Comparing Efficacy and Safety Between Pertuzumab® and Perjeta® in Neoadjuvant Treatment of HER2+ Breast Cancer: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Comparing Efficacy and Safety Between Pertuzumab® and Perjeta® in Neoadjuvant Treatment of HER2+ Breast Cancer (NCT04957212), a randomized phase 3 study. The primary outcome is Breast Pathological Complete Response (bpCR).

2. Clinical Question

3. Trial Design

This was a phase III, randomized, parallel-group, active-controlled clinical trial in HER2-positive breast cancer. The registry record reports enrollment of 214 and describes the trial as completed. It gives a study start date of 2018-08-11 and a primary completion date of 2020-05-27. The brief summary describes the trial as multicenter and triple-blind, while the registry's masking field says quadruple. These descriptions do not agree, and the registry record does not explain the difference.

Participants were assigned to one of two neoadjuvant TCHP regimens: trastuzumab, pertuzumab, carboplatin, and docetaxel, with either Pertuzumab® (CinnaGen Co.) or Perjeta®. The summary says assignment was stratified dynamically. Both regimens were described as intravenous and administered consecutively on the same day on a 3-weekly schedule. The posted arm descriptions begin to give dosing information but are truncated, so the complete dosing schedules are not reported in the registry record.

The primary endpoint was bpCR, assessed 18-20 weeks after the first intervention. The recorded primary-result denominators are 105 for the CinnaGen pertuzumab arm and 102 for the Perjeta® arm. Secondary outcome domains include total pathological complete response, objective response rate, breast-conserving surgery, treatment-related adverse events, abnormal laboratory data, change in left ventricular ejection fraction, symptomatic left ventricular systolic dysfunction, and immunogenicity. The registry lists 9 outcome measures and 4 analyses. Details on the randomization sequence, concealment, full analysis populations, and the trial's original sample-size justification are not 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.

Overall Study

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 Breast Pathological Complete Response (bpCR), measured over 18-20 weeks after first intervention.

The primary endpoint, breast pathological complete response, is a binary outcome recorded as a participant count. It indicates whether invasive neoplastic cells were absent from the breast on microscopic examination of the primary tumor at surgery after primary systemic therapy. The registry definition specifies ypT0/is. The assessment timeframe is 18-20 weeks after the first intervention.

Pathological response is used in neoadjuvant studies because it is assessed in tissue removed at surgery after systemic treatment, rather than relying only on an earlier clinical or imaging assessment. It captures a treatment response in the breast at the specified time. The registry record does not describe whether other anatomical sites were included in this primary definition; the stated definition is specifically about the breast and primary tumor.

For the CinnaGen pertuzumab regimen, 71 of 105 participants were recorded with bpCR. For the Perjeta® regimen, the posted count was 73 of 102. These counts are the observed endpoint data, not estimates of what would happen in every patient with this disease. The comparison estimate and its confidence interval describe the difference between the recorded group results, while the endpoint itself does not establish that any individual will or will not have a response. Additional rules for handling missing pathology assessments or participants who did not undergo surgery are not reported in the registry record.

7. Results Posted in the Registry

• TCHP Regimen (Trastuzumab, Perjeta®, Carboplatin, and Docetaxel): 71.6% (73/102) versus 67.6% (71/105) on control; risk difference 3.9 percentage points (95% CI -8.6 to 16.5), risk ratio 1.06 (0.88–1.27); unadjusted two-proportion z-test p = 0.537.

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.

Total Pathological Complete Response (tpCR)

• 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:
  • TCHP Regimen (Trastuzumab, Perjeta®, Carboplatin, and Docetaxel): 63.6% (68/107) versus 56.1% (60/107) on control; risk difference 7.5 percentage points (95% CI -5.6 to 20.6), risk ratio 1.13 (0.91–1.41); unadjusted two-proportion z-test p = 0.265.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between TCHP Regimen (Trastuzumab, Perjeta®, Carboplatin, and Docetaxel) and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists secondary domains that cover pathological response, objective tumor response, breast-conserving surgery, treatment-related adverse events, laboratory findings, cardiac measures, and immunogenicity. The detailed quantitative results include total pathological complete response; complete numerical results for every listed outcome are not reported in the registry record. Across the available secondary information, there is no basis for treating a secondary measure as a replacement for the primary bpCR comparison.

Total pathological complete response is a response outcome related to, but distinct from, the breast-specific primary endpoint. Its sponsor-reported analysis is also labeled as a risk-difference comparison. The registry record reports no secondary outcome adjustment for the number of comparisons, and it does not provide a complete multiplicity plan. Secondary outcomes can help describe a broader pattern of response and safety, but their interpretation depends on the endpoint definitions, analysis populations, and uncertainty for each outcome.

When many outcomes are examined, the chance of finding an apparently notable result by chance can increase if each is assessed independently. General statistical context: multiplicity adjustments or a prespecified hierarchy can control how evidence is interpreted across several tests. Without such details, unadjusted secondary p-values carry less weight than a prespecified primary result and should be treated as exploratory rather than as stand-alone confirmation. The registry record does not report whether secondary analyses were prespecified in a hierarchy or adjusted for multiplicity.

The breadth of the listed outcomes is useful for understanding which response and safety domains were considered, but the posted record does not give complete numerical evidence for all of them. It is therefore not possible to describe a comprehensive direction of effect across every secondary outcome. The available secondary findings should be read alongside, not in place of, the primary estimate and its confidence interval.

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

• Total Pathological Complete Response (tpCR)
• Objective Response Rate (ORR)
• Rate of Breast-conserving Surgery (BCS)
• Safety Assessment Including Treatment Related Adverse Events
• Abnormal Laboratory Data
• Decrease in Left Ventricular Ejection Fraction (LVEF)
• Incidence of Symptomatic Left Ventricular Systolic Dysfunction (LVSD)
• Immunogenicity

9. Statistical Interpretation

10. Statistical Methods Explained

The reported primary comparison is a binary-outcome comparison: each participant is counted according to whether bpCR was recorded. The group counts are 71 of 105 and 73 of 102. A risk is the proportion of participants with the outcome in a group. The recalculated risk difference compares those group risks, with positive values indicating a higher risk in the Perjeta® group under the stated subtraction order. The registry's reported analysis uses the reverse group order, so its negative estimate describes the same direction of comparison using the other subtraction order.

What does a risk difference describe?

A risk difference is an absolute contrast between the outcome risks in two groups. It keeps the comparison on the scale of the outcome itself and is distinct from a relative measure such as a risk ratio or odds ratio. The recalculation gives a risk difference of 0.040 and a 95% confidence interval from -0.086 to 0.165. The confidence interval represents uncertainty in the estimated contrast under the method's assumptions. Its inclusion of zero means that a zero difference is among the values compatible with the data at that confidence level; it does not establish that the groups are equivalent.

The record also reports a chi-squared analysis for the primary outcome, with a risk difference of -0.04, a 95% confidence interval from -0.16 to 0.09, and p = 0.54. A chi-squared test assesses whether the observed categorical outcome distribution is compatible with a null hypothesis of no group difference, subject to its assumptions. The recalculation is an unadjusted analysis based on the posted summary counts. The registry does not report whether the sponsor's analysis adjusted for stratification factors or used other covariates.

Why does the equivalence label need context?

Equivalence testing asks whether the uncertainty around a treatment contrast is sufficiently contained within prespecified lower and upper limits that define an acceptable range of difference. These limits, often called an equivalence margin, must be set before interpreting the results. A conventional test of no difference and an equivalence test answer different questions: failure to reject no difference does not demonstrate that the difference is small enough to be considered equivalent. The registry record labels its primary analysis as equivalence, but the margin, hypotheses, and decision procedure are not reported in the registry record. It is therefore possible to describe the label and estimates, but not to verify the formal equivalence conclusion from the posted details.

General statistical context: confidence intervals and p-values are affected by sample size, variability, and the analysis model. A confidence interval is not a range that guarantees the true effect lies within its limits. Instead, under repeated use of the same method and its assumptions, the procedure has a stated coverage property. For an individual study, the interval conveys the range of effect estimates that are reasonably compatible with the data and method. The posted interval is broad enough to include both negative and positive risk differences, making the direction and magnitude uncertain.

What do the other effect measures add?

The recalculation also reports a risk ratio of 1.058, with interval 0.884 to 1.267, and an odds ratio of 1.205, with interval 0.666 to 2.182. A risk ratio compares the group risks multiplicatively; an odds ratio compares the odds of the outcome. These measures use different scales and should not be treated as interchangeable with the risk difference. Their intervals also span the no-association value for their respective scales. They are unadjusted calculations from posted summary statistics, not separate sponsor analyses. The registry's reported primary analysis is the more direct source for the sponsor's stated result.

The primary endpoint is binary, so the recorded result does not require modeling a continuous outcome distribution. The listed analysis method is chi-squared. General statistical context: chi-squared methods compare observed categorical counts with counts expected under a null model. Their adequacy depends in part on the data structure and expected counts. The registry does not give further detail on implementation, continuity corrections, stratification, or model adjustments. The registry also does not report whether an intention-to-treat, per-protocol, or other analysis population was used for the primary equivalence assessment.

Why does over-dispersion matter in other settings?

General statistical context: over-dispersion occurs when observed variability is greater than a model assumes. It matters when a model's standard errors depend on a variance assumption, because underestimating variability can make confidence intervals too narrow and tests too favorable. Over-dispersion is mainly a concern for outcomes analyzed with count or other variance-based models; it is not a separate reported finding for this binary primary comparison. The registry record does not report an over-dispersion assessment or a model-based adjustment.

The analysis is based on the posted endpoint counts, but the registry does not explain how missing outcome information was handled or whether any participants were excluded after assignment. The endpoint denominators differ by arm in the primary results, and the relation between those denominators and the enrollment figure is not explained in the registry record. These details matter because analysis population and missing-data choices can affect the estimated contrast, particularly in an equivalence study where conclusions may depend on how participants with incomplete data are treated.

11. Confidence Intervals and Precision

The recalculated primary risk difference is 0.040, with a 95% confidence interval from -0.086 to 0.165. This interval includes zero and values on both sides of zero. In practical statistical terms, the posted data do not pin down a single direction or a narrow range of possible differences. The interval describes uncertainty around the estimated contrast; it does not imply that every value in the interval is equally likely, and it is not a guarantee about the true effect.

The sponsor's reported risk difference is -0.04, with a 95% confidence interval from -0.16 to 0.09. The sign differs because the sponsor presents the groups in the reverse order. The interval likewise includes zero and extends in both directions. The sponsor's estimate and the unadjusted recalculation should not be compared by sign alone without checking which group is subtracted from which.

The risk ratio interval, 0.884 to 1.267, includes its no-difference value of 1. The odds ratio interval, 0.666 to 2.182, also includes 1. These intervals convey uncertainty on relative scales, while the risk-difference interval conveys uncertainty in absolute risk units. All are based on the posted summary counts for the recalculation.

General statistical context: greater precision usually appears as a narrower interval, while limited information can leave a wide range of effect sizes compatible with the data. Precision is not the same as whether a result is statistically significant, and neither alone answers whether a difference is clinically acceptable. For an equivalence question, precision must be assessed relative to a prespecified equivalence margin. Because that margin is not reported in the registry record, the intervals cannot be used to verify the trial's formal equivalence criterion.

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 participants across both arms and not total events. They are illustrations calculated from the observed effect, rather than the original trial's design justification. The assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation; the effect to detect is the stated fraction of the observed effect. The trial's own original sample-size assumptions are not reported in the registry record.

For the primary endpoint, planning for 100% of the observed effect gives 2,129 participants per arm for 80% power and 2,849 participants per arm for 90% power. Planning for 75% of the observed effect gives 3,819 participants per arm for 80% power and 5,112 participants per arm for 90% power. Planning for 50% of the observed effect gives 8,669 participants per arm for 80% power and 11,605 participants per arm for 90% power.

In plain language, the 80% power column gives the estimated number of participants per arm for a design with an 80% chance of detecting the assumed effect under the stated planning assumptions. The 90% column expresses the corresponding planning target for a higher chance of detecting that effect. Smaller effects need more participants because they are harder to distinguish from random variation. These figures are not observed power, and they do not show whether the completed trial had adequate power for its original question. They are planning illustrations based on the observed effect, which is itself uncertain.

For any sample-size curve associated with these calculations, the same distinction applies: it represents planning under the stated assumptions, not a new result from the trial. The registry does not report the original design effect, the original power target, or the sample-size justification for the equivalence objective. The posted planning figures should therefore be read as hypothetical design guidance tied to the stated fractions of the observed effect, not as evidence that the trial was planned to those targets.

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 = 0.676; treatment proportion p₁ = 0.716; average p̄ = 0.696.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6506 = 1.2751.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6500 = 0.5470.
4. n = (1.2751 + 0.5470)² / (0.0395)² = 2,128.3, rounded up to 2,129 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 <- 0.676190476190476                          # control proportion
p1 <- 0.715686274509804                          # 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(4957212)
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 = 2,129 (80% power), 2,849 (90% power)
 75% of observed effect: n per arm = 3,819 (80% power), 5,112 (90% power)
 50% of observed effect: n per arm = 8,669 (80% power), 11,605 (90% power)
power.prop.test: 2128.3 
Simulated power at n = 2,129 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. Analyses Reported by the Sponsor

The sponsor's posted primary analysis reports a risk difference of -0.04, with a 95% confidence interval from -0.16 to 0.09 and p = 0.54. It uses a chi-squared method and is labeled as an equivalence analysis. The unadjusted recalculation from the posted counts gives a risk difference of 0.040, with a 95% confidence interval from -0.086 to 0.165, and an unadjusted p-value of 0.537.

The opposite signs do not indicate conflicting directions: the sponsor's estimate and the recalculation use opposite group orders for the risk difference. The p-values are close, and both analyses are consistent with substantial uncertainty around the contrast. The recalculation is based directly on the summary counts and is not a substitute for a full participant-level analysis or for the sponsor's prespecified analysis.

The registry record does not report enough detail to reconstruct every feature of the sponsor's analysis, including whether it accounted for the dynamic stratification or how its analysis population was defined. The equivalence margin and formal decision rule are also not reported in the registry record. Thus the numerical agreement in broad direction and scale does not allow independent verification of the equivalence conclusion. The sponsor's own analysis is the reported trial analysis; the recalculation is an unadjusted check based on the posted summaries.

15. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when several hypotheses or outcomes are assessed. Even if each test is conducted using a conventional decision threshold, examining many results can increase the chance that at least one appears noteworthy by chance. This is a general statistical concern, not a claim that any specific secondary result is spurious. The registry lists 9 outcome measures and 4 analyses, but a complete account of prespecification, testing hierarchy, or multiplicity adjustment is not reported in the registry record.

The primary endpoint is identified as bpCR, and the reported analysis is labeled as equivalence. However, the registry does not report the equivalence margin, the detailed hypotheses, or a decision rule. Those details are central to interpreting an equivalence analysis. The record also does not explain whether secondary outcomes were treated as confirmatory, adjusted, or exploratory. As a result, nominal secondary p-values, where posted, should not be interpreted as though the multiplicity strategy were known.

The registry record gives group denominators for the primary endpoint that differ from the enrollment figure, but does not explain the analysis population or the reason for the denominators. It does not report how missing primary endpoint assessments were handled, whether participants without surgery were included, or whether missing values were imputed. These choices can influence an equivalence analysis: excluding participants, counting missing outcomes in a particular way, or using different analysis populations may alter the contrast and its uncertainty.

The record does not specify whether the primary analysis was intention-to-treat, modified intention-to-treat, per-protocol, or another population. It also does not report a sensitivity analysis examining the effect of missing data or departures from protocol. General statistical context: equivalence trials often benefit from examining more than one analysis population because exclusions and nonadherence can make groups look more similar. That general concern cannot establish what occurred in this trial; the relevant procedures are not reported in the registry record.

Without these details, interpretation should stay close to the posted endpoint counts, estimates, confidence intervals, and labeled analysis. The unavailable information limits assessment of robustness and the strength of formal equivalence claims, rather than changing the numerical results that are posted.

16. 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 0% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: anaemia (13.1%), thrombocytopenia (5.6%), vomiting (4.7%), nausea (3.7%), diarrhoea (2.8%).

The serious adverse event figures are reported for groups of 107 participants at risk in each arm. Serious adverse events affected 24 participants in the CinnaGen pertuzumab regimen group and 15 in the Perjeta® regimen group. The record reports zero deaths in each group. These figures describe the registry's reported counts; they do not by themselves establish that a difference between groups is reliable or attributable to the pertuzumab product.

The listed serious-event terms include anaemia at 13.1%, thrombocytopenia at 5.6%, vomiting at 4.7%, nausea at 3.7%, diarrhoea at 2.8%, and febrile neutropenia at 1.9%. The registry record does not explain in the posted material whether these terms are percentages of all participants, how overlapping events were counted, or whether the listed events occurred in one or both groups. The figures should therefore be read as the recorded serious-event terms and percentages, without inferring group-specific rates from them.

The record also reports other adverse events affecting 107 of 107 participants in the CinnaGen group and 104 of 107 in the Perjeta® group. Safety counts can be affected by follow-up duration, event definitions, and ascertainment procedures, which are not fully described in the registry record. These observations summarize reported events and are not a complete safety assessment or an individualized prediction.

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

The posted results describe a randomized comparison of two neoadjuvant TCHP regimens that differed in the pertuzumab product used. For the primary breast pathological complete response outcome, the observed counts were 71 of 105 in the CinnaGen pertuzumab arm and 73 of 102 in the Perjeta® arm. The unadjusted risk difference estimate and its interval show uncertainty in the size and direction of the contrast. The registry also labels the sponsor's primary analysis as an equivalence analysis.

These results do not establish that the regimens are identical. Equivalence requires a prespecified margin and a confidence interval or test evaluated against that margin; the margin and complete decision procedure are not reported in the registry record. Nor does a nonsignificant p-value prove equivalence. The estimates are compatible with a range of differences, including no difference, and should be interpreted with the interval rather than as a binary verdict based on the p-value alone.

The comparison concerns the regimens as administered in the trial, not pertuzumab in isolation. Both arms included trastuzumab, carboplatin, and docetaxel, and the intervention was neoadjuvant. The primary endpoint concerns absence of invasive neoplastic cells in the breast at surgery at the stated assessment timeframe. It does not on its own report outcomes beyond that measure or establish what will happen for an individual participant.

The registry record provides some safety counts and a limited set of secondary results, but not complete details on every listed outcome, missing data, analysis populations, or the original statistical plan. Those limitations constrain how strongly the results can be generalized or how fully the formal equivalence claim can be evaluated. The findings are best understood as posted estimates from this trial, with their stated uncertainty and documentation gaps.

No treatment recommendation follows from these statistics alone. Clinical decisions require broader evidence and individual context, neither of which is assessed by this registry comparison.

18. Why This Trial Matters Statistically

This trial is statistically notable because it is described as an equivalency study. Equivalence questions differ from the more familiar question of whether there is evidence of any difference. A study can fail to detect a difference and still leave substantial uncertainty about whether the treatments fall within an acceptable equivalence range. The margin that defines that range is therefore essential for interpreting an equivalence claim, yet it is not reported in the registry record.

The posted results also illustrate why a point estimate and a p-value are not enough. The primary comparison has a risk-difference estimate and a confidence interval that extends on both sides of zero. The interval communicates the uncertainty in a way that a single p-value cannot. The sponsor and the unadjusted recalculation present the groups in opposite orders, demonstrating why the direction of a risk difference must be read together with its subtraction convention.

Another statistical issue is the distinction between a trial's planned sample size and a retrospective planning illustration based on the observed effect. The registry's planning figures use the observed effect and stated hypothetical assumptions, whereas the original design justification is not reported. The illustrations help explain how required sample size changes with the effect one aims to detect, but they cannot establish what the investigators planned or the power of the completed study.

Finally, the record lists several response and safety outcomes but does not fully document multiplicity handling, missing-data procedures, or analysis populations. These details are especially relevant when interpreting equivalence and secondary results. Together, the trial offers a useful example of how statistical interpretation depends not only on the observed counts, but also on confidence intervals, the estimand, the decision margin, and the completeness of the reporting.

19. Limitations

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

The registry record does not report the equivalence margin or the detailed prespecified rule used to declare equivalence. This is a major limitation for assessing the study's stated objective: the reported p-value and an interval that includes zero do not alone establish equivalence. The posted record also does not give the original sample-size justification, design effect, or planned power target, so the planning illustrations cannot be used to evaluate the original design.

The masking descriptions are inconsistent: the brief summary calls the trial triple-blind, while the registry masking field says quadruple. The record does not explain the difference. The arm descriptions are truncated after the beginning of the dosing details, leaving the complete dose schedules unavailable. The registry identifies dynamic stratification but does not report the stratification variables or the allocation-concealment procedure.

The primary outcome denominators are 105 and 102, while enrollment is 214. The registry record does not explain the relationship between these figures, the analysis population, or the missing-data handling. It does not report whether the primary analysis was intention-to-treat or per-protocol, nor does it describe sensitivity analyses for missing outcomes or protocol deviations. Such information is important for an equivalence interpretation.

The registry lists multiple secondary outcomes but does not report a complete multiplicity strategy or complete numerical findings for all listed outcomes. The safety summary gives group counts for serious events and other events, but event definitions, ascertainment details, and duration of follow-up are not reported in the posted material. Finally, the registry provides no details on generalizability beyond the stated HER2-positive early breast cancer population and study setting. These reporting gaps limit independent appraisal; they do not alter the reported counts themselves.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Comparing Efficacy and Safety Between Pertuzumab® and Perjeta® in Neoadjuvant Treatment of HER2+ Breast Cancer — NCT04957212.
• Registry record last updated 2024-07-26; status last verified 2024-02.
• Results first posted 2024-07-26.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

23. Record Summary

The registry record describes a completed phase III, randomized, parallel, active-controlled trial with enrollment of 214 participants with HER2-positive breast cancer. It compared neoadjuvant TCHP regimens containing either Pertuzumab® (CinnaGen Co.) or Perjeta®. The stated primary endpoint was breast pathological complete response assessed 18-20 weeks after the first intervention.

The posted primary counts were 71 of 105 for the CinnaGen regimen and 73 of 102 for the Perjeta® regimen. The sponsor-reported risk difference was -0.04, with a 95% confidence interval from -0.16 to 0.09 and p = 0.54; the analysis was labeled equivalence. The equivalence margin and key analysis details are not reported in the registry record, limiting independent evaluation of that label. Secondary response and safety outcomes are listed, but results and methodological details are incomplete.