record does not report a multiplicity adjustment, hierarchy, or gatekeeping procedure for the outcomes.

The record lists one analysis for the primary endpoint and reports a chi-squared method. It does not report whether the primary analysis was prespecified in a protocol or statistical analysis plan, how secondary outcomes were tested, or whether there were planned subgroup analyses. Details of interim analyses, stopping rules, and any adjustment for repeated looks at the data are not reported in the registry record. Their presence or absence cannot be inferred from the posted result alone.

The endpoint population is described as the ITT population with p190 or p210 variants, identified by central laboratory testing. The record does not fully describe how participants with other variants, missing central laboratory results, or unavailable endpoint assessments were handled in the analysis. It also does not report an imputation method, a missing-data sensitivity analysis, or the number of participants with missing primary endpoint status. The posted arm denominators should not be used to infer why participants are absent from the endpoint analysis.

In general, missing outcomes can affect a binary comparison if the probability of being missing differs by treatment group or is related to endpoint status. A complete-case analysis, imputation approach, or other method can produce different results depending on assumptions. The registry record does not identify which missing-data assumptions or procedures were used. It also does not report whether the primary result was analyzed strictly by randomized assignment or under another analysis population definition beyond the stated ITT population with p190 or p210 variants.

These reporting gaps limit assessment of the full statistical plan. They do not change the arithmetic of the posted counts, but they leave uncertainty about analysis choices that may matter for interpretation and reproducibility.

15. Safety Results

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

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: febrile neutropenia (16.6%), covid-19 (4.3%), septic shock (3.7%), pneumonia (3.7%), pyrexia (3.7%).

For serious adverse events, the registry lists 97 affected participants among 163 at risk in the ponatinib arm and 45 among 81 at risk in the imatinib arm. The listed counts for participants with other adverse events are 159 among 163 and 80 among 81, respectively. The registry also reports 21 deaths in the ponatinib group and 13 in the imatinib group. These are descriptive safety counts with their posted denominators; they do not by themselves establish that an event was caused by the study treatment.

The most frequently listed serious adverse-event terms are febrile neutropenia at 16.6%, COVID-19 at 4.3%, and septic shock, pneumonia, pyrexia, and sepsis, each at 3.7%. These percentages describe the listed terms in the registry record. The record does not provide further details about event timing, severity grades, treatment relatedness, overlap among participants, or the analysis population for each term. A participant may have experienced more than one event, so event terms should not be interpreted as mutually exclusive categories.

Safety comparisons require context about exposure duration, definitions, ascertainment, and participant characteristics. Those details are not reported in the registry record for these figures. The counts therefore describe what was posted, rather than providing a complete comparative safety analysis.

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

The primary result describes the proportion of participants in each study arm who met a combined molecular and clinical response definition at the end of induction. The posted counts are 53 of 154 in the ponatinib arm and 13 of 78 in the imatinib arm. The sponsor’s reported risk difference is 0.18, with a 95% confidence interval from 0.06 to 0.29. These statistics show a higher observed response proportion in the ponatinib group in this randomized comparison, while the confidence interval conveys uncertainty about the size of the contrast.

The endpoint is specific: it requires both MRD negativity and complete remission, using the thresholds and criteria in the registry description. It does not summarize every aspect of disease status, and it is assessed at the end of induction. It should not be treated as equivalent to remission duration, event-free survival, overall response rate, or another outcome. The registry lists several such outcomes, but their numerical results are not included in the registry record for this analysis.

The result does not establish what would happen for every person with this disease, nor does it determine an individual’s likely outcome. It also does not establish an effect on long-term outcomes, because the primary endpoint is an assessment at approximately 3 months and the relevant follow-up results are not available in this record. No medical advice follows from these statistics.

Interpretation is bounded by the study record. The trial was randomized and open-label, and the primary endpoint population is described as an ITT population with p190 or p210 variants. The registry does not explain the difference between planned enrollment of 245 and the endpoint denominators, nor does it provide full details about missing data, multiplicity, or the sponsor’s detailed analysis plan. Those omissions do not erase the observed comparison, but they matter when judging its scope and robustness.

17. Why This Trial Matters Statistically

This trial raises a clear statistical comparison: two randomized treatment groups, a binary response endpoint, and a reported absolute contrast between the groups. The primary outcome combines clinical remission criteria with a molecular threshold, making the endpoint definition central to understanding what the counts represent. Statistical interpretation depends not only on the size and direction of the contrast, but also on the timing and definition of the measured outcome.

The comparison illustrates why arm-specific counts and denominators should be read together. The posted response counts differ, and the arm sizes also differ. The risk difference translates those data into an absolute comparison, while its confidence interval communicates the precision of that estimate. The sponsor’s reported interval lies on the positive side of zero, but statistical evidence about a difference is not the same as evidence about durability, broader outcomes, or clinical importance.

The study also offers a useful example of separating a sponsor’s analysis from a simple unadjusted recalculation. The sponsor reports a chi-squared risk-difference analysis; the recalculation is based on the available summary counts. Similar direction does not make the methods identical, and incomplete reporting means some analytic details cannot be independently assessed from the registry record.

Finally, the planning illustrations show how sample-size requirements depend on the effect size chosen for planning. Smaller target effects require larger participant counts under the listed assumptions. Such calculations are useful for future planning, but they are not a retrospective measure of the trial’s original design quality. The original design assumptions and several analysis details are not reported in the registry record.

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 registry record has an important denominator limitation: planned enrollment is 245, whereas the posted primary endpoint groups include 154 and 78 participants. The record does not explain how these figures relate, whether some participants were excluded from the endpoint population, or why the posted denominators differ from the planned enrollment. The endpoint population is specified as participants in the ITT population with p190 or p210 variants, but the record does not give further detail on applying that definition to the posted results.

The study was open-label. The endpoint includes laboratory criteria, but masking of laboratory personnel, endpoint assessors, or adjudicators is not reported in the registry record. Nor are the exact missing-data procedures, the number of missing endpoint assessments, or sensitivity analyses reported. These omissions make it harder to evaluate the effect of incomplete measurements or outcome ascertainment.

The registry identifies the sponsor analysis as chi-squared but does not provide further detail about test implementation, adjustment, or the full statistical analysis plan. Multiplicity procedures, subgroup plans, interim analyses, and sample-size justification are not reported in the registry record. The planning illustrations are based on the observed effect and stated hypothetical assumptions; they do not describe the trial’s original design rationale.

Finally, the primary outcome is assessed at the end of induction, approximately 3 months. The registry entries available for this analysis do not include numerical results for the listed secondary outcomes, including event-free survival and response-duration measures. The primary result therefore cannot answer questions about the persistence of response or outcomes beyond the endpoint assessment.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: A Study of Ponatinib Versus Imatinib in Adults With Acute Lymphoblastic Leukemia — NCT03589326.
• Registry record last updated 2025-11-26; status last verified 2025-11.
• Results first posted 2023-10-27.
• 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

NCT03589326 is a Phase 3, randomized, open-label, multicenter, parallel-group study comparing ponatinib with imatinib, each given with reduced-intensity chemotherapy, in adults with newly diagnosed Philadelphia chromosome-positive acute lymphoblastic leukemia. The registry lists planned enrollment of 245, a start date of 2018-10-04, primary completion on 2022-08-12, and status as active, not recruiting.

The primary endpoint is the number of participants with MRD-negative complete remission at the end of induction, from Cycle 1 through Cycle 3, approximately 3 months. The posted counts are 53 of 154 for ponatinib and 13 of 78 for imatinib. The sponsor reports a risk difference of 0.18, with a 95% confidence interval from 0.06 to 0.29, from a chi-squared analysis. The registry also lists secondary response, survival, and duration outcomes. Further details on missing data, multiplicity, and the full analysis plan are not reported in the registry record.