Comparison of Anthracycline-Containing and Anthracycline-Free Neoadjuvant Regimens in HER2-Positive Breast Cancer

Comparison of Anthracycline-Containing and Anthracycline-Free Neoadjuvant Regimens in HER2-Positive 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 Comparison of Anthracycline-Containing and Anthracycline-Free Neoadjuvant Regimens in HER2-Positive Breast Cancer Mahmut Kara, Senar Ebinç, Tuba Baydaş, Hatice Ayyıldız Sevim, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8673435/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background Concurrent administration of anti-HER2 therapies and chemotherapy has significantly improved response rates (43%–55%). However, the potential for cardiotoxicity when combining anti-HER2 agents with anthracyclines remains a concern. Consequently, anthracycline-free regimens are increasingly utilized, particularly for patients with cardiac history. This study aims to compare the efficacy and safety of anthracycline-containing chemotherapy versus anthracycline-free TCHP (Docetaxel, Carboplatin, Trastuzumab, and Pertuzumab) regimens in the neoadjuvant treatment of HER2-positive early-stage breast cancer. Methods This multicenter retrospective study analyzed patients diagnosed with HER2-positive breast cancer between 2015 and 2025 who received neoadjuvant anti-HER2 therapy followed by surgery. We evaluated the association between treatment regimens and outcomes, specifically pathological complete response (pCR)—defined as the absence of residual invasive tumor in the breast and axillary nodes—and event-free survival (EFS). Results A total of 358 patients were included, with a mean age of 50 years. Most presented with T2 tumors (74%) and N1 disease (60.9%). The most common regimens were Adriamycin, Cyclophosphamide, Docetaxel, Pertuzumab, Trastuzumab (AC + DPT) (35.2%) and TCHP (30.7%), with a 95.5% treatment completion rate. Pathological complete response rates were statistically comparable between the AC + DPT and TCHP regimens (p = 0.360). Conversely, significantly lower pCR rates were observed with other regimens (OR 0.35, 95% CI 0.17–0.73; p = 0.005). Advanced lymph node involvement (N3) was strongly associated with worse event-free survival (HR 8.43, p = 0.038), while ER and PR status showed no significant impact. Regarding safety, febrile neutropenia was more frequent in the TCHP group (8.2%) compared to the AC + DPT group (1.6%). Notably, no Grade 3–4 cardiac toxicity was detected in either cohort (Table 1, 2; Fig. 1). Conclusions The TCHP regimen demonstrates efficacy comparable to anthracycline-containing regimens without increased cardiac toxicity, despite a higher incidence of hematological adverse events. Therefore, anthracycline-free regimens may be the preferred option for patients with cardiac comorbidities, while advanced lymph node involvement remains a critical poor prognostic factor. HER2-positive breast cancer neoadjuvant therapy pathological complete response Figures Figure 1 Figure 2 INTRODUCTION Breast cancer is the most common cancer type worldwide ( 1 ). It is also the most common cause of cancer-related deaths in women ( 2 ). The most frequent subtype is invasive ductal carcinoma (IDC) ( 3 ). Analysis of subtypes reveals that the hormone receptor-positive (ER, PR) group is the most common (approximately 70%), while HER2 overexpression accounts for 23%, and the triple-negative group constitutes approximately 13% ( 4 ). HER2 positivity is determined by demonstrating HER2 overexpression immunohistochemically or a HER2/CEP17 ratio greater than 2.0 using fluorescence in situ hybridization (FISH) (5 Although breast cancer with HER2 overexpression is aggressive, chemotherapy responses are quite good ( 6 ). Anti-HER2 targeted therapies administered concurrently with chemotherapy significantly increase response rates. Among these agents, trastuzumab inhibits the receptor by binding to subdomain IV of the HER2 receptor, whereas pertuzumab binds to subdomain II ( 7 ). Patients who are clinically lymph node positive or have large tumors are candidates for neoadjuvant therapy. Anthracycline, taxane, and platinum-based agents are preferred as chemotherapy alongside anti-HER2 therapies. In patients with tumors larger than 2 cm or positive lymph nodes, the addition of pertuzumab to trastuzumab and chemotherapy has been shown to be beneficial ( 8 ). Studies have reported response rates ranging from 43% to 55% when anti-HER2 therapies are added to chemotherapy ( 9 , 10 , 11 ). However, it is known that anti-HER2 targeted therapies and anthracycline-based drugs are cardiotoxic ( 12 , 13 ). Neoadjuvant treatment regimens without anthracyclines have also been used, especially in patients with a history of cardiac disease or who have previously received anthracycline-based treatment. The BCIRG-006 study compared anthracycline-free chemotherapy with anthracycline-containing regimens. Although a statistically significant increase in toxicity was observed in the anthracycline-containing regimen, survival differences favored trastuzumab-containing regimens. A higher incidence of hematological adverse events was observed in the anthracycline-free Docetaxel-Carboplatin-Trastuzumab arm ( 14 ). In another phase III study, the TRAIN-2 trial, patients receiving neoadjuvant chemotherapy with and without anthracyclines were compared. No significant differences were found between the two groups in terms of pathological complete response (pCR), event-free survival (EFS) and overall survival (OS) ( 15 ). The TRYPHAENA study compared a group receiving anthracycline-free chemotherapy combined with trastuzumab and pertuzumab against an anthracycline-based group. The patients in the anthracycline-free group were administered trastuzumab, pertuzumab, carboplatin, and docetaxel (TCHP). While the pCR rate was approximately 55% in the anthracycline group, it was 64% in the TCHP arm. Hematological toxicity was similar in both groups, whereas cardiac toxicity was observed to be slightly lower in the TCHP arm ( 16 ). Completing one year of postoperative trastuzumab treatment was found to be more effective in patients who achieved a complete response after neoadjuvant therapy. For patients who did not achieve a complete response, the trastuzumab emtansine (T-DM1) regimen was found to be superior to trastuzumab ( 17 , 18 , 19 ). Based on the existing uncertainties in the literature, the present study aims to compare the efficacy and safety of anthracycline-containing chemotherapy versus anthracycline-free (TCHP) chemotherapy in the neoadjuvant treatment of HER2-positive early-stage breast cancer. MATERIAL AND METHODS Patients diagnosed with HER2-positive breast cancer between January 2015 and December 2025 were analyzed in this study. The study was designed as a multicenter retrospective study. The patients' age, gender, tumour histology, receptor status, T, N, M stages, treatments received, treatment responses, recurrence status, and survival were obtained retrospectively from patient files and the hospital automation system. The study examined the clinicopathological characteristics of patients diagnosed with breast cancer who were HER2-positive, received neoadjuvant anti-HER2 therapy and subsequently underwent surgery. The objective was to investigate the relationship between the treatments received and both pathological complete response (pCR) and event-free survival (EFS). Inclusion Criteria: Patients over 18 years of age, diagnosed with breast cancer, identified as HER2 2+/FISH+ or HER2 3+, received neoadjuvant therapy and had an ECOG performance status of 0-1 were included in the study. Exclusion Criteria: Patients under 18 years of age, those with prior breast surgery, metastatic disease, those who had previously received chemotherapy, those with a history of breast radiotherapy and HER2-negative/HER2 1+ status were excluded. Treatment protocols were determined according to ASCO, ESMO and NCCN guidelines. The study included patients receiving either an anthracycline-containing chemotherapy regimen with HER2-targeted therapy or an anthracycline-free regimen as neoadjuvant treatment. In patients who underwent surgery following neoadjuvant therapy, adjuvant anti-HER2 therapy was completed to one year. Pathological complete response (pCR) was defined as the absence of invasive tumor cells in the breast and axillary lymph nodes. Event-free survival (EFS) was calculated as the time from the initiation of neoadjuvant therapy to disease progression, recurrence, or death. Statistical Analysis: Statistical analysis was performed using PASW Statistics for Windows, Version 18.0 (SPSS Inc., Chicago, USA). The patient characteristics and parameter frequencies were evaluated using descriptive statistical methods. The evaluation of parameter frequencies was conducted through the utilisation of descriptive statistics. Kaplan-Meier survival analysis was utilised for the purpose of conducting survival analyses. The Log Rank P value was utilised as the foundation for determining statistical significance. For survival analyses, the Cox regression "Enter" method was used for univariate analysis and the Cox regression "Backward LR" method was used for multivariate analysis. The confidence interval was set at 95% and a two-sided p-value of <0.05 was considered statistically significant. Assessment of Treatment-Related Toxicity: The assessment of treatment-related toxicity was conducted in accordance with the National Cancer Institute Common Terminology Criteria for Adverse Events (NCI-CTCAE) version 5.0 guidelines Cardiac toxicity was assessed by echocardiography at three-month intervals before and after treatment. The development of symptomatic heart failure was defined as a decrease in ejection fraction to below 50% or a decrease of more than 10%. Hematological toxicities were determined based on laboratory analyses performed before, during and after treatment. The lower limit for neutropenia was defined as a neutrophil count of 2000/mm³, for anemia as a hemoglobin level of 10.5 g/dl and for thrombocytopenia as a platelet count of 100,000/mm³. Ethical approval: Approval was obtained from the Ethics Committee of Van Yuzuncu Yıl University Faculty of Medicine. No: 34304, Date: 31.10.2025 RESULTS The study comprised 358 patients with HER2-positive (HER+2/FISH+ or HER+3) breast cancer who received neoadjuvant chemotherapy. The mean age at diagnosis was 50 years and the majority of histopathological subtypes were invasive ductal carcinoma (IDC). Regarding clinical staging, most patients were in stage T2 (74%) and N1 (60.9%). In terms of hormone receptor status, 67.3% were estrogen receptor (ER) positive, and 56.4% were progesterone receptor (PR) positive. Regarding HER2 expression levels, 85.2% of patients were HER2 3+, while 14.8% were HER2 2+/FISH+. The administered treatment protocols were ddAC + DPT (Dose-dense Adriamycin-Cyclophosphamide + Docetaxel-Pertuzumab-Trastuzumab) in 35.2%, TCHP (Docetaxel-Carboplatin-Herceptin-Pertuzumab) in 30.7%, Taxane + ddAC + Herceptin in 22.9%, and other regimens in 11.2% of patients. Overall, 95.5% of the patients completed the planned treatment regimen (Table 1). Table 1 Clinical characteristics of the patients Variables N 358 (%) Median Age 50.36 (25.0–81.0) Pathological subtype IDC 274 (76.5) ILC 13 (3.6) NOS 59 (16.5) Diğer 12 (3.4) Grade Grade 1 10 (3.2) Grade 2 207 (66.1) Grade 3 96 (30.7) Clinical T Stage cT1 56 (15.6) cT2 265 (74.0) cT3 21 (5.9) cT4 16 (4.5) Clinical N Stage cN0 40 (11.2) cN1 218 (60.9) cN2 69 (19.3) cN3 31 (8.7) Hormone receptors ER Positive 241 (67.3) PR Positive 202 (56.4) HER2 expression HER2 (+++) 305 (85.2) HER2 (++) 53 (14.8) Mediastinal lymph nodes Yes 21 (5.9) No 337 (94.1) Treatment regimen ddAC + DPT 126 (35.2) TCHP 110 (30.7) Taksan+ ddAC+Herceptin 82 (22.9) Diğer 40 (11.2) Completed treatment (Yes) 342 (95.5) Radiotherapy (Received) 271 (75.7) Abbreviations: n: Number of patients, IDC: Invasive Ductal Carcinoma, ILC: Invasive Lobular Carcinoma, ddAC: Dose-dense Adriamycin-Cyclophosphamide, DPT: Docetaxel-Pertuzumab-Trastuzumab, TCHP: Docetaxel-Carboplatin-Herceptin-Pertuzumab. In the pCR subgroup analysis, a statistical contribution was observed in the invasive lobular carcinoma (ILC) group, despite the comparatively low number of patients. Regarding clinical lymph node subgroups, the N2 group benefited most from treatment in univariate analysis, whereas the N3 group showed greater benefit in multivariate analysis. However, no statistically significant difference was observed among lymph node groups. Although T2 and T4 subgroups, as well as Grade 2 and 3 groups, appeared more significant in terms of p-values, no statistically significant difference was found in terms of odds ratio (OR). Compared to the reference arm (AC+DPT), the probability of achieving pCR was significantly lower in the group receiving "other" treatment regimens (OR: 0.35, 95% CI: 0.17-0.73, p=0.005). No statistically significant difference in pCR was observed between the TCHP and AC+DPT regimens (p=0.360). In the HER2 3+ group, although pCR rates were numerically higher in univariate analysis, there was no statistical difference in multivariate analysis (Table 2). Table 2 Univariate and multivariate analysis of parameters predicting pCR Univariate analysis Multivariate analysis Variables P value OR 95% CI P value OR 95% CI Age 0.45 0.99 0.98-1.01 0.09 0.98 0.96-1.01 Pathological subtype IDC 0.16 1.00 ILC 0.02 0.17 0.03-0.81 Others 0.74 0.81 0.24-2.73 NOS 0.86 1.05 0.59-1.86 Clinical N stage N0 0.21 1.00 N1 0.88 0.95 0.48-1.88 N2 0.15 0.56 0.26-1.25 N3 0.31 0.61 0.23-1.60 Clinical T stage T1 0.67 1.00 T2 0.33 0.75 0.41-1.35 T3 0.80 0.88 0.32-2.42 T4 0.29 0.53 0.17-1.71 Histological grade Grade 1 0.53 1.00 Grade 2 0.26 2.20 0.55-8.74 Grade 3 0.31 2.06 0.50-8.44 Treatment protocol AC+DPT 0.19 1.00 0.023 1.00 TCHP 0.98 1.00 0.59-1.67 0.65 0.86 0.46-1.62 Others 0.11 0.66 0.40-1.10 0.009 0.40 0.20-0.79 ER status Negative (-) 1.00 Positive (+) 0.85 0.96 0.61-1.50 HER2 score (+2*/+3) 0.16 1.53 0.84-2.78 0.05 2.13 0.97-4.69 PCR: Pathological Complete Response, OR: Odds Ratio, CI: Confidence Interval, IDC: Invasive Ductal Carcinoma, ILC: Invasive Lobular Carcinoma, NOS: Not Otherwise Specified, AC: Doxorubicin (Adriamycin) and Cyclophosphamide, DPT: Docetaxel, Pertuzumab and Trastuzumab, TCHP: Docetaxel, Carboplatin, Herceptin and Pertuzumab, ER: Estrogen Receptor, HER2: Human Epidermal Growth Factor Receptor 2 When the event-free survival (EFS) analysis was examined, it was determined that ER and PR positivity had no effect on survival. HER2 3+ status was identified as a risk-increasing factor for EFS compared to HER2 2+/FISH+ patients. Regarding clinical lymph node status, advanced lymph node involvement (N3) was evaluated as a risk factor for EFS (HR: 8.43, p=0.038) (Table 3), (Figure 1,2). With regard to adverse effects, febrile neutropenia was observed in 8.2% of patients in the TCHP arm and 1.6% of patients in the AC+DPT arm. Grade 1-2 anemia occurred in 42.7% of the TCHP arm versus 19.1% in the AC+DPT arm. With regard to adverse effects, febrile neutropenia was observed in 8.2% of patients in the TCHP arm and 1.6% of patients in the AC+DPT arm. No severe (Grade 3-4) cardiac events were observed (Table 4). Table 3. Results of univariate and multivariate analyses of parameters affecting event-free survival Univariate analysis Multivariate analysis Variables P value HR 95% CI P value HR 95% CI Grade Grade 1* 0.81 Grade 2 0.58 0.67 0.15-2.83 Grade 3 0.52 0.6 0.13-2.80 ER % (linear) 0.02 0.99 0.98-0.99 0.083 0.994 0.986-1.001 PR % (linear) 0.63 0.99 0.99-1.00 HER-2 status (+2*/+3) 0.02 9.03 1.24-65.3 0.038 8.436 1.12-63.43 Pathological subtype İDC* 0.65 İLC 0.97 0.00 0.00-6.43 Others 0.63 0.61 0.08-4.49 NOS 0.23 0.53 0.19-1.49 Treatment protocol ddAC + DPT* 0.016 TCHP 0.13 0.32 0.07-1.43 Other 0.017 2.4 1.17-5.18 ddAC+ taxan +herceptin 0.41 1.32 0.66-2.64 T stage T1* 0.04 T2 0.48 0.75 0.34-1.64 T3 0.18 1.97 0.71-5.46 T4 0.2 2.17 0.65-7.25 N stage N0* 0 0.11 N1 0.12 4.8 0.65-35.3 0.078 6.11 0.81-45.63 N2 0.1 5.4 0.69-42.3 0.163 4.38 0.54-34.97 N3 0.004 20.4 2.65-157.4 0.010 15.33 1.90-123.78 EFS: Event-Free Survival, HR: Hazard Ratio, CI: Confidence Interval, ER: Estrogen Receptor, PR: Progesterone Receptor, HER-2: Human Epidermal Growth Factor Receptor 2, IDC: Invasive Ductal Carcinoma, ILC: Invasive Lobular Carcinoma, NOS: Not Otherwise Specified, ddAC: Dose-dense Doxorubicin and Cyclophosphamide, DPT: Docetaxel, Pertuzumab and Trastuzumab, TCHP: Docetaxel, Carboplatin, Herceptin and Pertuzumab DISCUSSION A previous meta-analysis found that patients in stages T3 and T4 had worse pCR, EFS, and OS. Patients who achieved a complete response were found to have a longer survival time In the present study, although a numerical difference was observed between stages T2 and T4, this difference was not statistically significant. The observation of comparable pCR rates in the TCHP arm indicates that it may be as beneficial as anthracycline-containing regimens for long-term survival. While meta-analyses have shown better pCR results in hormone receptor-negative groups, our study observed no statistically significant difference in pCR between hormone receptor-positive and negative groups. Our study included a high rate of ER+ patients (67%). İt is thought that the gap may have been closed by new-generation anti-HER2 therapies (20). Although it is generally believed that patients achieving pCR with neoadjuvant therapy will have better survival, some studies do not support this. A different meta-analysis found a weak correlation between pCR and long-term survival. This result suggests that if pCR does not affect survival, anthracycline-based regimens, which are more toxic particularly to the heart, could be avoided. The present study indicated that the biological aggressiveness of the tumour may be a factor in the observed difference in survival rates between pCR and non-pCR. The fact that the HER2 3+ group in our study had worse EFS supports the notion that survival may differ in biologically aggressive diseases (21). Studies by Symmans et al. indicate that lymph node involvement is the most critical factor affecting prognosis. Metastatic lymph node involvement dramatically negatively impacts the prognosis of the disease. The high recurrence risk observed in N3 patients in our study is consistent with the literature. While the Symmans study noted that the risk of recurrence in the hormone receptor-positive group could occur in later years, it stated that the hormone receptor-negative group typically recurs within the first 5 years. In our study, hormonal status did not affect EFS. This may be explained by the insufficient maturation of our follow-up period and patient sample size (22). The Phase 3 Z1041 study demonstrated no difference between concurrent and sequential administration of trastuzumab with anthracycline-based chemotherapy. The study found no additional benefit from dose intensification. Our study goes a step further, identifying that omitting anthracyclines does not alter pCR rates. In the Z1041 study, the pCR rate was distinctly better in the hormone-negative subgroup compared to the hormone-positive subgroup. The absence of such a difference in our study may be related to the development of new anti-HER2 targeted therapies, as mentioned above (9). In the previously conducted TRAIN-2 study, an anthracycline-containing regimen was compared with an anthracycline-free regimen, and pCR rates were found to be similar. which aligns with our findings. However, while febrile neutropenia was more common in the anthracycline-containing regimen arm in the TRAIN-2 study, the opposite was true in our study. This could be due to the use of paclitaxel with carboplatin in the anthracycline-free regimen of that study, whereas our study utilized docetaxel, which is hematologically more toxic. Consistent with our study, cardiac events were found to be rare and similar between groups (15). In the GETN(A)-1 study, only docetaxel with carboplatin and trastuzumab were used as the anthracycline-free regimen. The response rate in this study was around 40%. Our study demonstrated a higher pCR rate We thought that this could be due to the use of dual anti-HER2 (trastuzumab+pertuzumab) therapy. The lower incidence of neutropenia in the GETN(A)-1 study compared to ours may be due to the inclusion of more selected patients. No cardiac adverse events were reported in that study. In our study, no additional cardiac events were observed with the addition of pertuzumab (22). In a Phase 2 study conducted by Chen and colleagues in a breast cancer patient population with HER2 +3, a pCR rate of approximately 33% was achieved with weekly paclitaxel + carboplatin. Although anti-HER2 therapy was not added in that study, it demonstrated the potential benefit of this chemotherapy group The higher pCR rate in our study demonstrates the synergistic effect of the taxane-platinum combination and anti-HER2 therapy (23). A small-sample study by Sikov et al. also used weekly carboplatin + paclitaxel, finding a response rate of 76% when trastuzumab was added. Although the sample size was small, it supports the synergistic benefit of the drugs used similarly in our study (24). In the TRYPHAENA study, the anthracycline-free TCHP regimen demonstrated sufficient efficacy in terms of pCR. In this respect, our study shows similar results, indicating that removing anthracyclines from the regimen does not negatively affect treatment. In a study by Schneeweiss et al., no cardiac events were observed in the TCHP arm, serving as a reference that omitting anthracyclines could reduce cardiac events. However, no significant difference in cardiac events was observed between regimens in our study The neutropenia rate in our study is consistent with the TCHP data in the TRYPHAENA study. This emphasizes the need for close monitoring for myelosuppression in the TCHP regimen (16). The multicenter nature of our study is limited due to patient heterogeneity. Other limiting factors include the time frame of 2015-2025, the use of different regimens, and changes in supportive care. However, the fact that anthracycline-free regimens show similar effects in real-world data is instructive. CONCLUSION In conclusion, our study demonstrates that the TCHP regimen has similar efficacy when compared to the standard anthracycline-containing regimen. While no difference was observed between the regimens in terms of cardiac toxicity, greater caution is required regarding hematological toxicity in the TCHP regimen. It should not be overlooked that patients with advanced lymph node involvement may have a worse clinical course. It is concluded that in clinical practice, anthracycline-free regimens can be used, particularly in patients with cardiac disease and sufficient hematological reserve. Abbreviations TCHP: Docetaxel, Carboplatin, Trastuzumab, Pertuzumab pCR: Pathological complete response EFS: Event-free survival AC+DPT: Adriamycin , Cyclophosphamide, Docetaxel, Pertuzumab, Trastuzumab HR: Hazard Ratio ER: Estrogen Receptor PR: Progesterone Receptor HER2: Human Epidermal Growth Factor Receptor 2 IDC: İnvasive ductal carcinoma FISH: Fluorescence in situ hybridization T-DM1: Trastuzumab emtansine ECOG: Eastern Cooperative Oncology Group Declarations Acknowledgements None Authors’ contributions M.K and S.E conceived and designed the study, performed the statistical analysis, drafted the manuscript, and critically revised it for important intellectual content. T.B, H.A.Y, M.H, S.Ç, and Z.H collected and organized the clinical data. N.A, N.K, M.Ü, M.N.A and Y.S critically reviewed the manuscript, performed additional statistical analyses, obtained funding, and provided administrative, technical, and material support. All authors read and approved the final manuscript. Funding None Availability of data and materials The database of the study is available in the corresponding author and will be sent when requested by e-mail Ethics approval and consent to participate This study approved by Ethical Committee of Van Yüzüncü Yıl University Faculty of Medicine. Due to retrospective nature of the study, Van Yüzüncü Yıl University Faculty of Medicine waived off the informed consent in our study. All methods/ protocols were performed in accordance with the relevant guidelines and regulations. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Author details ¹*²˒ ¹⁰˒ ¹¹˒¹² Department of Medical Oncology, Faculty of Medicine, Van Yüzüncü Yıl University, Van, Turkiye ³Department of Medical Oncology, Goztepe Suleyman Yalcin City Hospital, Istanbul, Turkiye ⁴˒⁶Department of Medical Oncology, Etlik City Hospital, Ankara, Turkiye ⁵Department of Medical Oncology, Faculty of Medicine , Turgut Ozal Medical Center, Malatya, Turkiye,⁷ Department of Medical Oncology, Bursa City Hospital, Bursa, Türkiye, ⁸ Department of Medical Oncology, Diyarbakır Gazi Yaşargil Training and Research Hospital, Diyarbakır, Türkiye ⁹ Department of Medical Oncology, Batman Training and Research Hospital, Batman, Türkiye References Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209–49. Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. 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J Clin Oncol. 2023;41(16):2988–97. Symmans WF, Wei C, Gould R, Yu X, Zhang Y, Liu M, et al. Long-Term Prognostic Risk After Neoadjuvant Chemotherapy Associated With Residual Cancer Burden and Breast Cancer Subtype. J Clin Oncol. 2017;35(10):1049–60. Coudert BP, Largillier R, Arnould L, Chollet P, Campone M, Coeffic D, et al. Multicenter phase II trial of neoadjuvant therapy with trastuzumab, docetaxel, and carboplatin for human epidermal growth factor receptor-2-overexpressing stage II or III breast cancer: results of the GETN(A)-1 trial. J Clin Oncol. 2007;25(19):2678–84. Chen XS, Nie XQ, Chen CM, Wu JY, Wu J, Lu JS, et al. Weekly paclitaxel plus carboplatin is an effective nonanthracycline-containing regimen as neoadjuvant chemotherapy for breast cancer. Ann Oncol. 2010;21(5):961–7. Sikov WM, Dizon DS, Strenger R, Legare RD, Theall KP, Graves TA, et al. Frequent pathologic complete responses in aggressive stages II to III breast cancers with every-4-week carboplatin and weekly paclitaxel with or without trastuzumab: a Brown University Oncology Group Study. J Clin Oncol. 2009;27(28):4693–700. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 22 Mar, 2026 Reviewers agreed at journal 05 Mar, 2026 Reviewers invited by journal 24 Feb, 2026 Editor assigned by journal 23 Feb, 2026 Editor invited by journal 02 Feb, 2026 Submission checks completed at journal 30 Jan, 2026 First submitted to journal 30 Jan, 2026 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8673435","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":596411395,"identity":"dfb4fe8f-e077-4a41-b33b-526e550aba96","order_by":0,"name":"Mahmut 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Göztepe Eğitim ve Araştırma Hastanesi","correspondingAuthor":false,"prefix":"","firstName":"Tuba","middleName":"","lastName":"Baydaş","suffix":""},{"id":596411398,"identity":"51ebf8ca-601f-4ce1-9ef9-b2668cbec2c1","order_by":3,"name":"Hatice Ayyıldız Sevim","email":"","orcid":"","institution":"Ankara City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hatice","middleName":"Ayyıldız","lastName":"Sevim","suffix":""},{"id":596411400,"identity":"ce5fea27-7c2e-4b72-9d87-8f92bdda7b56","order_by":4,"name":"Murat Haskul","email":"","orcid":"","institution":"Turgut Özal Tıp Merkezi","correspondingAuthor":false,"prefix":"","firstName":"Murat","middleName":"","lastName":"Haskul","suffix":""},{"id":596411405,"identity":"04d3cea2-bd0c-433d-8e5a-2f10a3739f49","order_by":5,"name":"Selahattin Çelik","email":"","orcid":"","institution":"Ankara City 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University","correspondingAuthor":false,"prefix":"","firstName":"Nurhan","middleName":"","lastName":"Kalkan","suffix":""},{"id":596411414,"identity":"0eb8bca3-9a57-453c-983c-9479ac0df04f","order_by":9,"name":"Muslih Ürün","email":"","orcid":"","institution":"Van Yüzüncü Yıl University","correspondingAuthor":false,"prefix":"","firstName":"Muslih","middleName":"","lastName":"Ürün","suffix":""},{"id":596411415,"identity":"e3dde3ba-038e-4c3d-8e71-eaf54932b595","order_by":10,"name":"Mehmet Naci Aldemir","email":"","orcid":"","institution":"Van Yüzüncü Yıl University","correspondingAuthor":false,"prefix":"","firstName":"Mehmet","middleName":"Naci","lastName":"Aldemir","suffix":""},{"id":596411416,"identity":"18b41d49-0c28-4384-85aa-0215d17ee485","order_by":11,"name":"Yasin Sezgin","email":"","orcid":"","institution":"Van Yüzüncü Yıl University","correspondingAuthor":false,"prefix":"","firstName":"Yasin","middleName":"","lastName":"Sezgin","suffix":""}],"badges":[],"createdAt":"2026-01-22 22:23:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8673435/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8673435/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103724369,"identity":"1bbaa4c4-c9b8-4b9d-a943-a0051325f1f1","added_by":"auto","created_at":"2026-03-02 07:57:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":41408,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan-Meier analysis comparing treatment options for event-free survival\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8673435/v1/af72e338744df76a7ef62715.png"},{"id":103724398,"identity":"7f923f13-e51e-4872-937b-838276070474","added_by":"auto","created_at":"2026-03-02 07:57:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":42822,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan-Meier analysis comparing AC+DPT and TCHP treatment regimens for event-free survival\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8673435/v1/dac51f17c43027b3bbab2801.png"},{"id":104399954,"identity":"892a6617-3abe-4d8f-9805-b7adfd542c8d","added_by":"auto","created_at":"2026-03-11 12:08:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1393060,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8673435/v1/2bc057fb-a2c7-44a4-b436-f1d13f30c69b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparison of Anthracycline-Containing and Anthracycline-Free Neoadjuvant Regimens in HER2-Positive Breast Cancer","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eBreast cancer is the most common cancer type worldwide (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). It is also the most common cause of cancer-related deaths in women (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). The most frequent subtype is invasive ductal carcinoma (IDC) (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Analysis of subtypes reveals that the hormone receptor-positive (ER, PR) group is the most common (approximately 70%), while HER2 overexpression accounts for 23%, and the triple-negative group constitutes approximately 13% (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). HER2 positivity is determined by demonstrating HER2 overexpression immunohistochemically or a HER2/CEP17 ratio greater than 2.0 using fluorescence in situ hybridization (FISH) (5 Although breast cancer with HER2 overexpression is aggressive, chemotherapy responses are quite good (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnti-HER2 targeted therapies administered concurrently with chemotherapy significantly increase response rates. Among these agents, trastuzumab inhibits the receptor by binding to subdomain IV of the HER2 receptor, whereas pertuzumab binds to subdomain II (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Patients who are clinically lymph node positive or have large tumors are candidates for neoadjuvant therapy. Anthracycline, taxane, and platinum-based agents are preferred as chemotherapy alongside anti-HER2 therapies. In patients with tumors larger than 2 cm or positive lymph nodes, the addition of pertuzumab to trastuzumab and chemotherapy has been shown to be beneficial (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Studies have reported response rates ranging from 43% to 55% when anti-HER2 therapies are added to chemotherapy (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). However, it is known that anti-HER2 targeted therapies and anthracycline-based drugs are cardiotoxic (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNeoadjuvant treatment regimens without anthracyclines have also been used, especially in patients with a history of cardiac disease or who have previously received anthracycline-based treatment. The BCIRG-006 study compared anthracycline-free chemotherapy with anthracycline-containing regimens. Although a statistically significant increase in toxicity was observed in the anthracycline-containing regimen, survival differences favored trastuzumab-containing regimens. A higher incidence of hematological adverse events was observed in the anthracycline-free Docetaxel-Carboplatin-Trastuzumab arm (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). In another phase III study, the TRAIN-2 trial, patients receiving neoadjuvant chemotherapy with and without anthracyclines were compared. No significant differences were found between the two groups in terms of pathological complete response (pCR), event-free survival (EFS) and overall survival (OS) (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe TRYPHAENA study compared a group receiving anthracycline-free chemotherapy combined with trastuzumab and pertuzumab against an anthracycline-based group. The patients in the anthracycline-free group were administered trastuzumab, pertuzumab, carboplatin, and docetaxel (TCHP). While the pCR rate was approximately 55% in the anthracycline group, it was 64% in the TCHP arm. Hematological toxicity was similar in both groups, whereas cardiac toxicity was observed to be slightly lower in the TCHP arm (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Completing one year of postoperative trastuzumab treatment was found to be more effective in patients who achieved a complete response after neoadjuvant therapy. For patients who did not achieve a complete response, the trastuzumab emtansine (T-DM1) regimen was found to be superior to trastuzumab (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBased on the existing uncertainties in the literature, the present study aims to compare the efficacy and safety of anthracycline-containing chemotherapy versus anthracycline-free (TCHP) chemotherapy in the neoadjuvant treatment of HER2-positive early-stage breast cancer.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"MATERIAL AND METHODS","content":"\u003cp\u003ePatients diagnosed with HER2-positive breast cancer between January 2015 and December 2025 were analyzed in this study. The study was designed as a multicenter retrospective study. The patients' age, gender, tumour histology, receptor status, T, N, M stages, treatments received, treatment responses, recurrence status, and survival were obtained retrospectively from patient files and the hospital automation system. The study examined the clinicopathological characteristics of patients diagnosed with breast cancer who were HER2-positive, received neoadjuvant anti-HER2 therapy and subsequently underwent surgery. The objective was to investigate the relationship between the treatments received and both pathological complete response (pCR) and event-free survival (EFS).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion Criteria:\u003c/strong\u003e Patients over 18 years of age, diagnosed with breast cancer, identified as HER2 2+/FISH+ or HER2 3+, received neoadjuvant therapy \u0026nbsp;and had an ECOG performance status of 0-1 were included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExclusion Criteria:\u003c/strong\u003e Patients under 18 years of age, those with prior breast surgery, metastatic disease, those who had previously received chemotherapy, those with a history of breast radiotherapy and HER2-negative/HER2 1+ status were excluded.\u003c/p\u003e\n\u003cp\u003eTreatment protocols were determined according to ASCO, ESMO and NCCN guidelines. The study included patients receiving either an anthracycline-containing chemotherapy regimen with HER2-targeted therapy or an anthracycline-free regimen as neoadjuvant treatment. In patients who underwent surgery following neoadjuvant therapy, adjuvant anti-HER2 therapy was completed to one year. Pathological complete response (pCR) was defined as the absence of invasive tumor cells in the breast and axillary lymph nodes. Event-free survival (EFS) was calculated as the time from the initiation of neoadjuvant therapy to disease progression, recurrence, or death.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis:\u003c/strong\u003e Statistical analysis was performed using PASW Statistics for Windows, Version 18.0 (SPSS Inc., Chicago, USA). The patient characteristics and parameter frequencies were evaluated using descriptive statistical methods. The evaluation of parameter frequencies was conducted through the utilisation of descriptive statistics. Kaplan-Meier survival analysis was utilised for the purpose of conducting survival analyses. The Log Rank P value was utilised as the foundation for determining statistical significance. For survival analyses, the Cox regression \"Enter\" method was used for univariate analysis and the Cox regression \"Backward LR\" method was used for multivariate analysis. The confidence interval was set at 95% and a two-sided p-value of \u0026lt;0.05 was considered statistically significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of Treatment-Related Toxicity:\u003c/strong\u003e The assessment of treatment-related toxicity was conducted in accordance with the National Cancer Institute Common Terminology Criteria for Adverse Events (NCI-CTCAE) version 5.0 guidelines Cardiac toxicity was assessed by echocardiography at three-month intervals before and after treatment. The development of symptomatic heart failure was defined as a decrease in ejection fraction to below 50% or a decrease of more than 10%. Hematological toxicities were determined based on laboratory analyses performed before, during and after treatment. The lower limit for neutropenia was defined as a neutrophil count of 2000/mm³, for anemia as a hemoglobin level of 10.5 g/dl and for thrombocytopenia as a platelet count of 100,000/mm³.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval:\u003c/strong\u003e Approval was obtained from the Ethics Committee of Van Yuzuncu Yıl\u003c/p\u003e\n\u003cp\u003eUniversity Faculty of Medicine. No: 34304, Date: 31.10.2025\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe study comprised 358 patients with HER2-positive (HER+2/FISH+ or HER+3) breast cancer who received neoadjuvant chemotherapy. The mean age at diagnosis was 50 years and the majority of histopathological subtypes were invasive ductal carcinoma (IDC). Regarding clinical staging, most patients were in stage T2 (74%) and N1 (60.9%). In terms of hormone receptor status, 67.3% were estrogen receptor (ER) positive, and 56.4% were progesterone receptor (PR) positive. Regarding HER2 expression levels, 85.2% of patients were HER2 3+, while 14.8% were HER2 2+/FISH+. The administered treatment protocols were ddAC + DPT (Dose-dense Adriamycin-Cyclophosphamide + Docetaxel-Pertuzumab-Trastuzumab) in 35.2%, TCHP (Docetaxel-Carboplatin-Herceptin-Pertuzumab) in 30.7%, Taxane + ddAC + Herceptin in 22.9%, and other regimens in 11.2% of patients. Overall, 95.5% of the patients completed the planned treatment regimen (Table 1).\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"619\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 619px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eClinical characteristics of the patients\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 308px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN 358 (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; Median Age\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\n \u003cp\u003e50.36 (25.0\u0026ndash;81.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePathological subtype\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u0026nbsp; IDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\n \u003cp\u003e274 (76.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u0026nbsp; ILC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\n \u003cp\u003e13 (3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u0026nbsp; NOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\n \u003cp\u003e59 (16.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u0026nbsp; Diğer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 308px;\"\u003e\n \u003cp\u003e12 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrade\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u0026nbsp; Grade 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\n \u003cp\u003e10 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u0026nbsp; Grade 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\n \u003cp\u003e207 (66.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u0026nbsp; Grade 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\n \u003cp\u003e96 (30.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical T Stage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u0026nbsp; cT1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\n \u003cp\u003e56 (15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u0026nbsp; cT2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\n \u003cp\u003e265 (74.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u0026nbsp; cT3\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\n \u003cp\u003e21 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; cT4\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\n \u003cp\u003e16 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical N Stage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u0026nbsp; cN0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\n \u003cp\u003e40 (11.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u0026nbsp; cN1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\n \u003cp\u003e218 (60.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u0026nbsp; cN2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\n \u003cp\u003e69 (19.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u0026nbsp; cN3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\n \u003cp\u003e31 (8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHormone receptors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u0026nbsp; ER Positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\n \u003cp\u003e241 (67.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u0026nbsp; PR Positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\n \u003cp\u003e202 (56.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHER2 expression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u0026nbsp; HER2 (+++)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\n \u003cp\u003e305 (85.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u0026nbsp; HER2 (++)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\n \u003cp\u003e53 (14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMediastinal lymph nodes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\n \u003cp\u003e21 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\n \u003cp\u003e337 (94.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment regimen\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u0026nbsp; ddAC + DPT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\n \u003cp\u003e126 (35.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 306px;\"\u003e\n \u003cp\u003e\u0026nbsp; TCHP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 313px;\"\u003e\n \u003cp\u003e110 (30.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 306px;\"\u003e\n \u003cp\u003e\u0026nbsp; Taksan+ ddAC+Herceptin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 313px;\"\u003e\n \u003cp\u003e82 (22.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 306px;\"\u003e\n \u003cp\u003e\u0026nbsp; Diğer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 313px;\"\u003e\n \u003cp\u003e40 (11.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 306px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCompleted treatment (Yes)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 313px;\"\u003e\n \u003cp\u003e342 (95.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 311px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRadiotherapy (Received)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 308px;\"\u003e\n \u003cp\u003e271 (75.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: n: Number of patients, IDC: Invasive Ductal Carcinoma, ILC: Invasive Lobular Carcinoma, ddAC: Dose-dense Adriamycin-Cyclophosphamide, DPT: Docetaxel-Pertuzumab-Trastuzumab, TCHP: Docetaxel-Carboplatin-Herceptin-Pertuzumab.\u003c/p\u003e\n\u003cp\u003eIn the pCR subgroup analysis, a statistical contribution was observed in the invasive lobular carcinoma (ILC) group, despite the comparatively low number of patients. Regarding clinical lymph node subgroups, the N2 group benefited most from treatment in univariate analysis, whereas the N3 group showed greater benefit in multivariate analysis. However, no statistically significant difference was observed among lymph node groups. Although T2 and T4 subgroups, as well as Grade 2 and 3 groups, appeared more significant in terms of p-values, no statistically significant difference was found in terms of odds ratio (OR). Compared to the reference arm (AC+DPT), the probability of achieving pCR was significantly lower in the group receiving \u0026quot;other\u0026quot; treatment regimens (OR: 0.35, 95% CI: 0.17-0.73, p=0.005). No statistically significant difference in pCR was observed between the TCHP and AC+DPT regimens (p=0.360). In the HER2 3+ group, although pCR rates were numerically higher in univariate analysis, there was no statistical difference in multivariate analysis (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"643\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 643px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2 Univariate and multivariate analysis of parameters predicting pCR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 277px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Univariate analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 221px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Multivariate analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.98-1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e0.96-1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePathological subtype\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eIDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eILC\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.03-0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.24-2.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eNOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.59-1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical N stage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eN0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eN1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.48-1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eN2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.26-1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eN3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.23-1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical T stage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eT2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.41-1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eT3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.32-2.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eT4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.17-1.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistological grade\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eGrade 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eGrade 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.55-8.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eGrade 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e2.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.50-8.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment protocol\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eAC+DPT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eTCHP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.59-1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e0.46-1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.40-1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e0.20-0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eER status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eNegative (-)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003ePositive (+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.61-1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHER2 score (+2*/+3)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e1.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e0.84-2.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e2.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e0.97-4.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ePCR: Pathological Complete Response, OR: Odds Ratio, CI: Confidence Interval, IDC: Invasive Ductal Carcinoma, ILC: Invasive Lobular Carcinoma, NOS: Not Otherwise Specified, AC: Doxorubicin (Adriamycin) and Cyclophosphamide, DPT: Docetaxel, Pertuzumab and Trastuzumab, TCHP: Docetaxel, Carboplatin, Herceptin and Pertuzumab, ER: Estrogen Receptor, HER2: Human Epidermal Growth Factor Receptor 2\u003c/p\u003e\n\u003cp\u003eWhen the event-free survival (EFS) analysis was examined, it was determined that ER and PR positivity had no effect on survival. HER2 3+ status was identified as a risk-increasing factor for EFS compared to HER2 2+/FISH+ patients. Regarding clinical lymph node status, advanced lymph node involvement (N3) was evaluated as a risk factor for EFS (HR: 8.43, p=0.038) (Table 3), (Figure 1,2).\u003c/p\u003e\n\u003cp\u003eWith regard to adverse effects, febrile neutropenia was observed in 8.2% of patients in the TCHP arm and 1.6% of patients in the AC+DPT arm. Grade 1-2 anemia occurred in 42.7% of the TCHP arm versus 19.1% in the AC+DPT arm. With regard to adverse effects, febrile neutropenia was observed in 8.2% of patients in the TCHP arm and 1.6% of patients in the AC+DPT arm. No severe (Grade 3-4) cardiac events were observed (Table 4).\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"642\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 632px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3. Results of univariate and multivariate analyses of parameters affecting event-free survival\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 260px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 271px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariate analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrade\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp; Grade 1*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp; Grade 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.15-2.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp; Grade 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.13-2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eER % (linear)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.98-0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.994\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.986-1.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePR % (linear)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.99-1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHER-2 status (+2*/+3)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e9.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e1.24-65.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e8.436\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e1.12-63.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePathological subtype\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp; İDC*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp; İLC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.00-6.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp; Others\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.08-4.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp; NOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.19-1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment protocol\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp; ddAC + DPT*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp; TCHP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.07-1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp; Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e1.17-5.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp; ddAC+ taxan +herceptin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.66-2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT stage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp; T1*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp; T2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.34-1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp; T3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.71-5.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp; T4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e2.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.65-7.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN stage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp; N0*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp; N1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.65-35.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e6.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.81-45.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp; N2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e5.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.69-42.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e4.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e0.54-34.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp; N3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e20.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e2.65-157.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e15.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e1.90-123.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eEFS: Event-Free Survival, HR: Hazard Ratio, CI: Confidence Interval, ER: Estrogen Receptor, PR: Progesterone Receptor, HER-2: Human Epidermal Growth Factor Receptor 2, \u0026nbsp;IDC: Invasive Ductal Carcinoma, ILC: Invasive Lobular Carcinoma, NOS: Not Otherwise Specified, ddAC: Dose-dense Doxorubicin and Cyclophosphamide, DPT: Docetaxel, Pertuzumab and Trastuzumab, TCHP: Docetaxel, Carboplatin, Herceptin and Pertuzumab\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\" width=\"695\" height=\"646\"\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eA previous meta-analysis found that patients in stages T3 and T4 had worse pCR, EFS, and OS. Patients who achieved a complete response were found to have a longer survival time In the present study, although a numerical difference was observed between stages T2 and T4, this difference was not statistically significant. The observation of comparable pCR rates in the TCHP arm indicates that it may be as beneficial as anthracycline-containing regimens for long-term survival. While meta-analyses have shown better pCR results in hormone receptor-negative groups, our study observed no statistically significant difference in pCR between hormone receptor-positive and negative groups. Our study included a high rate of ER+ patients (67%). İt is thought that the gap may have been closed by new-generation anti-HER2 therapies (20).\u003c/p\u003e\n\u003cp\u003eAlthough it is generally believed that patients achieving pCR with neoadjuvant therapy will have better survival, some studies do not support this. A different meta-analysis found a weak correlation between pCR and long-term survival. This result suggests that if pCR does not affect survival, anthracycline-based regimens, which are more toxic particularly to the heart, could be avoided. The present study indicated that the biological aggressiveness of the tumour may be a factor in the observed difference in survival rates between pCR and non-pCR. The fact that the HER2 3+ group in our study had worse EFS supports the notion that survival may differ in biologically aggressive diseases (21).\u003c/p\u003e\n\u003cp\u003eStudies by Symmans et al. indicate that lymph node involvement is the most critical factor affecting prognosis. Metastatic lymph node involvement dramatically negatively impacts the prognosis of the disease. The high recurrence risk observed in N3 patients in our study is consistent with the literature. While the Symmans study noted that the risk of recurrence in the hormone receptor-positive group could occur in later years, it stated that the hormone receptor-negative group typically recurs within the first 5 years. In our study, hormonal status did not affect EFS. This may be explained by the insufficient maturation of our follow-up period and patient sample size (22).\u003c/p\u003e\n\u003cp\u003eThe Phase 3 Z1041 study demonstrated no difference between concurrent and sequential administration of trastuzumab with anthracycline-based chemotherapy. The study found no additional benefit from dose intensification. Our study goes a step further, identifying that omitting anthracyclines does not alter pCR rates. In the Z1041 study, the pCR rate was distinctly better in the hormone-negative subgroup compared to the hormone-positive subgroup. The absence of such a difference in our study may be related to the development of new anti-HER2 targeted therapies, as mentioned above (9).\u003c/p\u003e\n\u003cp\u003eIn the previously conducted TRAIN-2 study, an anthracycline-containing regimen was compared with an anthracycline-free regimen, and pCR rates were found to be similar. which aligns with our findings. However, while febrile neutropenia was more common in the anthracycline-containing regimen arm in the TRAIN-2 study, the opposite was true in our study. This could be due to the use of paclitaxel with carboplatin in the anthracycline-free regimen of that study, whereas our study utilized docetaxel, which is hematologically more toxic. Consistent with our study, cardiac events were found to be rare and similar between groups (15).\u003c/p\u003e\n\u003cp\u003eIn the GETN(A)-1 study, only docetaxel with carboplatin and trastuzumab were used as the anthracycline-free regimen. The response rate in this study was around 40%. Our study demonstrated a higher pCR rate We thought that this could be due to the use of dual anti-HER2 (trastuzumab+pertuzumab) therapy. The lower incidence of neutropenia in the GETN(A)-1 study compared to ours may be due to the inclusion of more selected patients. No cardiac adverse events were reported in that study. In our study, no additional cardiac events were observed with the addition of pertuzumab (22).\u003c/p\u003e\n\u003cp\u003eIn a Phase 2 study conducted by Chen and colleagues in a breast cancer patient population with HER2 +3, a pCR rate of approximately 33% was achieved with weekly paclitaxel + carboplatin. Although anti-HER2 therapy was not added in that study, it demonstrated the potential benefit of this chemotherapy group The higher pCR rate in our study demonstrates the synergistic effect of the taxane-platinum combination and anti-HER2 therapy (23).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA small-sample study by Sikov et al. also used weekly carboplatin + paclitaxel, finding a response rate of 76% when trastuzumab was added. Although the sample size was small, it supports the synergistic benefit of the drugs used similarly in our study (24).\u003c/p\u003e\n\u003cp\u003eIn the TRYPHAENA study, the anthracycline-free TCHP regimen demonstrated sufficient efficacy in terms of pCR. In this respect, our study shows similar results, indicating that removing anthracyclines from the regimen does not negatively affect treatment. In a study by Schneeweiss et al., no cardiac events were observed in the TCHP arm, serving as a reference that omitting anthracyclines could reduce cardiac events. However, no significant difference in cardiac events was observed between regimens in our study The neutropenia rate in our study is consistent with the TCHP data in the TRYPHAENA study. This emphasizes the need for close monitoring for myelosuppression in the TCHP regimen (16).\u003c/p\u003e\n\u003cp\u003eThe multicenter nature of our study is limited due to patient heterogeneity. Other limiting factors include the time frame of 2015-2025, the use of different regimens, and changes in supportive care. \u0026nbsp;However, the fact that anthracycline-free regimens show similar effects in real-world data is instructive.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eIn conclusion, our study demonstrates that the TCHP regimen has similar efficacy when compared to the standard anthracycline-containing regimen. While no difference was observed between the regimens in terms of cardiac toxicity, greater caution is required regarding hematological toxicity in the TCHP regimen. It should not be overlooked that patients with advanced lymph node involvement may have a worse clinical course. It is concluded that in clinical practice, anthracycline-free regimens can be used, particularly in patients with cardiac disease and sufficient hematological reserve.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eTCHP: Docetaxel, Carboplatin, Trastuzumab, Pertuzumab\u003c/p\u003e\n\u003cp\u003epCR: Pathological complete response\u003c/p\u003e\n\u003cp\u003eEFS: Event-free survival\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAC+DPT: Adriamycin , Cyclophosphamide, Docetaxel, Pertuzumab, Trastuzumab\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHR: Hazard Ratio\u003c/p\u003e\n\u003cp\u003eER: Estrogen Receptor\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePR: Progesterone Receptor\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHER2: Human Epidermal Growth Factor Receptor 2\u003c/p\u003e\n\u003cp\u003eIDC: İnvasive ductal carcinoma\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFISH: Fluorescence in situ hybridization\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eT-DM1: Trastuzumab emtansine\u003c/p\u003e\n\u003cp\u003eECOG: Eastern Cooperative Oncology Group\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eM.K and S.E conceived and designed the study, performed the statistical analysis, drafted the manuscript, and critically revised it for important intellectual content. T.B, H.A.Y, M.H, S.Ç, and Z.H collected and organized the clinical data. N.A, N.K, M.Ü, M.N.A and Y.S critically reviewed the manuscript, performed additional statistical analyses, obtained funding, and provided administrative, technical, and material support. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe database of the study is available in the corresponding author and will be sent when requested by e-mail\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study approved by Ethical Committee of Van Yüzüncü Yıl University Faculty of Medicine. Due to retrospective nature of the study, Van Yüzüncü Yıl University Faculty of Medicine waived off the informed consent in our study. All methods/ protocols were performed in accordance with the relevant guidelines and regulations.\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\u003eCompeting interests\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e¹*²˒ ¹⁰˒ ¹¹˒¹² Department of Medical Oncology, Faculty of Medicine, Van Yüzüncü Yıl University, Van, Turkiye ³Department of Medical Oncology, Goztepe Suleyman Yalcin City Hospital, Istanbul, Turkiye ⁴˒⁶Department of Medical Oncology, Etlik City Hospital, Ankara, Turkiye ⁵Department of Medical Oncology, Faculty of Medicine , Turgut Ozal Medical Center, Malatya, Turkiye,⁷ Department of Medical Oncology, Bursa City Hospital, Bursa, Türkiye, ⁸ Department of Medical Oncology, Diyarbakır Gazi Yaşargil Training and Research Hospital, Diyarbakır, Türkiye ⁹ Department of Medical Oncology, Batman Training and Research Hospital, Batman, Türkiye\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209\u0026ndash;49.\u003c/li\u003e\n\u003cli\u003eSiegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA Cancer J Clin. 2023;73(1):17\u0026ndash;48.\u003c/li\u003e\n\u003cli\u003eLi CI, Uribe DJ, Daling JR. Clinical characteristics of different histologic types of breast cancer. Br J Cancer. 2005;93(9):1046\u0026ndash;52.\u003c/li\u003e\n\u003cli\u003eParise CA, Bauer KR, Brown MM, Caggiano V. Breast cancer subtypes as defined by the estrogen receptor (ER), progesterone receptor (PR), and the human epidermal growth factor receptor 2 (HER2) among women with invasive breast cancer in California, 1999-2004. Breast J. 2009;15(6):593\u0026ndash;602.\u003c/li\u003e\n\u003cli\u003eWolff AC, Hammond ME, Hicks DG, Dowsett M, McShane LM, Allison KH, et al. Recommendations for human epidermal growth factor receptor 2 testing in breast cancer: American Society of Clinical Oncology/College of American Pathologists clinical practice guideline update. J Clin Oncol. 2013;31(31):3997\u0026ndash;4013.\u003c/li\u003e\n\u003cli\u003eCortazar P, Zhang L, Untch M, Mehta K, Costantino JP, Wolmark N, et al. Pathological complete response and long-term clinical benefit in breast cancer: the CTNeoBC pooled analysis. Lancet. 2014;384(9938):164\u0026ndash;72.\u003c/li\u003e\n\u003cli\u003eWolff AC, Hammond MEH, Allison KH, Harvey BE, Mangu PB, Bartlett JMS, et al. Human Epidermal Growth Factor Receptor 2 Testing in Breast Cancer: American Society of Clinical Oncology/College of American Pathologists Clinical Practice Guideline Focused Update. J Clin Oncol. 2018;36(20):2105\u0026ndash;22.\u003c/li\u003e\n\u003cli\u003eKolberg HC, Akpolat-Basci L, Stephanou M, Aktas B, Hannig CV, Liedtke C. Neoadjuvant chemotherapy with docetaxel, carboplatin and weekly trastuzumab is active in HER2-positive early breast cancer: results after a median follow-up of over 4 years. Breast Care (Basel). 2016;11(5):323\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eBuzdar AU, Suman VJ, Meric-Bernstam F, Leitch AM, Ellis MJ, Boughey JC, et al. Fluorouracil, epirubicin, and cyclophosphamide (FEC-75) followed by paclitaxel plus trastuzumab versus paclitaxel plus trastuzumab followed by FEC-75 plus trastuzumab as neoadjuvant treatment for patients with HER2-positive breast cancer (Z1041): a randomised, controlled, phase 3 trial. Lancet Oncol. 2013;14(13):1317\u0026ndash;25.\u003c/li\u003e\n\u003cli\u003eRobidoux A, Tang G, Rastogi P, Geyer CE Jr, Azar CA, Atkins JN, et al. Lapatinib as a component of neoadjuvant therapy for HER2-positive operable breast cancer (NSABP protocol B-41): an open-label, randomised phase 3 trial. Lancet Oncol. 2013;14(12):1183\u0026ndash;92.\u003c/li\u003e\n\u003cli\u003eUntch M, Loibl S, Bischoff J, Eidtmann H, Kaufmann M, Blohmer JU, et al. Lapatinib versus trastuzumab in combination with neoadjuvant anthracycline-taxane-based chemotherapy (GeparQuinto, GBG 44): a randomised phase 3 trial. Lancet Oncol. 2012;13(2):135\u0026ndash;44.\u003c/li\u003e\n\u003cli\u003eCote GM, Sawyer DB, Chabner BA. ERBB2 inhibition and heart failure. N Engl J Med. 2012;367(22):2150\u0026ndash;3.\u003c/li\u003e\n\u003cli\u003eSlamon D, Eiermann W, Robert N, Pienkowski T, Martin M, Press M, et al. Adjuvant trastuzumab in HER2-positive breast cancer. N Engl J Med. 2011;365(14):1273\u0026ndash;83.\u003c/li\u003e\n\u003cli\u003ePerez EA, Press MF, Dueck AC, Jenkins RB, Kim C, Chen B, et al. Immunohistochemistry and fluorescence in situ hybridization assessment of HER2 in clinical trials of adjuvant therapy for breast cancer (NCCTG N9831, BCIRG 006, and BCIRG 005). Breast Cancer Res Treat. 2013;138(1):99\u0026ndash;108.\u003c/li\u003e\n\u003cli\u003evan Ramshorst MS, van der Voort A, van Werkhoven ED, Mandjes IA, Kemper I, Dezentj\u0026eacute; VO, et al. Neoadjuvant chemotherapy with or without anthracyclines in the presence of dual HER2 blockade for HER2-positive breast cancer (TRAIN-2): a multicentre, open-label, randomised, phase 3 trial. Lancet Oncol. 2018;19(12):1630\u0026ndash;40.\u003c/li\u003e\n\u003cli\u003eSchneeweiss A, Chia S, Hickish T, Harvey V, Eniu A, Hegg R, et al. Pertuzumab plus trastuzumab in combination with standard neoadjuvant anthracycline-containing and anthracycline-free chemotherapy regimens in patients with HER2-positive early breast cancer: a randomized phase II cardiac safety study (TRYPHAENA). Ann Oncol. 2013;24(9):2278\u0026ndash;84.\u003c/li\u003e\n\u003cli\u003evon Minckwitz G, Huang CS, Mano MS, Loibl S, Mamounas EP, Untch M, et al. Trastuzumab Emtansine for Residual Invasive HER2-Positive Breast Cancer. N Engl J Med. 2019;380(7):617\u0026ndash;28.\u003c/li\u003e\n\u003cli\u003eGeyer CE Jr, Untch M, Huang CS, Mano MS, Mamounas EP, Wolmark N, et al. Survival with Trastuzumab Emtansine in Residual HER2-Positive Breast Cancer. N Engl J Med. 2025;392(3):249\u0026ndash;57.\u003c/li\u003e\n\u003cli\u003evan Mackelenbergh MT, Loibl S, Untch M, Buyse M, Geyer CE Jr, Gianni L, et al. Pathologic Complete Response and Individual Patient Prognosis After Neoadjuvant Chemotherapy Plus Anti-Human Epidermal Growth Factor Receptor 2 Therapy of Human Epidermal Growth Factor Receptor 2-Positive Early Breast Cancer. J Clin Oncol. 2023;41(16):2998\u0026ndash;3008.\u003c/li\u003e\n\u003cli\u003eSquifflet P, Saad ED, Loibl S, van Mackelenbergh MT, Untch M, Rastogi P, et al. Re-Evaluation of Pathologic Complete Response as a Surrogate for Event-Free and Overall Survival in Human Epidermal Growth Factor Receptor 2-Positive, Early Breast Cancer Treated With Neoadjuvant Therapy Including Anti-Human Epidermal Growth Factor Receptor 2 Therapy. J Clin Oncol. 2023;41(16):2988\u0026ndash;97.\u003c/li\u003e\n\u003cli\u003eSymmans WF, Wei C, Gould R, Yu X, Zhang Y, Liu M, et al. Long-Term Prognostic Risk After Neoadjuvant Chemotherapy Associated With Residual Cancer Burden and Breast Cancer Subtype. J Clin Oncol. 2017;35(10):1049\u0026ndash;60.\u003c/li\u003e\n\u003cli\u003eCoudert BP, Largillier R, Arnould L, Chollet P, Campone M, Coeffic D, et al. Multicenter phase II trial of neoadjuvant therapy with trastuzumab, docetaxel, and carboplatin for human epidermal growth factor receptor-2-overexpressing stage II or III breast cancer: results of the GETN(A)-1 trial. J Clin Oncol. 2007;25(19):2678\u0026ndash;84.\u003c/li\u003e\n\u003cli\u003eChen XS, Nie XQ, Chen CM, Wu JY, Wu J, Lu JS, et al. Weekly paclitaxel plus carboplatin is an effective nonanthracycline-containing regimen as neoadjuvant chemotherapy for breast cancer. Ann Oncol. 2010;21(5):961\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eSikov WM, Dizon DS, Strenger R, Legare RD, Theall KP, Graves TA, et al. Frequent pathologic complete responses in aggressive stages II to III breast cancers with every-4-week carboplatin and weekly paclitaxel with or without trastuzumab: a Brown University Oncology Group Study. J Clin Oncol. 2009;27(28):4693\u0026ndash;700.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"HER2-positive breast cancer, neoadjuvant therapy, pathological complete response","lastPublishedDoi":"10.21203/rs.3.rs-8673435/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8673435/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eConcurrent administration of anti-HER2 therapies and chemotherapy has significantly improved response rates (43%\u0026ndash;55%). However, the potential for cardiotoxicity when combining anti-HER2 agents with anthracyclines remains a concern. Consequently, anthracycline-free regimens are increasingly utilized, particularly for patients with cardiac history. This study aims to compare the efficacy and safety of anthracycline-containing chemotherapy versus anthracycline-free TCHP (Docetaxel, Carboplatin, Trastuzumab, and Pertuzumab) regimens in the neoadjuvant treatment of HER2-positive early-stage breast cancer.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis multicenter retrospective study analyzed patients diagnosed with HER2-positive breast cancer between 2015 and 2025 who received neoadjuvant anti-HER2 therapy followed by surgery. We evaluated the association between treatment regimens and outcomes, specifically pathological complete response (pCR)\u0026mdash;defined as the absence of residual invasive tumor in the breast and axillary nodes\u0026mdash;and event-free survival (EFS).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 358 patients were included, with a mean age of 50 years. Most presented with T2 tumors (74%) and N1 disease (60.9%). The most common regimens were Adriamycin, Cyclophosphamide, Docetaxel, Pertuzumab, Trastuzumab (AC\u0026thinsp;+\u0026thinsp;DPT) (35.2%) and TCHP (30.7%), with a 95.5% treatment completion rate. Pathological complete response rates were statistically comparable between the AC\u0026thinsp;+\u0026thinsp;DPT and TCHP regimens (p\u0026thinsp;=\u0026thinsp;0.360). Conversely, significantly lower pCR rates were observed with other regimens (OR 0.35, 95% CI 0.17\u0026ndash;0.73; p\u0026thinsp;=\u0026thinsp;0.005). Advanced lymph node involvement (N3) was strongly associated with worse event-free survival (HR 8.43, p\u0026thinsp;=\u0026thinsp;0.038), while ER and PR status showed no significant impact. Regarding safety, febrile neutropenia was more frequent in the TCHP group (8.2%) compared to the AC\u0026thinsp;+\u0026thinsp;DPT group (1.6%). Notably, no Grade 3\u0026ndash;4 cardiac toxicity was detected in either cohort (Table\u0026nbsp;1, 2; Fig.\u0026nbsp;1).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe TCHP regimen demonstrates efficacy comparable to anthracycline-containing regimens without increased cardiac toxicity, despite a higher incidence of hematological adverse events. Therefore, anthracycline-free regimens may be the preferred option for patients with cardiac comorbidities, while advanced lymph node involvement remains a critical poor prognostic factor.\u003c/p\u003e","manuscriptTitle":"Comparison of Anthracycline-Containing and Anthracycline-Free Neoadjuvant Regimens in HER2-Positive Breast Cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-02 07:56:08","doi":"10.21203/rs.3.rs-8673435/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-03-23T00:50:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"278481154376823173324868274419731818592","date":"2026-03-05T11:37:46+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-24T12:14:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-23T07:43:24+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-02T06:59:01+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-30T16:14:42+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2026-01-30T16:06:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"797f86be-9e85-4b03-96c6-7e44d102c881","owner":[],"postedDate":"March 2nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-02T07:56:08+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-02 07:56:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8673435","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8673435","identity":"rs-8673435","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}