Translational and Real-World Evidence of Trastuzumab Biosimilar CT-P6 Plus Pertuzumab in Neoadjuvant HER2-Positive Early Breast Cancer

Translational and Real-World Evidence of Trastuzumab Biosimilar CT-P6 Plus Pertuzumab in Neoadjuvant HER2-Positive Early Breast Cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Translational and Real-World Evidence of Trastuzumab Biosimilar CT-P6 Plus Pertuzumab in Neoadjuvant HER2-Positive Early Breast Cancer José Luis Alonso-Romero, Jerónimo Martínez-García, Raúl Carrillo-Vicente, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8020339/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Jan, 2026 Read the published version in Breast Cancer Research and Treatment → Version 1 posted 7 You are reading this latest preprint version Abstract Background Data on neoadjuvant treatment with trastuzumab biosimilars, particularly CT-P6, in combination with pertuzumab, are limited. This study evaluates the efficacy, tolerability, and immunogenicity of CT-P6 plus pertuzumab and chemotherapy, according to routine clinical practice, in the neoadjuvant setting for HER2-positive early breast cancer, while integrating translational biomarker analyses and exploratory predictors of pathologic complete response (pCR). Methods Prospective, multicenter, observational study in 102 patients with HER2-positive early breast cancer. Patients received hospital-preferred neoadjuvant regimens protocol, with (scheme 1 and 3) or without anthracyclines (scheme 2). The primary endpoint was pCR in breast tissue and axilla. Translational endpoints included soluble HER2, anti-trastuzumab CT-P6 antibodies, and exploratory response prediction models validated using machine learning approaches. Results Overall, pCR was achieved in 60.40% of patients in the breast and 80.20% in the axilla, with no significant differences between anthracycline-based and non-anthracycline-based regimens. Soluble HER2 and anti-trastuzumab CT-P6 antibodies were not significantly associated with pCR. Treatment was well tolerated; the most relevant Grade 3–4 treatment-related adverse events were diarrhea (2.25%) and asthenia (0.50%). No immunogenicity or clinically relevant cardiotoxicity was observed. Conclusions Trastuzumab CT-P6 combined with pertuzumab and chemotherapy can be used in neoadjuvant treatment for HER2-positive early breast cancer, showing pCR rates comparable to the reference trastuzumab and without evidence of immunogenicity. Exploratory analyses of soluble HER2 and anti-trastuzumab CT-P6 antibodies did not show predictive value for pCR, although this possibility cannot be excluded. Their systematic assessment nevertheless contributes to the translational understanding of biosimilar integration into curative regimens. Trial registration: The study has been registered in Clinicaltrials.gov ( https://clinicaltrials.gov/study/NCT06907082 ). HER2-positive early breast cancer neoadjuvant treatment routine clinical practice trastuzumab biosimilar trastuzumab CT-P6 Figures Figure 1 Background Breast cancer is the most common malignancy in women in developed countries and the leading cause of cancer death in women. In developed countries most patients with breast cancer are diagnosed at an early stage [ 1 ]. HER2-positive breast cancer is associated with a poor prognosis and accounts for 13–15% of breast cancer cases [ 2 , 3 ]. Randomized trials have found no difference in long-term outcomes when chemotherapy is given before or after surgery [ 4 ]. Neoadjuvant chemotherapy (NACT) has traditionally been used to improve the surgical outcome of locally advanced tumors, but it also provides important prognostic information based on response and is associated with higher breast preservation rates [ 5 , 6 ]. Achievement of pathologic complete response (pCR) after NACT is associated with increased progression-free survival and overall survival in HER2 positive breast cancer [ 4 – 7 ]. In tumors that overexpress or amplify HER2, NACT with dual anti-HER2 blockade is indicated as standard of care according to the 2017 St. Gallen consensus conference [ 8 ]. Trastuzumab and pertuzumab are recombinant humanized monoclonal antibodies that target different extracellular regions of the HER2 receptor. In the different clinical trials to date, neoadjuvant treatment with dual blockade with pertuzumab and trastuzumab against HER2-positive tumors has been shown to provide a high rate of pCR, with acceptable tolerance, with a slight increase in left ventricular ejection fraction (LVEF) reduction, but with rare events of clinical cardiac dysfunction [ 9 – 13 ]. However, a standard chemotherapy regimen to accompany dual anti-HER2 blockade is not yet available. The emergence of biosimilars in general, and trastuzumab biosimilars in particular, is contributing to the economic sustainability of healthcare systems. Beyond demonstrating clinical efficacy and safety, the integration of biosimilars into curative settings requires robust translational evaluation, including immunogenicity and biomarker analyses, to ensure their reliability in combination regimens. The biosimilar CT-P6 (trastuzumab-pkrb, Herzuma®, Celltrion, South Korea) is a trastuzumab biosimilar approved by the European Medicines Agency (EMA) for use in the same indications as the reference biologic [ 14 ]. Preclinical development and clinical studies showed no differences between CT-P6 and the reference product [ 15 ]. Currently, the information available on the use of neoadjuvant treatment with pertuzumab and trastuzumab biosimilars is very limited, especially for the trastuzumab biosimilar CT-P6. To date, no prospective study has explored not only the real-world efficacy of trastuzumab CT-P6 in combination with pertuzumab, but also its immunogenicity profile and potential translational biomarkers of response in the neoadjuvant setting. Therefore, we designed a study to prospectively analyze the use of the trastuzumab CT-P6 in the neoadjuvant setting of HER2-positive early breast cancer in combination with pertuzumab and chemotherapy according to the routine clinical practice (RCP), with the objective of analyzing the efficacy, tolerability, immunogenicity data collected to corroborate the safe use of trastuzumab CT-P6 in the neoadjuvant setting, and to explore clinical and biomarker predictors of pCR with this combination. Methods Study design and participants This was a prospective, observational (non-interventional), open-label, multicenter study conducted in 5 Spanish hospitals with experience in breast cancer treatment. All participants had HER2-positive early breast cancer amenable to neoadjuvant treatment with chemotherapy and dual anti-HER2 blockade. The study was registered in Clinicaltrials.gov ( https://clinicaltrials.gov/study/NCT06907082 ). Main inclusion criteria were women aged 18 years or older, with a diagnosis of HER2-positive breast cancer confirmed by immunohistochemistry (IHC) of 3 + or positive fluorescence in situ hybridization (FISH) result, and early stage without systemic dissemination amenable to neoadjuvant treatment with chemotherapy and dual anti-HER2 blockade with pertuzumab and trastuzumab CT-P6 according to ESMO guideline 2019 [ 16 ]. Exclusion criteria included metastatic breast cancer, known hypersensitivity to trastuzumab or pertuzumab, current treatment with an investigational agent, diagnosis of any other neoplastic pathology of prognostic relevance within the previous two years except cervical or breast carcinoma in situ and basal cell or squamous cell carcinoma of the skin, non-neoplastic pathology with a life expectancy of less than one year, and pregnancy or lactation. The study was conducted in full compliance with the principles of the Declaration of Helsinki and the Good Pharmacoepidemiology Practices (GPP), as well as with all Spanish legislation applicable to observational studies (Order SAS/3470/2009). The study was evaluated and approved by the Ethics Committee (2020-3-2-HCUVA) of the Hospital Clínico Universitario Virgen de la Arrixaca, Murcia, Spain. All patients provided written informed consent. Procedures and outcomes Patients were treated in accordance with the preferred hospital protocol, primarily regarding the use or non-use of anthracyclines. Only three treatment schemes were allowed: 1) Scheme 1 : Adriamycin 60 mg/m 2 (or epirubicin 90 mg/m 2 ) + cyclophosphamide 600 mg/m 2 x 4 cycles, every 15 or 21 days (according to the usual clinical protocol of the service), followed by paclitaxel 80 mg/m 2 weekly x 12 weeks (or docetaxel 100 mg/m 2 every 3 weeks x 4), pertuzumab 840 mg in cycle 1 and 420 mg in cycles 2–4 (cycles every 21 days) + trastuzumab CT-P6 8 mg/kg in cycle 1 and 6 mg/kg in cycles 2–4 (cycles every 21 days). 2) Scheme 2 : docetaxel 75 mg/m 2 every 3 weeks x 6 cycles + carboplatin 5 or 6 AUC every 3 weeks x 6 cycles + pertuzumab 840 mg in cycle 1 and 420 mg in cycles 2–6 (cycles every 21 days) + trastuzumab CT-P6 8 mg/kg in cycle 1 and 6 mg/kg in cycles 2–6 (cycles every 21 days). 3) Scheme 3 : paclitaxel 100 mg/m 2 weekly x 8 weeks + pertuzumab 840 mg in cycle 1 and 420 mg in cycles 2–3 (cycles every 21 days) + trastuzumab CT-P6 8 mg/kg in cycle 1 and 6 mg/kg in cycles 2–3 (cycles every 21 days) (both administered together with doses 1, 4 and 7 of paclitaxel), followed by epirubicin 90 mg/m 2 every 3 weeks + pertuzumab and trastuzumab CT-P6 IV every 3 weeks, with the same doses x 4 cycles. The primary endpoint was the pCR in breast tissue and axilla in patients with HER2-positive early breast cancer after neoadjuvant treatment. pCR was defined as the absence of infiltrating tumor cells in the breast tumor (ypT0/is) and any tumor cells in the axilla (ypN0). Demographic, clinical, tumor, efficacy and toxicity data were collected. In addition to standard clinical outcomes, a translational substudy was integrated to assess soluble HER2 plasma levels, anti-trastuzumab CT-P6 antibodies, and exploratory prediction models using machine learning techniques. Three blood samples were additionally taken (immunogenicity and Her2 soluble protein): sample 1 (M1) or baseline sample obtained prior to the start of oncological treatment with dual anti-HER2 blockade, sample 2 (M2) obtained in cycle 4 of NACT with dual anti-HER2 blockade, and sample 3 (M3) obtained 10 days prior to surgery or at the post-surgical visit. The translational study added in this project was conducted concurrently with routine blood sampling, requiring no additional venipunctures. Statistical analysis A sample size of 96 was planned considering a pCR rate of 52.8%, a precision of 10% in a bilateral analysis, an alpha risk of 0.05, and a power of 0.8 (estimating a 10% loss rate, a total sample size of 106 patients should be recruited). A descriptive analysis was conducted in which quantitative variables were summarized using measures of central tendency and dispersion, including the mean, standard deviation, median, minimum, and maximum values. Categorical variables were described using absolute frequencies and corresponding percentages. For the purpose of analysis, treatment schemes 1 and 3 were grouped together, resulting in two comparison groups: Scheme 1 + 3 and Scheme 2 , corresponding to anthracycline-based versus non-anthracycline-based regimens, respectively. For the inferential analysis, parametric tests were applied to continuous variables, while nonparametric tests were employed for ordinal, categorical, or non-normally distributed variables. All hypothesis testing was conducted using two-tailed tests with a significance level set at 0.05. For variables that did not meet the assumptions of normality, the Mann–Whitney U test was used for unpaired data, and the Wilcoxon signed-rank test was applied for paired data. The comparison of categorical variables was performed using the Chi-square test or Fisher’s exact test, as appropriate. The findings from the response prediction analysis were validated through the application of machine learning algorithms, including decision trees, random forest, and clustering techniques. The analysis was conducted using Python, along with relevant scientific libraries such as NumPy and SciPy . Results Patients and treatment A total of 106 patients were included in the study. Four patients were excluded from the study (three withdrew their consent, and one received a different subcutaneous trastuzumab than the study treatment). Therefore, the final number of evaluable patients was 102. Patient characteristics at baseline are shown in Table 1 . Since only 2 patients from a single hospital were included in Scheme 3, and as it was a scheme with anthracyclines and taxanes that was highly similar to Scheme 1 , it was decided to merge Schemes 1 and 3 for analysis. However, the data were also analyzed independently and can be found in Supplementary Table S1 . The median age of the patients was 52 years, ranging from 30 to 78 years old. Of the 102 patients receiving NACT, 55 (53.92%) received Scheme 2 , and 47 (46.08%) received Scheme 1 + 3. Table 1 Patient demographics at baseline. All patients n = 102 NACT Scheme 2 n = 55 NACT Scheme 1 + 3 n = 47 Age (years), median (range) 52.00 (30–78) 56.00 (36–74)* 45.00 (30–78)* 0 to < 40 20 (19.61%) 6 (10.91%) 14 (29.79%) 40 to < 65 64 (62.74%) 37 (67.27%) 27 (57.45%) ≥ 65 18 (17.65%) 12 (21.82%) 6 (12.76%) Menopausal state Pre-menopause 46 (45.10%) 17 (30.91%)* 29 (61.70%)* Post-menopause 56 (54.90%) 38 (69.09%)* 18 (38.30%)* ER Positive 58 (56.86%) 33 (60.00%) 25 (53.19%) Negative 44 (43.14%) 22 (40.00%) 22 (46.81%) PR Positive 37 (36.27%) 23 (41.82%) 14 (29.79%) Negative 65 (63.73%) 32 (58.18%) 33 (70.21%) ER and/or PR Positive 59 (57.84%) 33 (60.00%) 26 (55.32%) Negative 43 (42.16%) 22 (40.00%) 21 (44.68%) Ki67 Ki67 < 20 20 (19.61%) 11 (20.00%) 9 (19.15%) Ki67 ≥ 20 82 (80.39%) 44 (80.00%) 38 (80.85%) HER2 2+ (FISH amplified) 20 (19.61%) 11 (20.00%) 9 (19.15%) 3+ 82 (80.39%) 44 (80.00%) 38 (80.85%) Tumor distribution Unique 68 (66.66%) 36 (65.44%) 32 (68.08%) Multifocal 19 (18. 63%) 9 (16.36%) 10 (21.28%) Multicentric 14 (13.73%) 9 (16.36%) 5 (10.64%) Unknown 1 (00.98%) 1 (01.82%) 0 Number of focus 1 67 (66.34%) 37 (7.26%) 30 (65.21%) 2 15 (14.85%) 7 (12.73%) 8 (17.39%) 3 6 (5.94%) 2 (3.64%) 4 (8.70%) >4 8 (7.84%) 7 (12.73%) 1 (2.17%) Unknown 5 (4.95%) 2 (3.64%) 3 (6.52%) Size of biggest tumor (mm), median (range) 30.50 (10–110) 35.00 (11–90) 30.00 (10–110) 0 to < 20 14 (13.72%) 5 (9.09%) 9 (19.15%) 20 to < 50 71 (69.61%) 39 (70.91%) 32 (68.08%) ≥ 50 17 (16.67%) 11 (20.00%) 6 (12.77%) Histologic grade G1 9 (8.82%) 3 (5.45%) 6 (12.77%) G2 44 (43.14%) 21 (38.18%) 23 (48.94%) G3 35 (34.31%) 29 (52.73%) 6 (12.77%) GX 14 (13.73%) 2 (3.64%) 12 (25.53%) Histological subtype Ductal NOS 94 (92.16%) 53 (96.36%) 41 (87.23%) Other subtypes a 8 (7.84%) 2 (3.64%) 6 (12.7%) cN 0 50 (49.02%) 22 (40.00%) 28 (59.57%) 1 26 (25.49%) 16 (29.09%) 10 (21.28%) 2 16 (15.69%) 10 (18.18%) 6 (12.77%) 3 7 (6.86%) 6 (10.91%) 1 (2.13%) x 3 (2.94%) 1 (1.82%) 2 (4.25%) cT 1 13 (12.74%) 7 (12.73%) 6 (12.76%) 2 66 (64.71%) 35 (63.63%) 31 (65.96%) 3 19 (18.63%) 10 (18.18%) 9 (19.15%) 4 2 (1.96%) 1 (1.82%) 1 (2.13%) x 2 (1.96%) 2 (3.64%) 0 (0.00%) Time to surgery (days), median (range) 68.50 (28–147) 56.00 (28–140) 84.00 (47–147) Type of surgery b - breast Conservative surgery 63 (62.38%) 34 (61.82%) 29 (63.04%) Mastectomy 38 (37.62%) 21 (38.18%) 17 (36.96%) Type of surgery b – axilla SLNB 62 (62.63%) 26 (49.06%) 36 (78.26%) Lymphadenectomy 37 (37.37%) 27 (50.94%) 10 (21.74%) Number of cycles of CT-P6 + pertuzumab, median (range) -- 6.0 (4–6) 4.0 (3–4) Data are number (%) unless otherwise specified. a Other histological subtypes include medullar, lobular, apocrine, and invasive carcinoma with micropapillary ductal and papillary type areas. b Of the 102 patients, 1 was not operated due to COVID-19; therefore, 101 patients underwent breast surgery and 99 underwent axillary surgery. * Indicates statistically significant difference between Scheme 2 and Scheme 1 + 3 ( p < 0.05). cN, clinical node stage; cT, clinical tumor stage; ER, estrogen receptor; FISH, fluorescence in situ hybridization; G1, well differentiated; G2, moderately differentiated; G3, poorly differentiated; GX, not classified; HER2, human epidermal growth factor receptor 2; NACT, neoadjuvant chemotherapy; NOS, no other specifications; PR, progesterone receptor; Scheme 2 , with anthracyclines; Scheme 1 + 3, without anthracyclines; SLNB, sentinel lymph node biopsy. The comparison of the study population by Scheme found a significant difference in age ( p = 0.001044), and in the menopausal state ( p = 0.002655). Patients in Scheme 1 + 3 were younger, and there were more pre-menopausal patients (see Table 1 ). Efficacy Table 2 shows pCR results obtained after NACT with dual anti-HER2 blockade. Of the 102 patients included in the study, 101 underwent surgery. One patient, despite completing all other study procedures, was not operated on due to a COVID-19 infection and was therefore excluded from the pathologic complete response evaluation. Table 2 Pathologic complete response (pCR) after surgery. All patients n = 101 a NACT Scheme 2 n = 55 NACT Scheme 1 + 3 n = 46 a pCR - Global Breast 61 (60.40%) 29 (52.73%) 32 (69.57%) Axilla 81 (80.20%) 41 (74.55%) 40 (86.96%) Breast & axilla 58 (57.43%) 29 (52.73%) 29 (63.04%) pCR - HR negative Breast 35 (83.33%) 17 (77.27%) 18 (90.00%) Axilla 37 (88.10%) 19 (86.36%) 18 (90.00%) Breast & axilla 33 (78.57%) 17 (77.27%) 16 (80.00%) pCR - HR positive Breast 26 (44.83%) 12 (37.50%) 14 (53.85%) Axilla 44 (75.86%) 22 (68.75%) 22 (84.62%) Breast & axilla 25 (43.10%) 12 (37.50%) 13 (50.00%) ypT ypT0 55 (54.46%) 26 (47.27%) 29 (63.05%) ypT1 32 (31.68%) 19 (34.55%) 13 (28.26%) ypT2 8 (7.92%) 7 (12.73%) 1 (2.17%) ypTis 6 (5.94%) 3 (5.45%) 3 (6.52%) ypN 0 81 (80.20%) 41 (74.55%) 40 (86.96%) 1 16 (15.84%) 10 (18.18%) 6 (13.04%) 2 2 (1.98%) 2 (3.64%) 0 (0.00%) 3 2 (1.98%) 2 (3.64%) 0 (0.00%) Data are number (%) unless otherwise specified. a Of the 102 patients, 1 was not operated due to COVID-19, and therefore was not included in the pathologic complete response evaluation after surgery. HR, hormonal receptor; NACT, neoadjuvant chemotherapy; pCR, pathologic complete response; ypN, lymph nodes in axilla; Scheme 2 , with anthracyclines; Scheme 1 + 3, without anthracyclines; ypT, tumor cells in breast tissue. pCR was achieved globally by 60.40% (61/101) of patients in breast and 80.20% (81/101) of patients in axilla. The percentage of patients achieving pCR both in breast and axilla (ypT0 + ypTis and ypN0) was 57.43% (58/101) globally, 52.73% (29/55) with Scheme 2 , and 63.04% (29/46) with Scheme 1 + 3. The comparative analysis of Schemes 2 and 1 + 3 revealed no significant differences in pCR, regardless of whether the results were examined in the breast ( p = 0.149643), in the axilla ( p = 0.204635), or in both the breast and axilla ( p = 0.417684). There was a significant negative association for the size of the biggest tumor in Scheme 1 + 3 in breast (correlation − 0.300048, p = 0.0053533) and in breast + axilla (correlation − 0.350816, p = 0.022734); and a significant positive association also for the size of the biggest tumor in Scheme 2 , in breast and in breast + axilla (in both cases, correlation − 0.449599, p = 0.01638). Translational analysis Translational endpoints included soluble HER2 and anti-trastuzumab CT-P6 antibody plasma levels, as well as exploratory prediction analyses validated with machine learning algorithms (due to the substantial size of the validation study employing machine learning techniques, the results will be incorporated into a subsequent publication). No anti-trastuzumab CT-P6 antibodies were detected at any timepoint. Soluble HER2 plasma levels did not show significant correlation with pCR. Biomarkers were obtained in 97.06% (99/102) of patients at M1, 94.12% (96/102) of patients at M2, and 85% (90/102) of patients at M3. As shown in Table 3 , the plasma concentrations of soluble HER2 and anti-trastuzumab CT-P6 antibodies are reported globally and by Scheme. Figure 1 illustrates the evolution of the mean plasma levels of HER2 (Fig. 1 A) and Trastuzumab CT-P6 (Fig. 1 B) by treatment Scheme. Soluble HER2 plasma concentration slightly increased in Scheme 2 , while decreased in Scheme 1 + 3, but there were no significant differences between both Schemes. Also, anti-trastuzumab CT-P6 antibody plasma levels slightly increased in Scheme 2 and decreased in Scheme 1 + 3, and no significant differences were found between both Schemes. Table 3 Soluble HER2 and anti-Trastuzumab CT-P6 antibodies plasma concentration. All patients n = 102 NACT Scheme 2 n = 55 NACT Scheme 1 + 3 n = 47 HER2 (ng/ml), median (range) M1 0.06 (0.00-0.81) 0.05 (0.00-0.39) 0.09 (0.00-0.81) 0.0 to < 0.01 5 (7,14%) 2 (7.69%) 3 (6.98%) 0.01 to < 1.0 65 (92.86%) 24 (92.31%) 40 (93.02%) M2 0.05 (0.00-0.27) 0.04 (0.00-0.24) 0.06 (0.00-0.27) 0.0 to < 0.01 7 (9.86%) 3 (10.71%) 4 (9.30%) 0.01 to < 1.0 64 (90.14%) 25 (89.29%) 39 (90.70%) M3 0.06 (0.00-0.41) 0.05 (0.00-0.41) 0.06 (0.00-0.36) 0.0 to < 0.01 6 (8.45%) 1 (3.57%) 5 (11.63%) 0.01 to < 1.0 65 (91.55%) 27 (96.43% 38 (88.37%) Trastuzumab CT-P6 (ng/ml), median (range) M1 5.38 (0.00-26.92) 5.38 (0.00-8.52) 5.00 (2.22–26.92) 0.0 to < 0.01 1 (1.43%) 1 (3.85%) 0 (0.00%) 0.01 to < 30.0 69 (98.57%) 25 (96.15%) 43 (100.00%) M2 5.38 (0.00–20.00) 5.10 (0.00–20.00) 5.42 (2.59–17.31) 0.0 to < 0.01 1 (1.41%) 1 (3.57%) 0 (0.00%) 0.01 to < 30.0 70 (98.59%) 27 (96.43%) 43 (100.00%) M3 5.00 (0.00–15.00) 5.80 (2.59-15.00) 4.62 (0.00-11.85) 0.0 to < 0.01 1 (1.41%) 0 (0.00%) 1 (2.33%) 0.01 to < 30.0 70 (98.59%) 28 (100.00%) 42 (97.67%) Data are number (%) unless otherwise specified. HER2, human epidermal growth factor receptor 2; M1, measurement corresponding to the baseline sample obtained prior to the start of oncological treatment with dual anti-HER2 blockade; M2, measurement corresponding to the sample obtained in cycle 4 of NACT with dual anti-HER2 blockade; M3, measurement corresponding to the sample obtained 10 days prior to surgery or at the post-surgical visit; NACT, neoadjuvant chemotherapy; Scheme 2 , with anthracyclines; Scheme 1 + 3, without anthracyclines. No significant correlations were found between pCR and soluble HER2 (phi = 0.334052), or with anti-trastuzumab CT-P6 antibodies (phi = 0.331133). Safety Globally, the most relevant treatment-related adverse events (AEs) in Scheme 2 were diarrhea (21.75%), mucositis (19.00%), nausea (17.88%), and asthenia (17.62%), while in Scheme 1 + 3 were asthenia (7.25%) and mucositis (5.25%) (see Table 4 ). Table 4 More relevant treatment-related adverse events per cycle. NACT Scheme 2 n = 55 NACT Scheme 1 + 3 n = 47 Global Grade 1&2 Grade 3&4 Required admission Global Grade 1&2 Grade 3&4 Required admission Diarrhea 21.75%* 19.38%* 2.25%* 0.88%* 4.00%* 4.00%* 0.00%* 0.00%* Mucositis 19.00%* 18.62%* 0.00% 0.00% 5.25%* 5.25%* 0.00% 0.00% Nausea 17.88%* 17.12%* 0.62% 0.25% 4.88%* 4.88%* 0.00% 0.00% Asthenia 17.62%* 17.38%* 0.12% 0.25% 7.25%* 6.75%* 0.50% 0.00% GI toxicity 10.88%* 10.62%* 0.12% 0.25% 2.62%* 2.38%* 0.00% 0.00% Anemia 7.75%* 7.00%* 0.62% 0.00% 0.50%* 0.50%* 0.00% 0.00% Neuropathic toxicity 5.58%* 5.75%* 0.00% 0.00% 3.12%* 3.12%* 0.00% 0.00% Neutropenia 4.00%* 2.50%* 1.50% 0.12% 1.25%* 0.38%* 0.88% 0.00% Neutropenic fever 0.00% 0.00% 0.25% 0.38% 0.00% 0.25% 0.12% 0.12% LVEF alteration 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Data are in percentage per cycle. * Indicates statistically significant difference between Scheme 2 and Scheme 1 + 3 ( p < 0.05). GI, gastrointestinal; LVEF, left ventricular ejection fraction; NACT, neoadjuvant chemotherapy; Scheme 2 , with anthracyclines; Scheme 1 + 3, without anthracyclines. The most relevant Grade 3&4 treatment-related AEs were diarrhea (2.25%) in Scheme 2 and asthenia (0.50%) in Scheme 1 + 3. The most relevant treatment-related AEs requiring hospital admission were diarrhea (0.88%) in Scheme 2 and neutropenic fever (0.12%) in Scheme 1 + 3. The percentage of patients requiring a dose reduction was 32.73% in Scheme 2 , and 22.45% in Scheme 1 + 3. The mean percentage of cycles with dose reduction was 40.09% for Scheme 2 , and 30.13% for Scheme 1 + 3. There were no deaths or AEs leading to death. The comparison of treatment-related AEs rates between Scheme 2 and Scheme 1 + 3 revealed that Scheme 2 had a significantly higher proportion of AEs. Significant differences (p < 0.05) were observed between the two schemes in nearly all parameters overall and for Grades 1&2, while for Grades 3&4, significance was found only for diarrhea. Regarding cardiac safety, no significant issues were identified, and LVEF remained unaffected. Discussion The primary objective of this study was to evaluate the efficacy, safety and immunogenicity of the trastuzumab CT-P6 in combination with pertuzumab and chemotherapy as neoadjuvant treatment in patients with HER2-positive early breast cancer in RCP according to pCR in breast and axilla. The results confirm that this regimen is effective, with 57% of all patients achieving full pCR both in breast and axilla, increasing to 63% of patients when receiving Scheme 1 + 3. Notably, when evaluated separately, while 60% of all patients achieved pCR in breast, a higher percentage of patients (80%) achieved pCR in axilla, consistent with known patterns of differential tumor response [ 17 ]. Despite the absence of a direct comparison with the original trastuzumab in this study, the results align with those of other published works using the original trastuzumab. The pCR results are similar although slightly lower than those found in the studies by Bernat-Peguera and Bae [ 18 , 19 ]. These studies compared the pCR rate in HER2-positive early breast cancer patients treated with either trastuzumab CT-P6 or reference trastuzumab, and found that patients treated with CT-P6 achieved pCR rates of 65% and 74.4%, respectively. This study is, to our knowledge, the first to prospectively evaluate immunogenicity and biomarker dynamics of a trastuzumab biosimilar in combination with pertuzumab in the neoadjuvant setting. It is important to highlight the absence of immunogenicity measured in the context of this trastuzumab biosimilar. This study is the first to evaluate trastuzumab CT-P6 immunogenicity when combined with pertuzumab in a neoadjuvant setting. No anti-trastuzumab CT-P6 antibodies were detected in any patient during treatment, which corroborates the findings of previous studies that reported low immunogenic potential for trastuzumab CT-P6 [ 20 , 21 ]. These findings reinforce the safety and reliability of this biosimilar, even when co-administered with another monoclonal antibody. The absence of anti-trastuzumab CT-P6 antibodies, even in the context of dual monoclonal antibody blockade, provides important translational reassurance of biosimilar safety at the immune interface. Despite the disparities in age and menopausal status identified by Scheme, while Scheme 1 + 3 exhibited a preponderance of younger patients and a higher proportion of premenopausal subjects, these observations had no impact on the outcomes concerning efficacy, as no significant differences in pCR were observed between the two Schemes. The results of the correlation analysis indicated a positive correlation between the extent of the tumor and the degree of response, with smaller tumors exhibiting higher levels of pCR. These findings are clinically reasonable and consistent with the observed responses. The comparison of Scheme 2 and Scheme 1 + 3 with respect to soluble HER2 plasma concentrations and anti-trastuzumab CT-P6 antibody plasma levels revealed no significant differences. The slight increase in anti-trastuzumab CT-P6 antibody plasma levels observed in Scheme 2 could be attributed to the number of trastuzumab CT-P6 + pertuzumab cycles administered to patients in this Scheme (median of 6 cycles), compared to Scheme 1 + 3 (median of 4 cycles). The stability of the anti-trastuzumab CT-P6 antibody levels, fluctuating within the range of 5 to 6, highlights the minimal immunogenic potential of trastuzumab CT-P6 and validates its safety profile. The exploratory analyses of soluble HER2 and anti-trastuzumab CT-P6 antibody levels, although not predictive of pCR In this cohort, provide a framework for future translational studies of biosimilars, where such markers may aid in tailoring therapy or monitoring treatment response. Regarding safety, the adverse events profile found in the present study was low and similar in patients treated with Scheme 1 + 3 and with Scheme 2 , although the incidence of AEs and SAEs was a little higher in patients treated with Scheme 2 . There were only 2 participants included in Scheme 3, so that no conclusions can be drawn for this group alone. The combination of trastuzumab CT-P6 and pertuzumab was generally well tolerated, whether or not it was administered sequentially or concomitantly with chemotherapy in any of the three Schemes, which confirms the results obtained in a similar study with trastuzumab and pertuzumab also given sequentially or concomitantly with chemotherapy in three different arms and in the corresponding long-term study [ 9 , 10 ]. Of particular relevance is the absence of cardiotoxicity in the present study. In a previous study with the original trastuzumab [ 22 ], heart failure episodes were not observed; however, a decrease in LVEF was documented in 3 of 70 patients. In the present study, no patient exhibited any heart failure or LVEF alteration in response to any of the NACT Schemes received. This finding serves to reinforce the cardiac safety of trastuzumab CT-P6, even when it is utilized in conjunction with pertuzumab and potentially cardiotoxic chemotherapies. The response prediction analysis results were not significant. Soluble HER2 did not predict pCR, although predictive potential cannot be excluded. Therefore, its usefulness remains to be determined. The analysis of the prediction of responses and the validation of this analysis through machine learning algorithms can be of great assistance when selecting the patients for whom the treatment will be most effective. However, due to the substantial size of the validation study employing machine learning techniques, the results will be incorporated into a subsequent publication. While exploratory and underpowered, the incorporation of machine learning approaches illustrates the feasibility of integrating computational oncology tools into translational biosimilar research, paving the way for precision-based prediction models in HER2-positive breast cancer. A potential limitation of the study is the observational design, which precludes causal inferences. However, it should also be noted that this is a study conducted in RCP, outside the clinical trial setting, and therefore the information provided is from real world evidence (RWE), which is an important strength of the study. RWE is increasingly recognized as a vital complement to clinical trial data, particularly in informing the adoption of biosimilars into standard practice. There have been similar studies before, but this one has two characteristics that make it different. First, it includes a relatively large sample size, with 102 patients, making it one of the largest real-world prospective studies in the neoadjuvant setting, involving dual HER2 blockade with a biosimilar. Second, it is the first time that a biosimilar, trastuzumab CT-P6, is being used in a curative indication in the neoadjuvant setting, which gives the study some additional power at a time when biosimilars are particularly interesting, and establishing a precedent for biosimilar use in early stage breast cancer. Taken together, these findings extend beyond clinical outcomes to provide translational evidence supporting the integration of trastuzumab CT-P6 into curative neoadjuvant strategies, highlighting its safety, non-immunogenicity, and potential for biomarker-driven optimization. Conclusions In conclusion, this prospective observational study has shown that trastuzumab CT-P6 is effective, safe and non-immunogenic, and can be used in neoadjuvant treatment in combination with pertuzumab, with pCR data similar to those obtained with the original trastuzumab and without immunogenicity. Abbreviations AEs Adverse Events cN clinical node stage cT clinical tumor stage EMA European Medicines Agency ER Estrogen Receptor FISH Fluorescence in situ hybridization G1 well differentiated G2 Moderately differentiates G3 Poorly differentiated GI Gastrointestinal GPP Good Pharmacoepidemiology Practices GX Not classified HER2 Human epidermal growth factor receptor HR Horme receptor IHC Immunohistochemistry LVEF Left ventricular ejection fraction NACT Neoadjuvant chemotherapy NOS no other spacifications pCR pathologic complete response PR Progesterone receptor RCP Routine clinical practice RWE Real World Evidence Scheme 2 With anthracyclines Scheme 1 + 3 Without anthracyclines SLNB Sentinel lymph node biopsy ypN Lymph nodes in axilla ypT tumor cells in breast tissue Declarations Ethics approval and consent to participate Written informed consent was obtained from all participants, and the study was approved by the Ethics Committee (2020-3-2-HCUVA) of the Hospital Clínico Universitario Virgen de la Arrixaca, Murcia, Spain. Consent for publication Not applicable Availability of data and materials All anonymized data, along with the scripts used for data analysis, figure generation, and the reproduction of the results presented in this article and its supplementary files, are available on request through the corresponding author and upon approval from the sponsor: Grupo Oncología Clínica y Traslacional – IMIB. Competing interests A. Fernández Aramburu reported speaker bureau fees from Pfizer, Lilly and Novartis. AHR is an employee of Kern Pharma S.L. P. de la Morena Barrio reported honoraria from Astrazeneca, GSK, Lilly, Clovis Oncology, MSD, Roche; travel support from Roche, Lilly, GSK, MSD, Novartis. A. de las Heras-Rubio is an employee of Kern Pharma, S.L. All other authors declare no potential conflicts of interest. Funding This work was supported by Kern Pharma, S.L. under its Program Grants for Research Program. The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and the decision to submit the manuscript for publication. Authors’ Contributions Conceptualization, JLAR and PRC; methodology, JLAR and PRC; validation, JLAR, JPS, JAPM and PRC; formal analysis, JPS and JAPM; investigation, JLAR, JMG, RC, AFA, AFD, PSH, PMB, APB, MDJ, PRC; resources, JLAR and PRC; data curation, JLAR, JPS, JAPM, PRC; writing original draft preparation, JLAR and PRC; writing-review and editing, JLAR, JMG, RC, AFA, AFD, PSH, PMB, APB, MDJ, PRC; supervision, JLAR and PRC; funding acquisition, AHR. All authors have read and agreed to the published version of the manuscript. Acknowledgements We thank the patients and their families for participating in the study, and the study teams who were involved at each participating institution. Medical writing and editorial assistance was provided by Esther Pellicer, MSc, PhD. This assistance was founded by Kern Pharma, S.L. This work was supported by Kern Pharma, S.L. under its Program Grants for Research Program. The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and the decision to submit the manuscript for publication. References Sant M, Allemani C, Capocaccia R, Hakulinen T, Aareleid T, Coebergh JW et al (2003) Stage at diagnosis is a key explanation of differences in breast cancer survival across Europe. Int J Cancer 106:416–422. 10.1002/ijc.11226 Harbeck N, Penault-Llorca F, Cortes J, Gnant M, Houssami N, Poortmans P et al (2019) Breast cancer. Nat Rev Dis Primers 5:66. 10.1038/s41572-019-0111-2 Li X, Zhang X, Yin S, Nie J (2025) Challenges and prospects in HER2-positive breast cancer-targeted therapy. 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A. Fernández Aramburu reported speaker bureau fees from Pfizer, Lilly and Novartis. AHR is an employee of Kern Pharma S.L. P. de la Morena Barrio reported honoraria from Astrazeneca, GSK, Lilly, Clovis Oncology, MSD, Roche; travel support from Roche, Lilly, GSK, MSD, Novartis. A. de las Heras-Rubio is an employee of Kern Pharma, S.L. All other authors declare no potential conflicts of interest. Supplementary Files SupplementaryTableS1.docx Cite Share Download PDF Status: Published Journal Publication published 20 Jan, 2026 Read the published version in Breast Cancer Research and Treatment → Version 1 posted Editorial decision: Revision requested 03 Dec, 2025 Reviews received at journal 30 Nov, 2025 Reviewers agreed at journal 24 Nov, 2025 Reviewers invited by journal 11 Nov, 2025 Editor assigned by journal 03 Nov, 2025 Submission checks completed at journal 03 Nov, 2025 First submitted to journal 03 Nov, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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11:36:48","extension":"html","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":150117,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8020339/v1/ab49cfa82e2e1a77e2596e61.html"},{"id":96554995,"identity":"cff47711-29ce-4144-8eaa-cea89fa704da","added_by":"auto","created_at":"2025-11-23 11:36:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":82777,"visible":true,"origin":"","legend":"\u003cp\u003eEvolution by Treatment Scheme 1+3 and 2. \u003cstrong\u003eA\u003c/strong\u003e for HER2. \u003cstrong\u003eB\u003c/strong\u003e for Trastuzumab CT-P6.\u003c/p\u003e\n\u003cp\u003eScheme 2, with anthracyclines; Scheme 1+3, without anthracyclines.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8020339/v1/564eda609da0801e055b4e6c.png"},{"id":101151770,"identity":"9168e42c-b56f-40e6-895c-2e5ed4429348","added_by":"auto","created_at":"2026-01-26 16:05:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1237381,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8020339/v1/58201b83-9312-4c74-8b0f-a85805b63a36.pdf"},{"id":96604596,"identity":"12197beb-b47d-48f3-be13-619bf5c59f95","added_by":"auto","created_at":"2025-11-24 09:14:18","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":32135,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8020339/v1/ac2ae011acdcfb15349f77ad.docx"}],"financialInterests":"Competing interest reported. A. Fernández Aramburu reported speaker bureau fees from Pfizer, Lilly and Novartis. AHR is an employee of Kern Pharma S.L. P. de la Morena Barrio reported honoraria from Astrazeneca, GSK, Lilly, Clovis Oncology, MSD, Roche; travel support from Roche, Lilly, GSK, MSD, Novartis. A. de las Heras-Rubio is an employee of Kern Pharma, S.L. All other authors declare no potential conflicts of interest.","formattedTitle":"Translational and Real-World Evidence of Trastuzumab Biosimilar CT-P6 Plus Pertuzumab in Neoadjuvant HER2-Positive Early Breast Cancer","fulltext":[{"header":"Background","content":"\u003cp\u003eBreast cancer is the most common malignancy in women in developed countries and the leading cause of cancer death in women. In developed countries most patients with breast cancer are diagnosed at an early stage [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. HER2-positive breast cancer is associated with a poor prognosis and accounts for 13\u0026ndash;15% of breast cancer cases [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eRandomized trials have found no difference in long-term outcomes when chemotherapy is given before or after surgery [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Neoadjuvant chemotherapy (NACT) has traditionally been used to improve the surgical outcome of locally advanced tumors, but it also provides important prognostic information based on response and is associated with higher breast preservation rates [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Achievement of pathologic complete response (pCR) after NACT is associated with increased progression-free survival and overall survival in HER2 positive breast cancer [\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn tumors that overexpress or amplify HER2, NACT with dual anti-HER2 blockade is indicated as standard of care according to the 2017 St. Gallen consensus conference [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Trastuzumab and pertuzumab are recombinant humanized monoclonal antibodies that target different extracellular regions of the HER2 receptor.\u003c/p\u003e\u003cp\u003eIn the different clinical trials to date, neoadjuvant treatment with dual blockade with pertuzumab and trastuzumab against HER2-positive tumors has been shown to provide a high rate of pCR, with acceptable tolerance, with a slight increase in left ventricular ejection fraction (LVEF) reduction, but with rare events of clinical cardiac dysfunction [\u003cspan additionalcitationids=\"CR10 CR11 CR12\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, a standard chemotherapy regimen to accompany dual anti-HER2 blockade is not yet available.\u003c/p\u003e\u003cp\u003eThe emergence of biosimilars in general, and trastuzumab biosimilars in particular, is contributing to the economic sustainability of healthcare systems. Beyond demonstrating clinical efficacy and safety, the integration of biosimilars into curative settings requires robust translational evaluation, including immunogenicity and biomarker analyses, to ensure their reliability in combination regimens.\u003c/p\u003e\u003cp\u003eThe biosimilar CT-P6 (trastuzumab-pkrb, Herzuma\u0026reg;, Celltrion, South Korea) is a trastuzumab biosimilar approved by the European Medicines Agency (EMA) for use in the same indications as the reference biologic [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Preclinical development and clinical studies showed no differences between CT-P6 and the reference product [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eCurrently, the information available on the use of neoadjuvant treatment with pertuzumab and trastuzumab biosimilars is very limited, especially for the trastuzumab biosimilar CT-P6. To date, no prospective study has explored not only the real-world efficacy of trastuzumab CT-P6 in combination with pertuzumab, but also its immunogenicity profile and potential translational biomarkers of response in the neoadjuvant setting.\u003c/p\u003e\u003cp\u003eTherefore, we designed a study to prospectively analyze the use of the trastuzumab CT-P6 in the neoadjuvant setting of HER2-positive early breast cancer in combination with pertuzumab and chemotherapy according to the routine clinical practice (RCP), with the objective of analyzing the efficacy, tolerability, immunogenicity data collected to corroborate the safe use of trastuzumab CT-P6 in the neoadjuvant setting, and to explore clinical and biomarker predictors of pCR with this combination.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design and participants\u003c/h2\u003e\u003cp\u003eThis was a prospective, observational (non-interventional), open-label, multicenter study conducted in 5 Spanish hospitals with experience in breast cancer treatment. All participants had HER2-positive early breast cancer amenable to neoadjuvant treatment with chemotherapy and dual anti-HER2 blockade. The study was registered in Clinicaltrials.gov (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://clinicaltrials.gov/study/NCT06907082\u003c/span\u003e\u003cspan address=\"https://clinicaltrials.gov/study/NCT06907082\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMain inclusion criteria were women aged 18 years or older, with a diagnosis of HER2-positive breast cancer confirmed by immunohistochemistry (IHC) of 3\u0026thinsp;+\u0026thinsp;or positive fluorescence in situ hybridization (FISH) result, and early stage without systemic dissemination amenable to neoadjuvant treatment with chemotherapy and dual anti-HER2 blockade with pertuzumab and trastuzumab CT-P6 according to ESMO guideline 2019 [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Exclusion criteria included metastatic breast cancer, known hypersensitivity to trastuzumab or pertuzumab, current treatment with an investigational agent, diagnosis of any other neoplastic pathology of prognostic relevance within the previous two years except cervical or breast carcinoma in situ and basal cell or squamous cell carcinoma of the skin, non-neoplastic pathology with a life expectancy of less than one year, and pregnancy or lactation.\u003c/p\u003e\u003cp\u003e The study was conducted in full compliance with the principles of the Declaration of Helsinki and the Good Pharmacoepidemiology Practices (GPP), as well as with all Spanish legislation applicable to observational studies (Order SAS/3470/2009). The study was evaluated and approved by the Ethics Committee (2020-3-2-HCUVA) of the Hospital Cl\u0026iacute;nico Universitario Virgen de la Arrixaca, Murcia, Spain. All patients provided written informed consent.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eProcedures and outcomes\u003c/h3\u003e\n\u003cp\u003ePatients were treated in accordance with the preferred hospital protocol, primarily regarding the use or non-use of anthracyclines. Only three treatment schemes were allowed:\u003c/p\u003e\u003cp\u003e1) Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e: Adriamycin 60 mg/m\u003csup\u003e2\u003c/sup\u003e (or epirubicin 90 mg/m\u003csup\u003e2\u003c/sup\u003e)\u0026thinsp;+\u0026thinsp;cyclophosphamide 600 mg/m\u003csup\u003e2\u003c/sup\u003e x 4 cycles, every 15 or 21 days (according to the usual clinical protocol of the service), followed by paclitaxel 80 mg/m\u003csup\u003e2\u003c/sup\u003e weekly x 12 weeks (or docetaxel 100 mg/m\u003csup\u003e2\u003c/sup\u003e every 3 weeks x 4), pertuzumab 840 mg in cycle 1 and 420 mg in cycles 2\u0026ndash;4 (cycles every 21 days)\u0026thinsp;+\u0026thinsp;trastuzumab CT-P6 8 mg/kg in cycle 1 and 6 mg/kg in cycles 2\u0026ndash;4 (cycles every 21 days).\u003c/p\u003e\u003cp\u003e2) Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e: docetaxel 75 mg/m\u003csup\u003e2\u003c/sup\u003e every 3 weeks x 6 cycles\u0026thinsp;+\u0026thinsp;carboplatin 5 or 6 AUC every 3 weeks x 6 cycles\u0026thinsp;+\u0026thinsp;pertuzumab 840 mg in cycle 1 and 420 mg in cycles 2\u0026ndash;6 (cycles every 21 days)\u0026thinsp;+\u0026thinsp;trastuzumab CT-P6 8 mg/kg in cycle 1 and 6 mg/kg in cycles 2\u0026ndash;6 (cycles every 21 days).\u003c/p\u003e\u003cp\u003e3) \u003cb\u003eScheme 3\u003c/b\u003e: paclitaxel 100 mg/m\u003csup\u003e2\u003c/sup\u003e weekly x 8 weeks\u0026thinsp;+\u0026thinsp;pertuzumab 840 mg in cycle 1 and 420 mg in cycles 2\u0026ndash;3 (cycles every 21 days)\u0026thinsp;+\u0026thinsp;trastuzumab CT-P6 8 mg/kg in cycle 1 and 6 mg/kg in cycles 2\u0026ndash;3 (cycles every 21 days) (both administered together with doses 1, 4 and 7 of paclitaxel), followed by epirubicin 90 mg/m\u003csup\u003e2\u003c/sup\u003e every 3 weeks\u0026thinsp;+\u0026thinsp;pertuzumab and trastuzumab CT-P6 IV every 3 weeks, with the same doses x 4 cycles.\u003c/p\u003e\u003cp\u003eThe primary endpoint was the pCR in breast tissue and axilla in patients with HER2-positive early breast cancer after neoadjuvant treatment. pCR was defined as the absence of infiltrating tumor cells in the breast tumor (ypT0/is) and any tumor cells in the axilla (ypN0).\u003c/p\u003e\u003cp\u003eDemographic, clinical, tumor, efficacy and toxicity data were collected. In addition to standard clinical outcomes, a translational substudy was integrated to assess soluble HER2 plasma levels, anti-trastuzumab CT-P6 antibodies, and exploratory prediction models using machine learning techniques. Three blood samples were additionally taken (immunogenicity and Her2 soluble protein): sample 1 (M1) or baseline sample obtained prior to the start of oncological treatment with dual anti-HER2 blockade, sample 2 (M2) obtained in cycle 4 of NACT with dual anti-HER2 blockade, and sample 3 (M3) obtained 10 days prior to surgery or at the post-surgical visit. The translational study added in this project was conducted concurrently with routine blood sampling, requiring no additional venipunctures.\u003c/p\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eA sample size of 96 was planned considering a pCR rate of 52.8%, a precision of 10% in a bilateral analysis, an alpha risk of 0.05, and a power of 0.8 (estimating a 10% loss rate, a total sample size of 106 patients should be recruited).\u003c/p\u003e\u003cp\u003eA descriptive analysis was conducted in which quantitative variables were summarized using measures of central tendency and dispersion, including the mean, standard deviation, median, minimum, and maximum values. Categorical variables were described using absolute frequencies and corresponding percentages. For the purpose of analysis, treatment schemes \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e and 3 were grouped together, resulting in two comparison groups: Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3 and Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e, corresponding to anthracycline-based versus non-anthracycline-based regimens, respectively.\u003c/p\u003e\u003cp\u003eFor the inferential analysis, parametric tests were applied to continuous variables, while nonparametric tests were employed for ordinal, categorical, or non-normally distributed variables. All hypothesis testing was conducted using two-tailed tests with a significance level set at 0.05. For variables that did not meet the assumptions of normality, the Mann\u0026ndash;Whitney U test was used for unpaired data, and the Wilcoxon signed-rank test was applied for paired data. The comparison of categorical variables was performed using the Chi-square test or Fisher\u0026rsquo;s exact test, as appropriate.\u003c/p\u003e\u003cp\u003eThe findings from the response prediction analysis were validated through the application of machine learning algorithms, including decision trees, random forest, and clustering techniques. The analysis was conducted using Python, along with relevant scientific libraries such as NumPy and \u003cem\u003eSciPy\u003c/em\u003e.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003ePatients and treatment\u003c/h2\u003e\u003cp\u003eA total of 106 patients were included in the study. Four patients were excluded from the study (three withdrew their consent, and one received a different subcutaneous trastuzumab than the study treatment). Therefore, the final number of evaluable patients was 102.\u003c/p\u003e\u003cp\u003ePatient characteristics at baseline are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Since only 2 patients from a single hospital were included in Scheme 3, and as it was a scheme with anthracyclines and taxanes that was highly similar to Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e, it was decided to merge Schemes \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e and 3 for analysis. However, the data were also analyzed independently and can be found in Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. The median age of the patients was 52 years, ranging from 30 to 78 years old. Of the 102 patients receiving NACT, 55 (53.92%) received Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e, and 47 (46.08%) received Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePatient demographics at baseline.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAll patients\u003c/p\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;102\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNACT\u003c/p\u003e\u003cp\u003eScheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;55\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNACT\u003c/p\u003e\u003cp\u003eScheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3\u003c/p\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;47\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years), median (range)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e52.00 (30\u0026ndash;78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e56.00 (36\u0026ndash;74)*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e45.00 (30\u0026ndash;78)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0 to \u0026lt;\u0026thinsp;40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20 (19.61%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6 (10.91%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14 (29.79%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e40 to \u0026lt;\u0026thinsp;65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e64 (62.74%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e37 (67.27%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27 (57.45%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge; 65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18 (17.65%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12 (21.82%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (12.76%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMenopausal state\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePre-menopause\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46 (45.10%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17 (30.91%)*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e29 (61.70%)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePost-menopause\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e56 (54.90%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e38 (69.09%)*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18 (38.30%)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eER\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePositive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e58 (56.86%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e33 (60.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25 (53.19%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNegative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e44 (43.14%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e22 (40.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22 (46.81%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePositive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e37 (36.27%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23 (41.82%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14 (29.79%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNegative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e65 (63.73%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e32 (58.18%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33 (70.21%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eER and/or PR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePositive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e59 (57.84%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e33 (60.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26 (55.32%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNegative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e43 (42.16%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e22 (40.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21 (44.68%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKi67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKi67\u0026thinsp;\u0026lt;\u0026thinsp;20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20 (19.61%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11 (20.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (19.15%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKi67\u0026thinsp;\u0026ge;\u0026thinsp;20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e82 (80.39%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e44 (80.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e38 (80.85%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHER2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2+ (FISH amplified)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20 (19.61%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11 (20.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (19.15%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e82 (80.39%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e44 (80.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e38 (80.85%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTumor distribution\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnique\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e68 (66.66%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e36 (65.44%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32 (68.08%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMultifocal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19 (18. 63%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9 (16.36%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (21.28%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMulticentric\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14 (13.73%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9 (16.36%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (10.64%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnknown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (00.98%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1 (01.82%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of focus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e67 (66.34%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e37 (7.26%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30 (65.21%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15 (14.85%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7 (12.73%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (17.39%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 (5.94%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2 (3.64%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (8.70%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8 (7.84%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7 (12.73%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (2.17%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnknown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (4.95%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2 (3.64%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (6.52%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSize of biggest tumor (mm), median (range)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30.50 (10\u0026ndash;110)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e35.00 (11\u0026ndash;90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30.00 (10\u0026ndash;110)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0 to \u0026lt;\u0026thinsp;20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14 (13.72%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5 (9.09%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (19.15%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20 to \u0026lt;\u0026thinsp;50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e71 (69.61%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e39 (70.91%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32 (68.08%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge; 50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17 (16.67%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11 (20.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (12.77%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHistologic grade\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eG1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9 (8.82%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3 (5.45%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (12.77%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eG2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e44 (43.14%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e21 (38.18%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23 (48.94%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eG3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35 (34.31%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e29 (52.73%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (12.77%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14 (13.73%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2 (3.64%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 (25.53%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHistological subtype\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDuctal NOS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e94 (92.16%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e53 (96.36%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41 (87.23%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther subtypes\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8 (7.84%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2 (3.64%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (12.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50 (49.02%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e22 (40.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28 (59.57%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26 (25.49%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16 (29.09%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (21.28%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16 (15.69%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10 (18.18%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (12.77%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (6.86%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6 (10.91%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (2.13%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (2.94%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1 (1.82%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (4.25%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13 (12.74%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7 (12.73%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (12.76%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e66 (64.71%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e35 (63.63%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31 (65.96%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19 (18.63%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10 (18.18%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (19.15%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (1.96%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1 (1.82%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (2.13%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (1.96%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2 (3.64%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTime to surgery (days), median (range)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e68.50 (28\u0026ndash;147)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e56.00 (28\u0026ndash;140)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e84.00 (47\u0026ndash;147)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eType of surgery\u003csup\u003eb\u003c/sup\u003e - breast\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConservative surgery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e63 (62.38%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e34 (61.82%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e29 (63.04%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMastectomy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e38 (37.62%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e21 (38.18%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17 (36.96%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eType of surgery\u003csup\u003eb\u003c/sup\u003e \u0026ndash; axilla\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSLNB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e62 (62.63%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26 (49.06%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36 (78.26%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLymphadenectomy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e37 (37.37%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e27 (50.94%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (21.74%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of cycles of CT-P6\u0026thinsp;+\u0026thinsp;pertuzumab, median (range)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e--\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6.0 (4\u0026ndash;6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.0 (3\u0026ndash;4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eData are number (%) unless otherwise specified. \u003csup\u003ea\u003c/sup\u003e Other histological subtypes include medullar, lobular, apocrine, and invasive carcinoma with micropapillary ductal and papillary type areas. \u003csup\u003eb\u003c/sup\u003e Of the 102 patients, 1 was not operated due to COVID-19; therefore, 101 patients underwent breast surgery and 99 underwent axillary surgery. * Indicates statistically significant difference between Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003ecN, clinical node stage; cT, clinical tumor stage; ER, estrogen receptor; FISH, fluorescence \u003cem\u003ein situ\u003c/em\u003e hybridization; G1, well differentiated; G2, moderately differentiated; G3, poorly differentiated; GX, not classified; HER2, human epidermal growth factor receptor 2; NACT, neoadjuvant chemotherapy; NOS, no other specifications; PR, progesterone receptor; Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e, with anthracyclines; Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3, without anthracyclines; SLNB, sentinel lymph node biopsy.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe comparison of the study population by Scheme found a significant difference in age (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001044), and in the menopausal state (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002655). Patients in Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3 were younger, and there were more pre-menopausal patients (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eEfficacy\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows pCR results obtained after NACT with dual anti-HER2 blockade. Of the 102 patients included in the study, 101 underwent surgery. One patient, despite completing all other study procedures, was not operated on due to a COVID-19 infection and was therefore excluded from the pathologic complete response evaluation.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePathologic complete response (pCR) after surgery.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAll patients\u003c/p\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;101\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNACT\u003c/p\u003e\u003cp\u003eScheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;55\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNACT\u003c/p\u003e\u003cp\u003eScheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3\u003c/p\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;46\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003epCR - Global\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBreast\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e61 (60.40%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e29 (52.73%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e32 (69.57%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAxilla\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e81 (80.20%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e41 (74.55%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40 (86.96%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBreast \u0026amp; axilla\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e58 (57.43%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e29 (52.73%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e29 (63.04%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003epCR - HR negative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBreast\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e35 (83.33%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17 (77.27%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18 (90.00%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAxilla\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e37 (88.10%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19 (86.36%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18 (90.00%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBreast \u0026amp; axilla\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e33 (78.57%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17 (77.27%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e16 (80.00%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003epCR - HR positive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBreast\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e26 (44.83%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12 (37.50%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14 (53.85%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAxilla\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e44 (75.86%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e22 (68.75%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22 (84.62%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBreast \u0026amp; axilla\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e25 (43.10%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12 (37.50%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e13 (50.00%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eypT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eypT0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e55 (54.46%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26 (47.27%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e29 (63.05%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eypT1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e32 (31.68%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19 (34.55%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e13 (28.26%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eypT2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8 (7.92%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7 (12.73%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1 (2.17%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eypTis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6 (5.94%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3 (5.45%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3 (6.52%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eypN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e81 (80.20%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e41 (74.55%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40 (86.96%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e16 (15.84%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10 (18.18%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6 (13.04%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2 (1.98%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2 (3.64%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2 (1.98%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2 (3.64%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eData are number (%) unless otherwise specified.\u003csup\u003ea\u003c/sup\u003e Of the 102 patients, 1 was not operated due to COVID-19, and therefore was not included in the pathologic complete response evaluation after surgery.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eHR, hormonal receptor; NACT, neoadjuvant chemotherapy; pCR, pathologic complete response; ypN, lymph nodes in axilla; Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e, with anthracyclines; Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3, without anthracyclines; ypT, tumor cells in breast tissue.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003epCR was achieved globally by 60.40% (61/101) of patients in breast and 80.20% (81/101) of patients in axilla. The percentage of patients achieving pCR both in breast and axilla (ypT0\u0026thinsp;+\u0026thinsp;ypTis and ypN0) was 57.43% (58/101) globally, 52.73% (29/55) with Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e, and 63.04% (29/46) with Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3.\u003c/p\u003e\u003cp\u003eThe comparative analysis of Schemes \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3 revealed no significant differences in pCR, regardless of whether the results were examined in the breast (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.149643), in the axilla (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.204635), or in both the breast and axilla (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.417684).\u003c/p\u003e\u003cp\u003eThere was a significant negative association for the size of the biggest tumor in Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3 in breast (correlation \u0026minus;\u0026thinsp;0.300048, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0053533) and in breast\u0026thinsp;+\u0026thinsp;axilla (correlation \u0026minus;\u0026thinsp;0.350816, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.022734); and a significant positive association also for the size of the biggest tumor in Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e, in breast and in breast\u0026thinsp;+\u0026thinsp;axilla (in both cases, correlation \u0026minus;\u0026thinsp;0.449599, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01638).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eTranslational analysis\u003c/h3\u003e\n\u003cp\u003eTranslational endpoints included soluble HER2 and anti-trastuzumab CT-P6 antibody plasma levels, as well as exploratory prediction analyses validated with machine learning algorithms (due to the substantial size of the validation study employing machine learning techniques, the results will be incorporated into a subsequent publication).\u003c/p\u003e\u003cp\u003eNo anti-trastuzumab CT-P6 antibodies were detected at any timepoint. Soluble HER2 plasma levels did not show significant correlation with pCR.\u003c/p\u003e\u003cp\u003eBiomarkers were obtained in 97.06% (99/102) of patients at M1, 94.12% (96/102) of patients at M2, and 85% (90/102) of patients at M3. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the plasma concentrations of soluble HER2 and anti-trastuzumab CT-P6 antibodies are reported globally and by Scheme. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the evolution of the mean plasma levels of HER2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA) and Trastuzumab CT-P6 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB) by treatment Scheme. Soluble HER2 plasma concentration slightly increased in Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e, while decreased in Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3, but there were no significant differences between both Schemes. Also, anti-trastuzumab CT-P6 antibody plasma levels slightly increased in Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e and decreased in Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3, and no significant differences were found between both Schemes.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSoluble HER2 and anti-Trastuzumab CT-P6 antibodies plasma concentration.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAll patients\u003c/p\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;102\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNACT Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;55\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNACT Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3\u003c/p\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;47\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHER2 (ng/ml), median (range)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eM1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.06 (0.00-0.81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.05 (0.00-0.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.09 (0.00-0.81)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0.0 to \u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (7,14%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (7.69%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (6.98%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0.01 to \u0026lt;\u0026thinsp;1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e65 (92.86%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24 (92.31%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e40 (93.02%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eM2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.05 (0.00-0.27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.04 (0.00-0.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.06 (0.00-0.27)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0.0 to \u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (9.86%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (10.71%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (9.30%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0.01 to \u0026lt;\u0026thinsp;1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e64 (90.14%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25 (89.29%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39 (90.70%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eM3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.06 (0.00-0.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.05 (0.00-0.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.06 (0.00-0.36)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0.0 to \u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 (8.45%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (3.57%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (11.63%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0.01 to \u0026lt;\u0026thinsp;1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e65 (91.55%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27 (96.43%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e38 (88.37%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrastuzumab CT-P6 (ng/ml), median (range)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eM1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.38 (0.00-26.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.38 (0.00-8.52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.00 (2.22\u0026ndash;26.92)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0.0 to \u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.43%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (3.85%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0.01 to \u0026lt;\u0026thinsp;30.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e69 (98.57%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25 (96.15%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e43 (100.00%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eM2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.38 (0.00\u0026ndash;20.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.10 (0.00\u0026ndash;20.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.42 (2.59\u0026ndash;17.31)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0.0 to \u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.41%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (3.57%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0.01 to \u0026lt;\u0026thinsp;30.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70 (98.59%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27 (96.43%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e43 (100.00%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eM3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.00 (0.00\u0026ndash;15.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.80 (2.59-15.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.62 (0.00-11.85)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0.0 to \u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (1.41%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (2.33%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0.01 to \u0026lt;\u0026thinsp;30.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70 (98.59%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28 (100.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42 (97.67%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eData are number (%) unless otherwise specified.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eHER2, human epidermal growth factor receptor 2; M1, measurement corresponding to the baseline sample obtained prior to the start of oncological treatment with dual anti-HER2 blockade; M2, measurement corresponding to the sample obtained in cycle 4 of NACT with dual anti-HER2 blockade; M3, measurement corresponding to the sample obtained 10 days prior to surgery or at the post-surgical visit; NACT, neoadjuvant chemotherapy; Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e, with anthracyclines; Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3, without anthracyclines.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eNo significant correlations were found between pCR and soluble HER2 (phi\u0026thinsp;=\u0026thinsp;0.334052), or with anti-trastuzumab CT-P6 antibodies (phi\u0026thinsp;=\u0026thinsp;0.331133).\u003c/p\u003e\n\u003ch3\u003eSafety\u003c/h3\u003e\n\u003cp\u003eGlobally, the most relevant treatment-related adverse events (AEs) in Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e were diarrhea (21.75%), mucositis (19.00%), nausea (17.88%), and asthenia (17.62%), while in Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3 were asthenia (7.25%) and mucositis (5.25%) (see Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMore relevant treatment-related adverse events per cycle.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eNACT Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;55\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e\u003cp\u003eNACT Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3\u003c/p\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;47\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGlobal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGrade 1\u0026amp;2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGrade 3\u0026amp;4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRequired admission\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGlobal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eGrade 1\u0026amp;2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eGrade 3\u0026amp;4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eRequired admission\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiarrhea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21.75%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19.38%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.25%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.88%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.00%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.00%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.00%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.00%*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMucositis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19.00%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18.62%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.25%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.25%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNausea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17.88%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.12%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.62%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.25%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.88%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.88%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAsthenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17.62%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.38%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.12%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.25%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.25%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e6.75%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.50%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGI toxicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.88%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.62%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.12%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.25%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.62%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.38%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.75%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.00%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.62%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.50%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.50%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeuropathic toxicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.58%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.75%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.12%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.12%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeutropenia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.00%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.50%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.50%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.12%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.25%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.38%*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.88%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeutropenic fever\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.25%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.38%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.25%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.12%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.12%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLVEF alteration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.00%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003eData are in percentage per cycle. * Indicates statistically significant difference between Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003eGI, gastrointestinal; LVEF, left ventricular ejection fraction; NACT, neoadjuvant chemotherapy; Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e, with anthracyclines; Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3, without anthracyclines.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe most relevant Grade 3\u0026amp;4 treatment-related AEs were diarrhea (2.25%) in Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e and asthenia (0.50%) in Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3. The most relevant treatment-related AEs requiring hospital admission were diarrhea (0.88%) in Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e and neutropenic fever (0.12%) in Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3.\u003c/p\u003e\u003cp\u003eThe percentage of patients requiring a dose reduction was 32.73% in Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e, and 22.45% in Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3. The mean percentage of cycles with dose reduction was 40.09% for Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e, and 30.13% for Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3.\u003c/p\u003e\u003cp\u003eThere were no deaths or AEs leading to death.\u003c/p\u003e\u003cp\u003eThe comparison of treatment-related AEs rates between Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3 revealed that Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e had a significantly higher proportion of AEs. Significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were observed between the two schemes in nearly all parameters overall and for Grades 1\u0026amp;2, while for Grades 3\u0026amp;4, significance was found only for diarrhea.\u003c/p\u003e\u003cp\u003eRegarding cardiac safety, no significant issues were identified, and LVEF remained unaffected.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe primary objective of this study was to evaluate the efficacy, safety and immunogenicity of the trastuzumab CT-P6 in combination with pertuzumab and chemotherapy as neoadjuvant treatment in patients with HER2-positive early breast cancer in RCP according to pCR in breast and axilla. The results confirm that this regimen is effective, with 57% of all patients achieving full pCR both in breast and axilla, increasing to 63% of patients when receiving Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3. Notably, when evaluated separately, while 60% of all patients achieved pCR in breast, a higher percentage of patients (80%) achieved pCR in axilla, consistent with known patterns of differential tumor response [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDespite the absence of a direct comparison with the original trastuzumab in this study, the results align with those of other published works using the original trastuzumab. The pCR results are similar although slightly lower than those found in the studies by Bernat-Peguera and Bae [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. These studies compared the pCR rate in HER2-positive early breast cancer patients treated with either trastuzumab CT-P6 or reference trastuzumab, and found that patients treated with CT-P6 achieved pCR rates of 65% and 74.4%, respectively.\u003c/p\u003e\u003cp\u003eThis study is, to our knowledge, the first to prospectively evaluate immunogenicity and biomarker dynamics of a trastuzumab biosimilar in combination with pertuzumab in the neoadjuvant setting.\u003c/p\u003e\u003cp\u003eIt is important to highlight the absence of immunogenicity measured in the context of this trastuzumab biosimilar. This study is the first to evaluate trastuzumab CT-P6 immunogenicity when combined with pertuzumab in a neoadjuvant setting. No anti-trastuzumab CT-P6 antibodies were detected in any patient during treatment, which corroborates the findings of previous studies that reported low immunogenic potential for trastuzumab CT-P6 [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. These findings reinforce the safety and reliability of this biosimilar, even when co-administered with another monoclonal antibody. The absence of anti-trastuzumab CT-P6 antibodies, even in the context of dual monoclonal antibody blockade, provides important translational reassurance of biosimilar safety at the immune interface.\u003c/p\u003e\u003cp\u003eDespite the disparities in age and menopausal status identified by Scheme, while Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3 exhibited a preponderance of younger patients and a higher proportion of premenopausal subjects, these observations had no impact on the outcomes concerning efficacy, as no significant differences in pCR were observed between the two Schemes.\u003c/p\u003e\u003cp\u003eThe results of the correlation analysis indicated a positive correlation between the extent of the tumor and the degree of response, with smaller tumors exhibiting higher levels of pCR. These findings are clinically reasonable and consistent with the observed responses.\u003c/p\u003e\u003cp\u003eThe comparison of Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3 with respect to soluble HER2 plasma concentrations and anti-trastuzumab CT-P6 antibody plasma levels revealed no significant differences. The slight increase in anti-trastuzumab CT-P6 antibody plasma levels observed in Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e could be attributed to the number of trastuzumab CT-P6\u0026thinsp;+\u0026thinsp;pertuzumab cycles administered to patients in this Scheme (median of 6 cycles), compared to Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3 (median of 4 cycles). The stability of the anti-trastuzumab CT-P6 antibody levels, fluctuating within the range of 5 to 6, highlights the minimal immunogenic potential of trastuzumab CT-P6 and validates its safety profile.\u003c/p\u003e\u003cp\u003eThe exploratory analyses of soluble HER2 and anti-trastuzumab CT-P6 antibody levels, although not predictive of pCR In this cohort, provide a framework for future translational studies of biosimilars, where such markers may aid in tailoring therapy or monitoring treatment response.\u003c/p\u003e\u003cp\u003eRegarding safety, the adverse events profile found in the present study was low and similar in patients treated with Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026thinsp;+\u0026thinsp;3 and with Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e, although the incidence of AEs and SAEs was a little higher in patients treated with Scheme \u003cspan refid=\"Sch3\" class=\"InternalRef\"\u003e2\u003c/span\u003e. There were only 2 participants included in Scheme 3, so that no conclusions can be drawn for this group alone. The combination of trastuzumab CT-P6 and pertuzumab was generally well tolerated, whether or not it was administered sequentially or concomitantly with chemotherapy in any of the three Schemes, which confirms the results obtained in a similar study with trastuzumab and pertuzumab also given sequentially or concomitantly with chemotherapy in three different arms and in the corresponding long-term study [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOf particular relevance is the absence of cardiotoxicity in the present study. In a previous study with the original trastuzumab [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], heart failure episodes were not observed; however, a decrease in LVEF was documented in 3 of 70 patients. In the present study, no patient exhibited any heart failure or LVEF alteration in response to any of the NACT Schemes received. This finding serves to reinforce the cardiac safety of trastuzumab CT-P6, even when it is utilized in conjunction with pertuzumab and potentially cardiotoxic chemotherapies.\u003c/p\u003e\u003cp\u003eThe response prediction analysis results were not significant. Soluble HER2 did not predict pCR, although predictive potential cannot be excluded. Therefore, its usefulness remains to be determined. The analysis of the prediction of responses and the validation of this analysis through machine learning algorithms can be of great assistance when selecting the patients for whom the treatment will be most effective. However, due to the substantial size of the validation study employing machine learning techniques, the results will be incorporated into a subsequent publication. While exploratory and underpowered, the incorporation of machine learning approaches illustrates the feasibility of integrating computational oncology tools into translational biosimilar research, paving the way for precision-based prediction models in HER2-positive breast cancer.\u003c/p\u003e\u003cp\u003eA potential limitation of the study is the observational design, which precludes causal inferences. However, it should also be noted that this is a study conducted in RCP, outside the clinical trial setting, and therefore the information provided is from real world evidence (RWE), which is an important strength of the study. RWE is increasingly recognized as a vital complement to clinical trial data, particularly in informing the adoption of biosimilars into standard practice.\u003c/p\u003e\u003cp\u003eThere have been similar studies before, but this one has two characteristics that make it different. First, it includes a relatively large sample size, with 102 patients, making it one of the largest real-world prospective studies in the neoadjuvant setting, involving dual HER2 blockade with a biosimilar. Second, it is the first time that a biosimilar, trastuzumab CT-P6, is being used in a curative indication in the neoadjuvant setting, which gives the study some additional power at a time when biosimilars are particularly interesting, and establishing a precedent for biosimilar use in early stage breast cancer.\u003c/p\u003e\u003cp\u003eTaken together, these findings extend beyond clinical outcomes to provide translational evidence supporting the integration of trastuzumab CT-P6 into curative neoadjuvant strategies, highlighting its safety, non-immunogenicity, and potential for biomarker-driven optimization.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, this prospective observational study has shown that trastuzumab CT-P6 is effective, safe and non-immunogenic, and can be used in neoadjuvant treatment in combination with pertuzumab, with pCR data similar to those obtained with the original trastuzumab and without immunogenicity.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAEs\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Adverse Events\u003c/p\u003e\n\u003cp\u003ecN\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;clinical node stage\u003c/p\u003e\n\u003cp\u003ecT\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;clinical tumor stage\u003c/p\u003e\n\u003cp\u003eEMA\u0026nbsp; \u0026nbsp; \u0026nbsp;European Medicines Agency\u003c/p\u003e\n\u003cp\u003eER\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Estrogen Receptor\u003c/p\u003e\n\u003cp\u003eFISH\u0026nbsp; \u0026nbsp; \u0026nbsp;Fluorescence in situ hybridization\u003c/p\u003e\n\u003cp\u003eG1\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;well differentiated\u003c/p\u003e\n\u003cp\u003eG2\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Moderately differentiates\u003c/p\u003e\n\u003cp\u003eG3\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Poorly differentiated\u003c/p\u003e\n\u003cp\u003eGI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Gastrointestinal\u003c/p\u003e\n\u003cp\u003eGPP\u0026nbsp; \u0026nbsp; \u0026nbsp;Good Pharmacoepidemiology Practices\u003c/p\u003e\n\u003cp\u003eGX\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Not classified\u003c/p\u003e\n\u003cp\u003eHER2\u0026nbsp; \u0026nbsp;Human epidermal growth factor receptor\u003c/p\u003e\n\u003cp\u003eHR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Horme receptor\u003c/p\u003e\n\u003cp\u003eIHC\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Immunohistochemistry\u003c/p\u003e\n\u003cp\u003eLVEF\u0026nbsp; \u0026nbsp;\u0026nbsp;Left ventricular ejection fraction\u003c/p\u003e\n\u003cp\u003eNACT\u0026nbsp; \u0026nbsp;Neoadjuvant chemotherapy\u003c/p\u003e\n\u003cp\u003eNOS\u0026nbsp; \u0026nbsp; \u0026nbsp;no other spacifications\u003c/p\u003e\n\u003cp\u003epCR\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;pathologic complete response\u003c/p\u003e\n\u003cp\u003ePR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Progesterone receptor\u003c/p\u003e\n\u003cp\u003eRCP\u0026nbsp; \u0026nbsp; \u0026nbsp;Routine clinical practice\u003c/p\u003e\n\u003cp\u003eRWE\u0026nbsp; \u0026nbsp;\u0026nbsp;Real World Evidence\u003c/p\u003e\n\u003cp\u003eScheme 2\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;With anthracyclines\u003c/p\u003e\n\u003cp\u003eScheme 1 + 3\u0026nbsp; \u0026nbsp;Without anthracyclines\u003c/p\u003e\n\u003cp\u003eSLNB\u0026nbsp; \u0026nbsp;\u0026nbsp;Sentinel lymph node biopsy\u003c/p\u003e\n\u003cp\u003eypN\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Lymph nodes in axilla\u003c/p\u003e\n\u003cp\u003eypT \u0026nbsp; \u0026nbsp; \u0026nbsp; tumor cells in breast tissue\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWritten informed consent was obtained from all participants, and the study was approved by the Ethics Committee (2020-3-2-HCUVA) of the Hospital Clínico Universitario Virgen de la Arrixaca, Murcia, Spain.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll anonymized data, along with the scripts used for data analysis, figure generation, and the reproduction of the results presented in this article and its supplementary files, are available on request through the corresponding author and upon approval from the sponsor: Grupo Oncología Clínica y Traslacional – IMIB.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Fernández Aramburu reported speaker bureau fees from Pfizer, Lilly and Novartis. AHR is an employee of Kern Pharma S.L. P. de la Morena Barrio reported honoraria from Astrazeneca, GSK, Lilly, Clovis Oncology, MSD, Roche; travel support from Roche, Lilly, GSK, MSD, Novartis. A. de las Heras-Rubio is an employee of Kern Pharma, S.L. All other authors declare no potential conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Kern Pharma, S.L. under its Program Grants for Research Program. The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and the decision to submit the manuscript for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, JLAR and PRC; methodology, JLAR and PRC; validation, JLAR, JPS, JAPM and PRC; formal analysis, JPS and JAPM; investigation, JLAR, JMG, RC, AFA, AFD, PSH, PMB, APB, MDJ, PRC; resources, JLAR and PRC; data curation, JLAR, JPS, JAPM, PRC; writing original draft preparation, JLAR and PRC; writing-review and editing, JLAR, JMG, RC, AFA, AFD, PSH, PMB, APB, MDJ, PRC; supervision, JLAR and PRC; funding acquisition, AHR. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the patients and their families for participating in the study, and the study teams who were involved at each participating institution. Medical writing and editorial assistance was provided by Esther Pellicer, MSc, PhD. This assistance was founded by Kern Pharma, S.L. This work was supported by Kern Pharma, S.L. under its Program Grants for Research Program. The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and the decision to submit the manuscript for publication.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSant M, Allemani C, Capocaccia R, Hakulinen T, Aareleid T, Coebergh JW et al (2003) Stage at diagnosis is a key explanation of differences in breast cancer survival across Europe. Int J Cancer 106:416\u0026ndash;422. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/ijc.11226\u003c/span\u003e\u003cspan address=\"10.1002/ijc.11226\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHarbeck N, Penault-Llorca F, Cortes J, Gnant M, Houssami N, Poortmans P et al (2019) Breast cancer. 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Int J Cancer 149:1585\u0026ndash;1592. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/ijc.33726\u003c/span\u003e\u003cspan address=\"10.1002/ijc.33726\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBernat-Peguera A, Trigueros M, Ferrando-D\u0026iacute;ez A, Ib\u0026aacute;\u0026ntilde;ez C, Bystrup S, Mart\u0026iacute;nez-Card\u0026uacute;s A et al (2022) Efficacy of CT-P6 (trastuzumab biosimilar) versus reference trastuzumab in combination with pertuzumab in HER2-positive early-stage breast cancer: Preclinical and real-life clinical data. 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Front Oncol 11:689587. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fonc.2021.689587\u003c/span\u003e\u003cspan address=\"10.3389/fonc.2021.689587\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStebbing J, Baranau Y, Baryash V, Manikhas A, Moisenyeko V, Dzagnidze G et al (2017) CT-P6 compared with reference trastuzumab for HER2-positive breast cancer: a randomised, double-blind, active-controlled, phase 3 equivalence trial. Lancet Oncol 18:917\u0026ndash;928. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S1470-2045(17)30434-5\u003c/span\u003e\u003cspan address=\"10.1016/S1470-2045(17)30434-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStebbing J, Baranau YV, Baryash V, Manikhas A, Moiseyenko V, Dzagnidze G et al (2021) Long-term efficacy and safety of CT-P6 versus trastuzumab in patients with HER2-positive early breast cancer: final results from a randomized phase III trial. Breast Cancer Res Treat 188:631\u0026ndash;640. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10549-021-06240-5\u003c/span\u003e\u003cspan address=\"10.1007/s10549-021-06240-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTiwari SR, Mishra P, Raska P, Calhoun B, Abraham J, Moore H et al (2016) Retrospective study of the efficacy and safety of neoadjuvant docetaxel, carboplatin, trastuzumab/pertuzumab (TCH-P) in nonmetastatic HER2-positive breast cancer. Breast Cancer Res Treat 158:189\u0026ndash;193. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10549-016-3866-0\u003c/span\u003e\u003cspan address=\"10.1007/s10549-016-3866-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"breast-cancer-research-and-treatment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"brea","sideBox":"Learn more about [Breast Cancer Research and Treatment](https://www.springer.com/journal/10549)","snPcode":"10549","submissionUrl":"https://submission.nature.com/new-submission/10549/3","title":"Breast Cancer Research and Treatment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"HER2-positive early breast cancer, neoadjuvant treatment, routine clinical practice, trastuzumab biosimilar, trastuzumab CT-P6","lastPublishedDoi":"10.21203/rs.3.rs-8020339/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8020339/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eData on neoadjuvant treatment with trastuzumab biosimilars, particularly CT-P6, in combination with pertuzumab, are limited. This study evaluates the efficacy, tolerability, and immunogenicity of CT-P6 plus pertuzumab and chemotherapy, according to routine clinical practice, in the neoadjuvant setting for HER2-positive early breast cancer, while integrating translational biomarker analyses and exploratory predictors of pathologic complete response (pCR).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eProspective, multicenter, observational study in 102 patients with HER2-positive early breast cancer. Patients received hospital-preferred neoadjuvant regimens protocol, with (scheme 1 and 3) or without anthracyclines (scheme 2). The primary endpoint was pCR in breast tissue and axilla. Translational endpoints included soluble HER2, anti-trastuzumab CT-P6 antibodies, and exploratory response prediction models validated using machine learning approaches.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eOverall, pCR was achieved in 60.40% of patients in the breast and 80.20% in the axilla, with no significant differences between anthracycline-based and non-anthracycline-based regimens. Soluble HER2 and anti-trastuzumab CT-P6 antibodies were not significantly associated with pCR. Treatment was well tolerated; the most relevant Grade 3\u0026ndash;4 treatment-related adverse events were diarrhea (2.25%) and asthenia (0.50%). No immunogenicity or clinically relevant cardiotoxicity was observed.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eTrastuzumab CT-P6 combined with pertuzumab and chemotherapy can be used in neoadjuvant treatment for HER2-positive early breast cancer, showing pCR rates comparable to the reference trastuzumab and without evidence of immunogenicity. Exploratory analyses of soluble HER2 and anti-trastuzumab CT-P6 antibodies did not show predictive value for pCR, although this possibility cannot be excluded. Their systematic assessment nevertheless contributes to the translational understanding of biosimilar integration into curative regimens.\u003c/p\u003e\u003ch2\u003eTrial registration:\u003c/h2\u003e\u003cp\u003eThe study has been registered in Clinicaltrials.gov (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://clinicaltrials.gov/study/NCT06907082\u003c/span\u003e\u003cspan address=\"https://clinicaltrials.gov/study/NCT06907082\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e","manuscriptTitle":"Translational and Real-World Evidence of Trastuzumab Biosimilar CT-P6 Plus Pertuzumab in Neoadjuvant HER2-Positive Early Breast Cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-23 11:36:43","doi":"10.21203/rs.3.rs-8020339/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-04T02:16:55+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-01T01:58:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"338179530347847926115948253480998657484","date":"2025-11-24T21:18:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-11T21:11:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-04T01:47:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-04T01:47:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Breast Cancer Research and Treatment","date":"2025-11-03T14:30:19+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"breast-cancer-research-and-treatment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"brea","sideBox":"Learn more about [Breast Cancer Research and Treatment](https://www.springer.com/journal/10549)","snPcode":"10549","submissionUrl":"https://submission.nature.com/new-submission/10549/3","title":"Breast Cancer Research and Treatment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"45e40858-8f85-4159-916d-689a6d54803a","owner":[],"postedDate":"November 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-26T16:01:21+00:00","versionOfRecord":{"articleIdentity":"rs-8020339","link":"https://doi.org/10.1007/s10549-026-07895-8","journal":{"identity":"breast-cancer-research-and-treatment","isVorOnly":false,"title":"Breast Cancer Research and Treatment"},"publishedOn":"2026-01-20 15:58:19","publishedOnDateReadable":"January 20th, 2026"},"versionCreatedAt":"2025-11-23 11:36:43","video":"","vorDoi":"10.1007/s10549-026-07895-8","vorDoiUrl":"https://doi.org/10.1007/s10549-026-07895-8","workflowStages":[]},"version":"v1","identity":"rs-8020339","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8020339","identity":"rs-8020339","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}