Long-term outcomes for neoadjuvant versus adjuvant chemotherapy in early breast cancer: meta-analysis of individual patient data from ten randomised trials

Factors associated with locoregional recurrence after neoadjuvant chemotherapy for breast cancer in a safety-net medical center

BACKGROUND

The management of locally advanced breast cancer poses significant challenges, with contemporary strategies involving an approach that combines systemic and local treatment. The current study was performed to validate the clinical impression that locoregional recurrences have become increasingly uncommon after standardized multimodal treatment protocol.Please check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary.All authors and affiliations are correct.

METHODS

A retrospective analysis was performed using a single-institution database that included clinical, radiographic, and pathologic parameters for all non-metastatic and non-inflammatory breast cancer patients treated with neoadjuvant chemotherapy (NAC) from 2015 to 2023. Uni- and multivariable analyses were performed to define associations between clinical factors, recurrence, and RFS.

RESULTS

The median age was 51 years for 274 predominantly Hispanic (78%) patients, with a median follow-up of 38.1 months. The recurrence rates were 4% local, 2% regional, and 18% distant. Median time from surgery to local recurrence was 8.2 months and to regional recurrence was 9.7 months. There were no locoregional clinical recurrences in 92 (34%) patients who had pCR or in 85 (31%) patients who had radiological complete response after NAC. Locoregional recurrences were uncommon > 12 months after surgery. Five of 11 local recurrences occurred in patients who had a poor response to NAC (ypT4b). All 6 patients having regional recurrences had adjuvant radiation therapy, and only 2 occurred in patients who were pathologically node-negative (ypN0) post-NAC.

CONCLUSIONS

Favorable responses to NAC were associated with excellent locoregional control rates. Results achieved for predominantly Hispanic patients at a safety net medical center were similar to those reported in prospective, randomized clinical trials.

Optimal timing of cancer treatments: a call for emerging evidence from clinical trials and real-world studies

Cancer treatment has entered the era of personalised or precision medicine. Biomarker-driven therapies provide improved treatment efficacy and manageable toxicity profiles compared to systemic standard-of-care therapies. They also drive the development of combining non-surgical treatments, extending indications to early-stage tumours and further refining treatment lines with more precise options. The current treatment landscape, however, has introduced a complexity of approaches to cancer treatment, including the optimal timing of when to initiate and discontinue these treatments. Of note, treatment timing usually lacks evaluation in clinical trials and can be variable in real-world settings due to the impacts of medical, healthcare, and social factors. Given that more patients can benefit from multi-modality strategies, a better understanding of the prognostic impact of treatment-to-treatment intervals (TTIs) - the intervals between combined treatments and between treatment lines - is needed. Studies for this purpose can rely on existing trial and real-world data and be context-specific for treatment options, therapeutic settings, cancer types and biomarkers, healthcare settings or systems. This perspective article calls for emerging evidence of the optimal timing of cancer treatments. We anticipate that new studies on the optimal timing will bring new insights into how to better use cancer treatments, further improving treatment efficacy.

Therapy of early breast cancer: current status and perspectives

Medical advancements in breast cancer are truly remarkable. Especially in recent years, numerous new therapeutics have been approved and surgical strategies have been de-escalated for specific patient groups. In the therapeutic setting, CDK4/6 inhibitors as oral maintenance therapy in early breast cancer and immune checkpoint inhibitors (Pembrolizumab) for triple-negative breast cancer (BC) are noteworthy. In the surgical field, prospective randomized controlled trials have currently explored the possibility to deescalate axillary surgery by omitting sentinel lymph node excision (INSEMA, SOUND). As a result, there have been significant improvements in prognosis and a reduction in surgical morbidity for patients. Many exciting trials are underway, and it remains to be seen whether antibody-drug conjugates beyond trastuzumab emtansine, will find their way into the treatment lines for early-stage BC. Furthermore, the integration of artificial intelligence in both diagnostics and treatment recommendation evaluation is a promising area with great potential.

Dynamic predictive power of TP53 signatures in breast cancer prognosis: Pre- and post-neoadjuvant chemotherapy insights

BACKGROUND

The TP53 signature determined using a biopsy specimen before neoadjuvant chemotherapy (pre-NAC biopsy specimens) predicts NAC response and prognosis in breast cancer. We aimed to compare the clinical utility of the TP53 signature determined using pre-NAC biopsy specimens and surgical specimens after NAC (post-NAC surgical specimens).

METHODS

This observational cohort study included patients with paired pre-NAC biopsy and post-NAC surgical specimens, analyzing the association between the TP53 signature from each specimen and prognosis (UMIN000042055).

RESULTS

Pre-NAC biopsy specimens classified 71 patients into those having a TP53 mutant signature (pre-mt, n = 47) and wild-type signature (pre-wt, n = 24), with the same for post-NAC surgical specimens (post-mt, n = 16 and post-wt, n = 55). Among the 47 pre-mt patients, 31 became post-wt (pre-mt/post-wt), whereas 16 remained post-mt (pre-mt/post-mt). All pre-wt patients remained post-wt (pre-wt/post-wt). Recurrence-free survival (RFS) was significantly shorter in the pre-mt group than in the pre-wt group, although no significant difference was observed between the post-mt and post-wt groups. Change in the TP53 signature following NAC did not affect predictive ability of the TP53 signature determined using pre-NAC biopsy specimens.

CONCLUSIONS

The TP53 signature status should be determined using pre-NAC biopsy specimens.

Is It Possible to Accurately Evaluate the Tumor Bed After Neoadjuvant Chemotherapy Using a 14G Tru-Cut Biopsy?

Background/Objectives: Accurately identifying residual disease in the breast following neoadjuvant systemic therapy (NST) is a critical aspect of treatment planning. While surgery remains the standard treatment, its omission may be considered in exceptional responders. However, this strategy is still under investigation and carries local and distant recurrence risks. No definitive method currently exists to confirm pathologic complete response (pCR) after NST. This study evaluates the reliability of ultrasound-guided 14G Tru-Cut biopsy in assessing post-NST disease status. Methods: Data from 204 breast cancer patients who underwent ultrasound-guided 14G Tru-Cut biopsy before surgery at Istanbul University Oncology Institute (March 2015-May 2024) were analyzed. Concordance between Tru-Cut biopsy and final pathology was assessed, along with diagnostic accuracy parameters, including false-negative rate (FNR), accuracy, negative predictive value (NPV), and positive predictive value (PPV). Results: The median patient age was 45 years (range: 26-86). The median initial tumor size was 32 mm, reducing to 10 mm post-treatment. Pathologic complete response (pCR) was 33.8% in surgical specimens and 40.7% in biopsy samples. Biopsy misdiagnosed 15 patients, with an overall FNR of 11.1% and accuracy of 92.2% (95% CI, 7.1-18.1%; 95% CI, 87.6-95.5%). Among patients with radiologic complete response (rCR) (n = 99), FNR was 25.8%, and accuracy was 92.1%. The best outcomes were in the rCR and Tru-Cut pCR subgroup, with an FNR of 5.9% and accuracy of 95.6%. In triple-negative breast cancer patients, FNR was 5%, and an accuracy was 97.4%. Conclusions: Although obtaining eight or more samples with a 14G Tru-Cut biopsy after NST is insufficient to alter clinical practice for detecting residual disease, the promising results observed in the rCR and Tru-Cut pCR subgroups suggest its potential role in guiding treatment strategies.

The 2024 Assisi think tank on breast cancer: Focus on the use of a tumour bed boost after breast conserving therapy

At the Fifth Assisi Think Tank Meeting (ATTM) on breast cancer, one key topic was the role of tumor bed boost in invasive breast cancer and ductal carcinoma in situ. The need for a tumor bed boost after whole breast irradiation is controversial. A literature review assessed boost indications, target volume definition, techniques, dose fractionation, and ongoing trials. Findings indicated that while a boost halves the risk of local recurrence at 10 years, it also leads to worsened cosmetic outcomes and increased fibrosis without improving overall survival. Therefore, we would recommend to omit the boost if the estimated reduction in local recurrence at 10 years is less than 3 %, and to apply shared decision-making with patients, if the boost is expected to reduce the local recurrence rate with >3 % at 10 years. Future research will focus on identifying patient subgroups that can safely omit the boost and improving boost volume precision.

Personalized multifactorial risk assessment in neoadjuvant-treated breast carcinoma

PURPOSE

Due to biological heterogeneity of breast carcinoma, predicting the individual response to neoadjuvant treatment (NAT) is complex. Consequently, there are no comprehensive, generally accepted practices to guide post-treatment follow-up. We present clinical and histopathological criteria to advance the prediction of disease outcome in NA-treated breast cancer.

METHODS

A retrospective consecutive cohort of 257 NA-treated Finnish breast cancer patients with up to 13-year follow-up and the corresponding tissue samples of pre- and post-NAT breast and metastatic specimen were evaluated for prognostic impacts. All relevant clinical and biomarker characteristics potentially correlated with tumor response to NAT, course of disease, or outcome of breast cancer were included in the statistical analyses.

RESULTS

The results highlight the intensified characterization of distinguished prognostic factors and previously overlooked histological features, e.g., mitotic and apoptotic activity. Particularly, decreased PR indicated 3.8-fold (CI 1.9-7.4, p = 0.0001) mortality risk, and a > 10.5-year shorter survival for the majority, > 75% of patients (Q1). Clinically applicable prognostic factors both preceding and following NAT were identified and compiled into heat maps to quantify mortality and recurrence risks. Combinations of risk factors for aggressive disease were exemplified as an interactive tool (bcnatreccalc.utu.fi) to illustrate the spectrum of disease outcomes.

CONCLUSION

The results emphasize the value of comprehensive evaluation of conventional patient and biomarker characteristics, especially concerning re-assessment of biomarkers, risk-adapted surveillance, and personalized treatment strategies. Future personalized NA-treatment strategies might benefit from models combining risk-adapted surveillance data and post-NAT re-assessed biomarkers.

LINC01235 Promotes Clonal Evolution through DNA Replication Licensing-Induced Chromosomal Instability in Breast Cancer

Despite the development of HER2-targeting drugs such as trastuzumab and T-DXd, treatment resistance is a substantial challenge, often leading to relapse and distant metastasis. Tumor heterogeneity in HER2-positive breast cancer drives the evolution of resistant clones following therapeutic stress. However, the targetable drivers of anti-HER2 treatment resistance are not thoroughly identified. This study aims to use neoadjuvant-targeted therapy cohorts and a patient-derived organoid in vitro treatment model to uncover the potential targetable drivers of anti-HER2 treatment resistance. it is found that LINC01235 significantly enhances DNA replication licensing and chromosomal instability, fostering clonal expansion and evolution, and ultimately increasing resistance to therapeutic interventions. LINC01235 regulates global H3K27ac, H3K9ac, and H3K36me3 modifications, promotes H2A.Z expression in regulatory regions, and increases the accessibility of DNA licensing factors to their promoter regions. XRCC5 is identified as a key component for maintaining genomic stability, crucial for LINC01235's role in replication licensing. Furthermore, therapeutic strategies targeting LINC01235, including the use of antisense oligonucleotides or ATR inhibitors, which showed promise in overcoming treatment resistance are explored. These findings underscore the pivotal role of LINC01235 in driving resistance mechanisms and highlight novel avenues for targeted therapies to improve the outcomes of patients with HER2-positive breast cancer.

Retrospective Study to Determine Factors Influencing Outcome in Patients With Human Epidermal Growth Factor Receptor 2-Positive Breast Cancer Receiving Neoadjuvant Chemotherapy

PURPOSE

There are scant data on patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer treated with neoadjuvant therapy (NAT) in real-world settings with limited access to HER2-targeted therapy.

METHODS

This was a retrospective analysis of patients with nonmetastatic, HER2-positive breast cancer treated with NAT between January 2014 and December 2018 to determine factors affecting pathologic complete response (pCR), event-free survival (EFS), and overall survival (OS).

RESULTS

The cohort comprised 1,004 patients with a median age of 47 years, 533 (53.1%) with clinical T3/T4 tumors, 466 (46.4%) with clinical N2/3 status, and 527 (52.5%) with hormone receptor-positive disease. Trastuzumab was given to 528 (52.6%) patients in the neoadjuvant setting and 711 (70.8%) patients in neoadjuvant and/or postoperative settings. pCR was achieved in 226 (22.5%) patients; the 5-year EFS in the whole cohort, pCR group, and no-pCR group was 63.5% (95% CI, 60.36 to 66.63), 86.1% (95% CI, 81.59 to 90.60), and 57% ([95% CI, 53.47 to 60.52]; P < .001), respectively. In multivariable analysis in the full cohort, smaller tumor size (cT1/T2 v cT3/T4), higher grade (III v II), hormone receptor-negative status, and use of neoadjuvant HER2-targeted therapy were significantly associated with higher pCR, and smaller tumor size (cT1/T2 v cT3/T4), lower node involvement (cN0/N1 v cN2/N3), achievement of pCR, and receiving trastuzumab were significantly associated with higher EFS and OS.

CONCLUSION

In a setting with constrained access to HER2-targeted therapy, lower clinical tumor burden and receiving trastuzumab were significantly associated with increased pCR and survival in patients with HER2-positive breast cancer treated with NAT. Efforts should be made to enhance early diagnosis and access to HER2-targeted therapy worldwide.

18F-FDG PET/CT radiomic analysis and artificial intelligence to predict pathological complete response after neoadjuvant chemotherapy in breast cancer patients

PURPOSE

Build machine learning (ML) models able to predict pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients based on conventional and radiomic signatures extracted from baseline [18F]FDG PET/CT.

MATERIAL AND METHODS

Primary tumor and the most significant lymph node metastasis were manually segmented in baseline [18F]FDG PET/CT of 52 newly diagnosed BC patients. Clinical parameters, NAC and conventional semiquantitative PET parameters were collected. The standard of reference considered was surgical pCR after NAC (ypT0;ypN0). Eight-hundred-fifty-four radiomic features (RFts) were extracted from both PET and CT datasets, according to IBSI; robust RFTs were selected. The cohort was split in training (70%) and validation (30%) sets. Four ML Models (Clinical Model, CT Model, PET Model_T and PET Model_T + N) each one with 3 learners (Random Forest (RF), Neural Network and Stochastic Gradient Descendent) were trained and tested using RFts and clinical signatures. PET Models were built considering robust RFTs extracted from either primary tumor alone (PET Model_T) or also including the reference lymph node (PET Model_T + N).

RESULTS

72 pathological uptakes (52 primary BC and 20 lymph node metastasis) at [18F]FDG PET/CT were segmented. pCR occurred in 44.2% cases. Twelve, 46 and 141 robust RFts were selected from CT Model, PET Model_T and PET Model_T + N, respectively. PET Models showed better performance than CT and Clinical Models. The best performances were obtained by the RF algorithm of the PET Model_T + N (AUC = 0.83;CA = 0.74;TP = 78%;TN = 72%).

CONCLUSION

ML models trained on PET/CT radiomic features extracted from primary BC and lymph node metastasis could concur in the prediction of pCR after NAC and improve BC management.

Real-world breast cancer treatment patterns and guideline-concordant treatment completion among Malawian women

PURPOSE

In Sub-Saharan Africa (SSA), resource-stratified guidelines for breast cancer treatment are increasingly recommended, but treatment receipt and outcomes according to these guidelines are underreported. Here, we describe breast cancer treatment patterns by stage and curative-intent guideline-concordant treatment (GCT) receipt among Malawian women.

METHODS

A prospective cohort of breast cancer patients were enrolled from December 2016 to October 2018 at Kamuzu Central Hospital with an assessment of demographics, stage, and treatment received, including neoadjuvant (NAC), adjuvant (AdC) and palliative chemotherapy and breast surgery. Curative-intent GCT was defined as having completed breast surgery and at least 4 cycles of chemotherapy. Overall survival (OS) was calculated using Kaplan Meier methods and odds ratios using logistic regression.

RESULTS

91 patients were included, of whom 13 (14%) presented as stage II, 54 (59%) as stage III, and 24 (26%) as stage IV. Curative treatment was recommended for 65 of 91 (71%) patients, of whom 47 (72%) were initiated on NAC, 14 (22%) on upfront breast surgery, and 4 (6%) received no treatment. Only 63% (41/65) of patients received curative-intent GCT as recommended with non-GCT associated with stage III (vs. stage II) disease (OR 0.10 CI (0.01-0.89)), HIV positivity ((OR 0.25 CI (0.06-0.99)) and hormone receptor (HR) negative/HER2 positive subtype ((OR 0.07 CI (0.01-0.49)). Curative-intent GCT was associated with improved OS (44.1 vs. 23.2 months; p = 0.00) compared to non-GCT.

CONCLUSION

While curative-intent GCT was associated with improved survival in this Malawian cohort, treatment completion rates were suboptimal. Resource-stratified guidelines must be paired with locally relevant, multilevel implementation strategies to target barriers to treatment completion.

Screening and exploration of neoadjuvant "de-escalation" therapy for early breast cancer

Background

Neoadjuvant therapy for breast cancer improves the prognosis of high-risk patients. However, whether pathological completed response (pCR) can be used as a surrogate endpoint for de-escalation therapy in patients who are relatively sensitive to treatment remains to be elucidated.

Methods

We retrospectively reviewed 143 breast cancer patients, with clinical stage (cStage) II-IIIA who received neoadjuvant chemotherapy and achieved pCR in a short time (within 16 weeks) from 2012 to 2022. The prognosis of patients was analysed using the Kaplan-Meier method, Cox proportional hazards regression models to identify independent clinicopathologic factors affecting prognosis.

Results

The median follow-up period was 47 months, the overall 4-year disease-free survival (DFS) and overall survival (OS) were 95.3% and 96.9%, respectively, in 143 patients with pCR after neoadjuvant chemotherapy. The 4-year DFS between the postoperative adjuvant chemotherapy and no adjuvant chemotherapy groups was 76.4% and 95.2%, with a significant statistical difference between both groups (P < 0.05). For HER2-positive (HER2+) and Triple negative breast cancer (TNBC), the addition of targeted therapy or platinum-based drugs had no impact on prognosis. Univariate and multivariate analyses of prognosis showed that only postoperative adjuvant chemotherapy significantly affected prognosis.

Conclusion

Patients with operable cStage II-IIIA breast cancer who achieved pCR after a short period of neoadjuvant chemotherapy have a satisfactory prognosis and may be suitable for chemotherapy "de-escalation." This approach is also a dominant application of neoadjuvant "tailoring therapy."

Comparison of neoadjuvant and adjuvant chemotherapy for operable triple-negative breast cancer before the era of immune checkpoint inhibitors: A retrospective study from the Japanese National Clinical Database-Breast Cancer Registry

BACKGROUND

While neoadjuvant chemotherapy (NAC) is recommended for stage II-III triple-negative breast cancer (TNBC), its equivalence to adjuvant chemotherapy (AdjC) has been questioned based on a retrospective study using the National Cancer Database in the United States, which lacked adjustment for important covariates. Given the unlikelihood of new randomized trials being conducted, well-designed, large-scale, retrospective studies are needed.

PATIENTS AND METHODS

We retrospectively analyzed operable TNBC patients from the Japanese National Clinical Database- Breast Cancer Registry (2012-2016). Inclusion criteria were clinical stage I-IIIB, estrogen receptor (ER) < 10 %, progesterone receptor (PgR) < 10 %, and HER2-negative. We excluded patients with carcinoma in situ, cT4a/T4c/T4d, cN3, cM1, bilateral breast cancer, male, non-epithelial tumor, no chemotherapy, no surgery and no follow-up. Primary and secondary outcomes of overall survival (OS) and recurrence-free survival (RFS) were compared between NAC and AdjC using Cox proportional Hazard regression among the exact matched cohort based on age, BMI, cT, cN, histology, ER/PgR positivity, chemotherapy regimen, breast operative technique, radiotherapy, and institution size.

RESULTS

Among 9,000 AdjC and 5,520 NAC patients, 3,256 matched cases were compared. OS and RFS were significantly worse for patients with NAC (Hazard Ratio 1.45 (95 % confidence interval 1.26-1.68) and 1.33 (1.19-1.49), respectively), particularly in patients <65 years, with stage II-IIIB, and with invasive ductal carcinoma.

CONCLUSION

Patients with NAC had worse prognosis, possibly due to unadjusted confounders. Although the availability of immune checkpoint inhibitors (ICIs) limits the clinical impact, the result could provide supplemental insights for treatment decisions in patients who are not candidates for ICIs.

Treatment Patterns, Trends, and Outcomes of Neoadjuvant Chemotherapy Use Among Patients With Early-Stage Invasive Triple-Negative Breast Cancer

PURPOSE

Triple-negative breast cancer (TNBC) is a clinically aggressive subtype associated with poorer survival outcomes. We examined the patterns and trends in neoadjuvant chemotherapy (NACT) use, pathologic complete response (pCR), and overall survival (OS). Furthermore, we evaluated the association between pCR and OS in a large cohort of patients.

METHODS

Patients aged 18 years and older with stage I-III TNBC diagnosed between 2010 and 2021 were identified in the National Cancer Database. Trends in NACT use, pCR, and OS were assessed using the Cochran-Armitage test for time trends. Multivariable logistic regression was used to evaluate the factors associated with NACT use and pCR. The impact of pCR on OS was examined using a multivariable Cox proportional hazards model with propensity score (PS) adjustment and matching.

RESULTS

The rate of NACT receipt increased from 19.1% to 56.4% (P < .001) between 2010 and 2021. Among those who received NACT, pCR rates increased from 19.6% to 40.3% between 2010 and 2021 (P < .001). Notably, 3- and 5-year OS rates increased among those with residual disease, while OS remained stable among those who achieved a pCR. Compared with non-Hispanic White patients, Black patients were less likely to receive NACT (adjusted odds ratio [aOR], 0.88 [95% CI, 0.85 to 0.91]) or achieve pCR (aOR, 0.90 [95% CI, 0.85 to 0.95]). Among patients treated with NACT, having a pCR was associated with a lower risk of death (adjusted hazard ratio, [aHR], 0.26 [95% CI, 0.24 to 0.29]).

CONCLUSION

The use of NACT among patients with TNBC has dramatically increased in the past decade. Although TNBC is more prevalent in Black patients, they were less likely to be treated with NACT and less likely to achieve a pCR. Further research is needed to elucidate the underlying disparities and advance drug development to enhance outcomes.

Mathematical Modeling to Address Questions in Breast Cancer Screening: An Overview of the Breast Cancer Models of the Cancer Intervention and Surveillance Modeling Network

The National Cancer Institute-funded Cancer Intervention and Surveillance Modeling Network (CISNET) breast cancer mathematical models have been increasingly utilized by policymakers to address breast cancer screening policy decisions and influence clinical practice. These well-established and validated models have a successful track record of use in collaborations spanning over 2 decades. While mathematical modeling is a valuable approach to translate short-term screening performance data into long-term breast cancer outcomes, it is inherently complex and requires numerous inputs to approximate the impacts of breast cancer screening. This review article describes the 6 independently developed CISNET breast cancer models, with a particular focus on how they represent breast cancer screening and estimate the contribution of screening to breast cancer mortality reduction and improvements in life expectancy. We also describe differences in structures and assumptions across the models and how variation in model results can highlight areas of uncertainty. Finally, we offer insight into how the results generated by the models can be used to aid decision-making regarding breast cancer screening policy.

Oncological outcomes of breast-conserving surgery versus mastectomy following neoadjuvant chemotherapy in a contemporary multicenter cohort

To evaluate local recurrence (LR), distant recurrence (DR) and death in non-metastatic patients undergoing breast-conserving surgery (BCS) or mastectomy following current neoadjuvant chemotherapy (NAC) regimens. Patients submitted to NAC in 2013-2023 were evaluated (n = 365; mastectomy: 165; BCS: 200). More mastectomy patients were over 70 years old (12.7% versus 7%; p = 0.02) and had T4b tumors (16.4% versus 4.5%; p = 0.0003), whereas more BCS patients had node-negative axilla (42% versus 31.5%; p = 0.02). After a mean follow-up of 65 months (range: 4-124), LR and DR were similar in the mastectomy and BCS groups (4.8% versus 5.0%; p = 0.95 and 10.9% versus 9%; p = 0.58, respectively). More deaths occurred in the mastectomy group (8.5% versus 3%; p = 0.03). Ten-year LR-free survival was higher in the BCS group (98.5% versus 95%; HR: 3.41; 1.09-10.64; p = 0.03), while 10-year DR-free survival was similar in both groups (91% BCS versus 89% mastectomy, HR: 1.25; 0.65-2.42; p = 0.4). Overall survival was better in the BCS group (97% versus 91.5%; HR: 2.62; 1.06-6.69; p = 0.03). Estimated 10-year disease-free survival, stratified according to tumor stage, showed no significant difference except for T4 disease, for which the risk was greater in the mastectomy group (94.5% versus 81.8%; HR: 2.86, 1.54-5.30, p = 0.0008). In the multivariate analysis, T3/T4 staging (OR: 4.37, 1.03-21.91; p = 0.04) and axillary dissection (OR: 5.11, 1.14-35.52; p = 0.04) were associated with LR in the BCS group. In this cohort of patients receiving contemporary NAC, BCS proved to be a safe alternative to mastectomy following treatment with NAC, even in cases of locally advanced BC.

Long-term outcome for neoadjuvant versus adjuvant chemotherapy in early breast cancer and the prognostic impact of nodal therapy response: A population-based study

INTRODUCTION

Although neoadjuvant systemic treatment for non-metastatic breast cancer has gained ground during the past decade, there is no compelling evidence that it improves overall survival compared to primary tumor resection and adjuvant treatment. At the same time, the approach to responders to neoadjuvant treatment in the axilla is evolving.

MATERIALS AND METHODS

This is a retrospective analysis of a prospectively collected population-based registry. Patients that received neoadjuvant (n = 2126) or adjuvant chemotherapy (n = 4754) for non-metastatic breast cancer during 2007-2020 in the Stockholm-Gotland region, which comprises 25 % of the entire Swedish population, were included. Overall survival of patients treated preoperatively and postoperatively was compared using inverse probability treatment weighting and landmark analysis. The prognostic impact of change between prechemotherapy clinical to postchemotherapy pathologic nodal stage (cN/pN) in women receiving neoadjuvant treatment was investigated.

RESULTS

Median follow-up was 4.93 years. There was no difference in adjusted overall survival between adjuvant (reference) and neoadjuvant treatment in the entire population (HR = 1.38, 95 % CI 0.98-1.93, p = 0.062) or in breast cancer subtypes. Patients converting from positive clinical to negative pathologic nodal stage (cN+/pN0) had improved outcomes compared to cN0/pN0 or patients with pN0 following primary surgery. These patients had a particular disease trajectory, with early peak in risk of death followed by quick and sustained decrease.

CONCLUSION

There was no difference in survival of patients treated with neoadjuvant versus adjuvant systemic therapy for non-metastatic breast cancer. Patients with cN+/pN0 have excellent prognosis and represent potential candidates for de-escalation of local and systemic treatment.

Identifying subgroups of ypN1 breast cancer patients who may exempt from axillary lymph node dissection after neoadjuvant chemotherapy: insights from a large cohort study

BACKGROUND

In patients with breast cancer staged ypN1 after neoadjuvant chemotherapy (NAC), there is limited evidence-based guidance regarding exemption from axillary lymph node dissection (ALND).

METHODS

This study analyzed ypN1 breast cancer patients post-NAC from the Surveillance, Epidemiology, and End Results databases. Patients were categorized into the breast-conserving surgery (BCS) group and the total mastectomy (TM) group, and further divided by the number of positive lymph nodes (LNs). The effects of three axillary management strategies, ALND, sentinel lymph node biopsy combined with radiotherapy (SLNB + RT), and ALND + RT were compared. The overall survival (OS) and breast cancer-specific survival (BCSS) of all subgroups and their independent risk factors were analyzed. Independent prognostic factors selected from multivariate Cox analysis were utilized to create nomograms for predicting OS and BCSS.

RESULTS

A total of 3641 patients were involved, with 1331 in the BCS group and 2310 in the TM group. In the TM group, patients with 3 residual positive LNs exhibited significant improvements in OS and BCSS when treated with ALND + RT. For patients with 1 or 2 residual positive LNs in the TM group and all BCS patients, no significant survival differences in survival outcomes were observed among the three axillary management methods. The accuracy of the nomograms was validated via calibration curves, receiver operating characteristic curves, and decision curve analysis curves.

CONCLUSION

For TM group patients with 3 residual positive LNs after NAC, ALND + RT is recommended. For other subgroups of ypN1 patients, SLNB + RT can be considered an alternative to ALND. The nomogram developed to predict OS and BCSS in ypN1 breast cancer patients demonstrated excellent predictive ability.

Apoptotic breast cancer cells after chemotherapy induce pro-tumour extracellular vesicles via LAP-competent macrophages

Chemotherapy is important in the systemic therapy for breast cancer. However, after chemotherapy, the left living tumour cells are more progressive. There is an urgent need to study the underlying mechanism which is still unclear to further improve the therapeutic efficacy of chemotherapy in breast cancer. Here we find a pro-tumour effect of the apoptotic cells induced by the chemotherapy, which is mediated by a new subset of macrophages undergoing LC3-associated phagocytosis (LAP). By transferring exosomal S100A11 into the living tumour cells after chemotherapy, the macrophage exhibits a more pro-tumour phenotype than classic M2-type macrophages. Moreover, S100A11 binds to IFITM3, inducing Akt phosphorylation of living tumour cells after chemotherapy, which promotes tumour progression. Of note, Akt inhibitor can enhance the therapeutic effcicay of chemotherapy in breast cancer. This study provides a novel mechanistic link between tumour-associated macrophages and breast cancer, uncovering Akt as a potential therapeutic target to improve chemotherapy efficacy.

Assessing neoadjuvant treatment response through serum human epidermal growth factor receptor 2 (HER2) dynamics

Background

Human epidermal growth factor receptor 2 (HER2)-positive invasive breast cancer (BC) accounts for 15-20% of all cases, requiring HER2-targeted neoadjuvant therapy (NAT). Despite the success of trastuzumab and other HER2-targeted treatments, many patients still experience inadequate responses, highlighting the need for more accurate and accessible biomarkers to predict treatment outcomes. Serum HER2 (sHER2) levels, as a non-invasive biomarker, have shown promise in monitoring treatment response; however, the role of sHER2 dynamics during treatment remains underexplored. The aim of this study was to investigate the potential of sHER2 dynamics as a predictor of pathological complete response (pCR) in HER2-positive BC patients undergoing NAT.

Methods

This retrospective study analyzed 120 HER2-positive BC patients who underwent standard NAT followed by surgery at Fudan University Shanghai Cancer Center (FUSCC). sHER2 levels were measured at three time points: baseline, after the second cycle of therapy (C2), and at surgery. Logistic regression analysis was used to assess the association between changes in sHER2 levels and the achievement of pCR. The study also examined the influence of other clinicopathological factors such as estrogen receptor (ER) status, Ki67, and tissue HER2 (tHER2) levels on pCR.

Results

During NAT, sHER2 levels showed a significant decline, with a more pronounced reduction observed in patients achieving pCR. The greatest reduction in sHER2 levels after C2 was strongly associated with pCR. Both univariate and multivariate analyses identified significant reductions in sHER2 levels after C2 and ER-negative status as independent predictors of pCR. Notably, sHER2 changes from baseline to C2 demonstrated a stronger predictive value for pCR compared to changes observed later in treatment.

Conclusions

Our study confirms that reductions in sHER2 levels after C2 are a strong indicator of favorable treatment response in HER2-positive BC patients undergoing NAT. Monitoring sHER2 dynamics early in treatment can serve as a useful, non-invasive biomarker to predict pCR and may guide therapeutic decisions in clinical practice.

Influence of histopathological changes after neoadjuvant chemotherapy on the survival of breast cancer patients

INTRODUCTION

Neoadjuvant chemotherapy (NACT) is an established form of therapy for early breast cancer (BC). The aim of our study was to analyze histopathological parameters before and after receiving NACT and to determine the influence of these changes on prognosis of BC patients.

MATERIAL AND METHODS

We retrospectively analyzed data of patients with primary early BC, diagnosed between January 2012 and December 2019, and NACT, followed by primary surgery. Patients achieving pathological complete response (pCR) were excluded. For the outcome analysis, disease-free survival (DFS) and overall survival (OS) were defined.

RESULTS

A total of 237 tumors were analyzed in the study. The conversion rates of tumor grade, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), Ki67 status, and BC subtype were 34.6 %, 3.4 %, 14.3 %, 4.6 %, 30.0 %, and 28.7 %, respectively. After a median follow-up of 58.03 months, we found an association between consistently negative ER/PR with the worst prognosis (DFS and OS) (ER p < 0.0001 for both; PR p = 0.0003, p = 0.0004, respectively). The conversion from Ki67 ≥14 % to <14 % led to an improved outcome compared to a constant Ki67 ≥14 % (DFS p = 0.003, OS p = 0.001). Tumor residuals with a non-triple-negative (nTN) subtype (TN → nTN) showed a better prognosis than those with TN subtype (nTN → TN) (DFS and OS p < 0.0001).

CONCLUSIONS

After NACT, tumor grade and Ki67 showed the highest conversion rates between primary biopsy and tumor residual. Depending on changes in ER, PR, Ki67, and subtype, we found significant differences in the prognosis of the patients.

Superior Survival and Lower Recurrence Outcomes with Breast-Conserving Surgery Compared to Mastectomy Following Neoadjuvant Therapy in 607 Breast Cancer Patients

BACKGROUNDS

Neoadjuvant therapy (NAT) is a cornerstone in the management of breast cancer (BC), enabling tumor downstaging and improved surgical options.

METHODS

This study retrospectively analyzed 607 BC patients treated with NAT and surgery at IRCCS Humanitas Research Hospital, Milan, Italy, to compare long-term oncologic outcomes of breast-conserving surgery (BCS) versus mastectomy. Patient demographics, tumor characteristics, and treatment details were analyzed using descriptive statistics, logistic regression, and Cox proportional hazards models.

RESULTS

Of the 607 patients, 54.7% underwent BCS, and 45.3% had mastectomy. BCS was associated with significantly superior 10-year outcomes compared to mastectomy, including disease-free survival (DFS, 75.2% vs. 71.1%, p = 0.001), distant DFS (75.2% vs. 71.1%, p = 0.001), overall survival (OS, 82.9% vs. 78.1%, p = 0.002), and BC-specific survival (BCSS, 87.7% vs. 83.1%, p = 0.001). Pathologic complete response (pCR) emerged as a protective factor across all endpoints, while mastectomy was independently associated with worse BCSS (HR: 2.068, 95% CI: 1.016-4.210, p = 0.045).

CONCLUSIONS

Our findings demonstrate the oncologic safety and potential superiority of BCS over mastectomy in NAT-treated BC patients, highlighting the importance of individualized surgical decision-making to optimize survival outcomes.

Retesting of oestrogen receptor, progesterone receptor and HER2 status of invasive carcinoma of the breast after neoadjuvant chemotherapy

AIMS

There is no consensus on whether oestrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) status should be assessed after neoadjuvant chemotherapy. This study assessed the frequency of changes in ER, PR and HER2 status after neoadjuvant chemotherapy.

METHODS AND RESULTS

Of 353 patients who had neoadjuvant chemotherapy and anti-HER2 treatment, receptors were assessed in 185 residual carcinomas. Eight per cent of carcinomas that were ER-negative in the core biopsy were ER-positive in the excision compared with 1.5% of controls. All were HER2-positive in the core biopsy and 23% were HER2-negative in the excision compared with 0% of controls. Controls were cases tested in the core biopsy and subsequent surgical resection with no neoadjuvant treatment. Of 589 patients who had neoadjuvant chemotherapy alone, receptors were assessed in 495 residual carcinomas. Six per cent of carcinomas that were ER-negative in the core biopsy were ER-positive in the excision (mainly ER-low positive) compared with 1.5% of controls. All were HER2-negative in the core biopsy and 6% were HER2-positive in the excision (mainly immunohistochemistry score 2+ and HER2 gene amplified) compared with 2% of controls.

CONCLUSIONS

Negative to positive changes in receptor status after neoadjuvant chemotherapy are infrequent and the positive result in the excision is often weakly positive. These results imply that repeat assessment after neoadjuvant chemotherapy and surgery could influence the subsequent treatment in a small proportion of patients.

Can residual proliferative cancer burden predict long-term outcomes following neoadjuvant chemotherapy in breast cancer?

Residual proliferative cancer burden (RPCB) has been suggested as a strong predictor model of long-term outcomes in breast cancer undergoing neoadjuvant chemotherapy (NACT). In our study, we aimed to compare the prognostic value of multiple post-NACT classifications for assessing residual disease. Archival surgical specimens of 97 patients with primary breast cancer who underwent NACT were evaluated for residual cancer burden (RCB). The post-operative Ki-67 proliferation index was quantified using immunohistochemistry on post-treatment surgical excision specimens with residual disease. Then, we calculated the RPCB scores by combining the anatomical RCB index with the biological post-therapeutic Ki-67 using the Cox proportional hazard model for each parameter. Using the Kaplan-Meier method, RCBIII showed an unfavourable prognosis with worse relapse-free survival (RFS) (estimated 5-year RFS rate of 38%) than RCBI, which displayed a similarly good prognosis as pathological complete response (equal to RCB0) (estimated 5-year RFS rates of 80% and 100%, respectively) (p=0.012). The RCBII showed an intermediate prognosis (estimated 5-year RFS rate of 79%). A higher post-NACT Ki-67 (greater than cut-off 20%) had a negative impact on the overall survival and RFS (p<0.0001 for both) using the Kaplan-Meier method. In multivariate analysis, the histological residual tumour size, number of affected lymph nodes, and RCB index remained independent prognostic factors for RFS. In addition, RPCBIII showed the worst prognosis (with an estimated 5-year RFS rate of 38%) compared to RPCBI (estimated 5-year RFS rate of 83%) (p=0.039) by the Kaplan-Meier method. The area under the curve of the RCB index was 0.82 compared to 0.62 for the RPCB model in terms of RFS prediction. Our study highlighted the potential stratification of RCBII cases based on the RPCB classification. Further studies with larger cohorts will be needed to validate whether the RCPB adds value to residual disease assessment.

Combined morphology and radiomics of intravoxel incoherent movement as a predictive model for the pathologic complete response before neoadjuvant chemotherapy in patients with breast cancer

Background

To develop a predictive model using baseline imaging of morphology and radiomics derived from intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) to determine the pathologic complete response (pCR) to neoadjuvant chemotherapy (NACT) in breast cancer patients.

Methods

A total of 265 patients who underwent 3.0 T MRI scans before NACT were examined. Among them, 113 female patients with stage II-III breast cancer were included. The training data set consisted of 79 patients (31/48=pCR/Non-PCR, npCR), while the remaining 34 cases formed the validation cohort (13/21=pCR/npCR). Radiomics and conventional magnetic resonance imaging features analysis were performed. To build a nomogram model that integrates the radiomics signature and conventional imaging, a logistic regression method was employed. The performance evaluation of the nomogram involved the area under the receiver operating characteristic curve (AUC), a decision curve analysis, and the calibration slope.

Results

In an assessment for predicting pCR, the radiomics model displayed an AUC of 0.778 and 0.703 for the training and testing cohorts, respectively. Conversely, the morphology model exhibited an AUC of 0.721 and 0.795 for the training and testing cohorts, respectively. The nomogram displayed superior predictive discrimination with an AUC of 0.862 for the training cohort and 0.861 for the testing cohort. Decision curve analyses indicated that the nomogram provided the highest clinical net benefit.

Conclusion

Performing a nomogram consisting of integrated morphology and radiomics assessment using IVIM-DWI before NACT enables effective prediction of pCR in breast cancer. This predictive model therefore can facilitate medical professionals in making individualized treatment decisions.

Accessible model predicts response in hormone receptor positive HER2 negative breast cancer receiving neoadjuvant chemotherapy

Hormone receptor-positive/HER2-negative breast cancer (BC) is the most common subtype of BC and typically occurs as an early, operable disease. In patients receiving neoadjuvant chemotherapy (NACT), pathological complete response (pCR) is rare and multiple efforts have been made to predict disease recurrence. We developed a framework to predict pCR using clinicopathological characteristics widely available at diagnosis. The machine learning (ML) models were trained to predict pCR (n = 463), evaluated in an internal validation cohort (n = 109) and validated in an external validation cohort (n = 151). The best model was an Elastic Net, which achieved an area under the curve (AUC) of respectively 0.86 and 0.81. Our results highlight how simpler models using few input variables can be as valuable as more complex ML architectures. Our model is freely available and can be used to enhance the stratification of BC patients receiving NACT, providing a framework for the development of risk-adapted clinical trials.

Label-free discrimination analysis of breast cancer tumor and adjacent tissues of patients after neoadjuvant treatment using Raman spectroscopy: a diagnostic study

BACKGROUND AND OBJECTIVE

Breast-conserving surgery (BCS) plays a crucial role in breast cancer treatment, with a primary focus on ensuring cancer-free surgical margins, particularly for patients undergoing neoadjuvant treatment. After neoadjuvant treatment, tumor regression can complicate the differentiation between breast cancer tumor and adjacent tissues. Raman spectroscopy, as a rapid and non-invasive optical technique, offers the advantage of providing detailed biochemical information and molecular signatures of internal molecular components in tissue samples. Despite its potential, there is currently no research on using label-free Raman spectroscopy to distinguish between breast cancer tumors and adjacent tissues after neoadjuvant treatment. This study intends to distinguish between tumor and adjacent tissues after neoadjuvant treatment in breast cancer through label-free Raman spectroscopy.

METHODS

In this study, the intraoperative frozen samples of breast cancer tumor and adjacent tissue were collected from patients who underwent neoadjuvant treatment during surgery. The samples were examined using Raman confocal microscopy, and Raman spectra were collected by LabSpec6 software. Spectra were preprocessed by Savitz-Golay filter, adaptive iterative reweighted penalized least squares and MinMax normalization method. The differences in Raman spectra between breast cancer tumor and adjacent tissues after neoadjuvant treatment were analyzed by Wilcoxon rank-sum test, with a Bonferroni correction for multiple comparisons. Based on the support vector machine (SVM) method in machine learning, a predictive model for classification was established in the total group and subgroups of different hormone receptor (HR) status, human epidermal growth factor receptor 2 (HER2) status and Ki-67 expression level. The independent test set was used to evaluate the performance of the model, and the area under curve (AUC) of the receiver operating characteristic (ROC) curve, sensitivity, specificity and accuracy of different models were obtained.

RESULT

This study comprised 4260 Raman spectra of breast cancer tumor and adjacent frozen tissue samples from 142 breast cancer patients treated with neoadjuvant treatment. The Raman peaks associated with nucleotides and their metabolites in the Raman spectra of breast cancer tumor tissues were higher in intensities than those of adjacent tissues after neoadjuvant therapy (676 cm -1 : Bonferroni adjusted P < 0.0001; 724 cm -1 : P < 0.0001; 754 cm -1 : P < 0.0001), and the Raman peaks from amide III bands were more intense (1271 cm -1 : P < 0.01). Multivariate curve resolution-alternating least squares (MCR-ALS) decomposition of Raman spectra revealed reduced lipid content and increased collagen and nucleic acid content in breast cancer tumor tissues compared to adjacent tissues following neoadjuvant therapy. The predictive model based on the Raman spectral signature of breast cancer tumor and adjacent tissues after neoadjuvant treatment achieved an AUC of 0.98, with accuracy, sensitivity, and specificity values of 0.89, 0.97, and 0.83, respectively. The AUC of subgroup analysis according to different status of molecular pathological biomarkers was stably around 99%.

CONCLUSION

This study demonstrated that label-free Raman spectroscopy can differentiate tumor and adjacent tissues of breast cancer patients treated with neoadjuvant therapy thorough getting the panoramic perspective of the biochemical compounds for the first time. Our study provided a novel technique for determining the margin status in BCS in breast cancer following neoadjuvant treatment rapidly and precisely.

The analysis of transcriptomic signature of TNBC-searching for the potential RNA-based predictive biomarkers to determine the chemotherapy sensitivity

Neoadjuvant chemotherapy is the foundation treatment for triple-negative breast cancer (TNBC) and frequently results in pathological complete response (pCR). However, there are large differences in clinical response and survival after neoadjuvant chemotherapy of TNBC patients. The aim was to identify genes whose expression significantly associates with the efficacy of neoadjuvant chemotherapy in patients with TNBC. Transcriptomes of 46 formalin-fixed paraffin-embedded (FFPE) tumor samples from TNBC patients were analyzed by RNA-seq by comparing 26 TNBCs with pCR versus 20 TNBCs with pathological partial remission (pPR). Subsequently, we narrowed down the list of genes to those that strongly correlated with drug sensitivity of 63 breast cancer cell lines based on Dependency Map Consortium data re-analysis. Furthermore, the list of genes was limited to those presenting specific expression in breast tumor cells as revealed in three large published single-cell RNA-seq breast cancer datasets. Finally, we analyzed which of the selected genes were significantly associated with overall survival (OS) in TNBC TCGA dataset. A total of 105 genes were significantly differentially expressed in comparison between pPR versus pCR. As revealed by PLSR analysis in breast cancer cell lines, out of 105 deregulated genes, 42 were associated with sensitivity to docetaxel, doxorubicin, paclitaxel, and/or cyclophosphamide. We found that 24 out of 42 sensitivity-associated genes displayed intermediate or strong expression in breast malignant cells using single-cell RNAseq re-analysis. Finally, 10 out of 24 genes were significantly associated with overall survival in TNBC TCGA dataset. Our RNA-seq-based findings suggest that there might be transcriptomic signature consisted of 24 genes specifically expressed in tumor malignant cells for predicting neoadjuvant response in FFPE samples from TNBC patients prior to treatment initiation. Additionally, nine out of 24 genes were potential survival predictors in TNBC. This group of 24 genes should be further investigated for its potential to be translated into a predictive test(s).

Enhancing breast cancer surgery outcomes: A comprehensive review of oncoplastic techniques, surgical planning, and aesthetic considerations

Breast cancer is one of the most common types of cancer among women in Western countries. Historically treated with radical and modified radical surgeries, breast cancer is now primarily managed with breast-conserving surgery combined with postsurgical radiotherapy. Oncoplastic breast surgery, a technique that integrates aesthetic breast reduction methods with cancer surgery, has been developed as a tumor-specific approach to facilitate breast conservation while removing the tumor. This method allows for higher excision volumes with minimal aesthetic compromise. The main components of oncoplastic surgery are volume displacement and volume replacement techniques. This review discusses the essential role of oncoplastic techniques in breast-conserving surgery (BCS), which has evolved into the standard of care for early-stage breast cancer. Understanding these techniques is critical for all breast surgeons to optimize both aesthetic and oncologic outcomes.

Assessment of quality of life, pain, depression, and body-image in breast cancer patients in neoadjuvant therapy

Breast cancer is the leading cancer type among women globally, and its chemotherapy often results in multiple side effects, compromising the patient's quality of life. Our study aimed to analyze the impact of neoadjuvant chemotherapy on the quality of life in Brazilian women with breast cancer within the public health system. This research was a one-year, observational, longitudinal study, conducted at a charitable health facility, examining the effect of neoadjuvant chemotherapy on these women's quality of life. Sociodemographic and clinical data were extracted from medical records. Quality of life parameters were gauged using Portuguese-validated questionnaires: EORTC.QLQ - C30 version 3.0, EORTC.BR-23, Body Image Scale (BIS), BPI-SF pain scale, and Beck Depression Inventory (BDI). These tools were utilized at three intervals: before the start of systemic treatment, after three months (before initiating paclitaxel), and upon concluding neoadjuvant therapy. Qualitative variables were tested for normality using the Kolmogorov-Smirnov test. As the continuous variables referring to the questionnaires did not show normal distribution, non-parametric tests were used: Friedman tests for paired pairs, and Wilcoxon and Mann-Whitney tests for multiple comparisons. In all tests, the significance level adopted was 5%. The software used for the analysis was SPSS. Our findings revealed a decline in quality of life, observing deterioration in the role, social, and cognitive functioning domains. Additionally, symptoms like fatigue, hyporexia, constipation, and diarrhea became more pronounced during the treatment. The presence of minimal depressive symptoms, associated with systemic therapy side effects also contributed to this worsening. Notably, there were no improvements in any quality of life-related parameters, and no discernible differences were observed in pain levels or body image across the evaluated periods.

Association between mammographic breast density and outcome in patients with unilateral invasive breast cancer receiving neoadjuvant chemotherapy

PURPOSE

To analyze the relationship between mammographic breast density and tumor response and outcome at follow-up, in terms of overall survival (OS) and disease-free survival (DFS), in patients with unilateral invasive breast cancer receiving neoadjuvant chemotherapy (NACT).

METHODS

A total of 228 women (mean age, 47.6 years ± 10 [SD]; range: 24-74 years) with invasive breast cancer who underwent NACT were included in this observational retrospective study. Clinical, radiological and histopatological data were retrieved. Categorization of breast density was performed by two radiologists in consensus on mammography acquired at the time of diagnosis according to BI-RADS categories. Association between density categories and tumor response was analyzed in the overall population and in subgroups defined by menopausal status, tumor phenotype and stage at diagnosis. Kaplan-Meier (KM) curves were used to estimate the OS and DFS probabilities. Subgroup analyses based on menopausal status and tumor phenotype were performed.

RESULTS

A total of 30 patients (13.2%) achieved pathological complete response (pCR). No association between density categories and pCR was found (P = 0.973), even at subgroups analysis. The median follow-up time was 92 months. Patients with dense breast showed the longest DFS (P = 0.0094), results confirmed in premenopausal patients (P = 0.0024) and in triple negative breast cancers (P = 0.0292). Density category did not show a statistically significant association with OS.

CONCLUSION

Breast cancer patients receiving NACT with extremely dense breasts showed better DFS. No evidence of breast density as a predictive marker for complete pathological response or as a prognostic factor in terms of OS was found.

Understanding cellular proliferation activity in breast cancer using multi-compartment model of transverse relaxation time mapping on 3T MRI

Introduction

Precise understanding of proliferative activity in breast cancer holds significant value in the monitoring of neoadjuvant treatment, while current immunostaining of Ki-67 from biopsy or resected tumour suffers from partial sampling error. Multi-compartment model of transverse relaxation time has been proposed to differentiate intra- and extra-cellular space and biochemical environment but susceptible to noise, with recent development of Bayesian algorithm suggested to improve robustness. We hence hypothesise that intra- and extra-cellular transverse relaxation times using Bayesian algorithm might be sensitive to proliferative activity.

Materials and methods

Twenty whole tumour specimens freshly excised from patients with invasive ductal carcinoma were scanned on a 3 T clinical scanner. The overall transverse relaxation time was computed using a single-compartment model with the non-linear least squares algorithm, while intra- and extra-cellular transverse relaxation times were computed using a multi-compartment model with the Bayesian algorithm. Immunostaining of Ki-67 was conducted, yielding 9 and 11 cases with high and low proliferating activities respectively.

Results

For single-compartment model, there was a significant higher overall transverse relaxation time (p = 0.031) in high (83.55 ± 7.38 ms) against low (73.30 ± 11.30 ms) proliferating tumours. For multi-compartment model, there was a significant higher intra-cellular transverse relaxation time (p = 0.047) in high (73.52 ± 10.92 ms) against low (61.30 ± 14.01 ms) proliferating tumours. There was no significant difference in extra-cellular transverse relaxation time (p = 0.203) between high and low proliferating tumours.

Conclusions

Overall and Bayesian intra-cellular transverse relaxation times are associated with proliferative activities in breast tumours, potentially serving as a non-invasive imaging marker for neoadjuvant treatment monitoring.

Clinico-pathological features predicting indication to mastectomy in breast cancer patients achieving complete response after neoadjuvant therapy: A retrospective analysis of the EUSOMA database

AIMS

We investigated factors related to the type of surgery, i.e. mastectomy versus breast conserving surgery (BCS), in breast cancer (BC) patients with complete pathologic response in the breast (ypT0) after neoadjuvant therapy (NAT).

METHODS

A retrospective analysis from the EUSOMA database was performed using data from 55 certified centers across 14 European countries, including ypT0 BC patients (i.e., neither invasive nor in situ residuals), treated between 2017 and 2022. Variables analyzed included year of surgery, age, number and distribution of tumor focality, extent, clinical and pathological stages, and biologic subtype. Logistic regression was used to identify predictors of surgical choice. The Kaplan-Meier method was used for comparison of local recurrence-free survival (LRFS) between surgical groups.

RESULTS

Of 1416 BC patients included, 67.5 % underwent BCS and 32.5 % mastectomy. At multivariable analysis, factors increasing the likelihood of mastectomy included: more recent year of surgery [odds ratio (OR) 2.61, 95 % confidence interval (95%CI): 1.51-4.51,p = 0.001], younger age (OR: 0.96, 95%CI: 0.95-0.97,p < 0.001), multifocality (OR: 2.20, 95%CI: 1.61-3.00,p < 0.001) and multicentricity (OR: 12.66, 95%CI: 6.82-23.49,p < 0.001), advanced clinical tumor stage (OR: 14.54, 95%CI: 5.80-36.47,p < 0.001), and baseline axillary nodal involvement (OR: 1.56, 95%CI: 1.12-2.17,p = 0.009). Comparison between groups did not show a significant difference in LRFS (p = 0.389).

CONCLUSION

Many BC patients undergo mastectomy despite achieving complete response of primary tumor after NAT. Patients-related and tumor-related features, as well as having surgery in more recent years, seems to influence this choice. Our findings suggest the need for an optimized decision-making to spare unnecessary mastectomies.

Comparing survival outcomes between neoadjuvant and adjuvant chemotherapy within hormone receptor-positive, human epidermal growth factor receptor 2-negative early breast cancer among young women (≤35): a retrospective cohort study based on SEER database and TJMUCH registry

Breast cancer is a leading cause of cancer morbidity and mortality among young women, who often experience more aggressive disease, which may impact their treatment responses and long-term prognoses. Understanding the effectiveness of neoadjuvant chemotherapy (NAC) versus adjuvant chemotherapy (AC) in this specific population is critical for optimizing treatment strategies and improving prognoses. This research was conducted to compare the prognoses of young women (≤35 years old) with early-stage hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative breast cancer, who were treated with NAC versus those treated with AC. This study retrospectively analyzed data from young women with HR+/HER2- breast cancer, with complete follow-up information, sourced from the Surveillance, Epidemiology, and End Results (SEER) database (2010-2018) and the Tianjin Medical University Cancer Institute and Hospital (TJMUCH) (2014-2018). Patients from both cohorts were allocated to NAC and AC groups based on their treatment regimens. Categorical variables were compared using chi-square, whereas the Kaplan-Meier method was utilized to generate survival curves; additionally, the log-rank test was employed for survival analysis. Propensity score matching (PSM) was employed to control baseline differences. Analysis of the SEER and TJMUCH cohorts revealed that patients treated with NAC had significantly worse overall survival (OS) compared to those treated with AC, as indicated by Kaplan-Meier curves both before and after PSM. The disease-free survival analysis of the TJMUCH cohort yielded similar results, indicating that patients treated with AC experienced longer periods without disease recurrence compared to their counterparts receiving NAC. Statistically significant differences were observed across both survival metrics, reinforcing the robustness of our findings. Overall, among young women (≤35 years old) with early-stage HR+/HER2- breast cancer, patients treated with AC exhibited a more favorable prognosis and improved survival outcomes compared to those treated with NAC. These findings could potentially influence clinical decision-making and treatment guidelines, advocating for a more tailored approach in managing young women with HR+/HER2- breast cancer.

Prediction of pathological complete response after neoadjuvant chemotherapy for HER2-negative breast cancer patients with routine immunohistochemical markers

BACKGROUND

Pathological complete response (pCR) is an established surrogate marker for prognosis in patients with breast cancer (BC) after neoadjuvant chemotherapy. Individualized pCR prediction based on clinical information available at biopsy, particularly immunohistochemical (IHC) markers, may help identify patients who could benefit from preoperative chemotherapy.

METHODS

Data from patients with HER2-negative BC who underwent neoadjuvant chemotherapy from 2002 to 2020 (n = 1166) were used to develop multivariable prediction models to estimate the probability of pCR (pCR-prob). The most precise model identified using cross-validation was implemented in an online calculator and a nomogram. Associations among pCR-prob, prognostic IHC3 distant recurrence and disease-free survival were studied using Cox regression and Kaplan-Meier analyses. The model's utility was further evaluated in independent external validation cohorts.

RESULTS

273 patients (23.4%) achieved a pCR. The most precise model had across-validated area under the curve (AUC) of 0.84, sensitivity of 0.82, and specificity of 0.71. External validation yielded AUCs between 0.75 (95% CI, 0.70-0.81) and 0.83 (95% CI, 0.78-0.87). The higher the pCR-prob, the greater the prognostic impact of pCR status (presence/absence): hazard ratios decreased from 0.55 (95% central range, 0.07-1.77) at 0% to 0.20 (0.11-0.31) at 50% pCR-prob. Combining pCR-prob and IHC3 score further improved the precision of disease-free survival prognosis.

CONCLUSIONS

A pCR prediction model for neoadjuvant therapy decision-making was established. Combining pCR and recurrence prediction allows identification of not only patients who benefit most from neoadjuvant chemotherapy, but also patients with a very unfavorable prognosis for whom alternative treatment strategies should be considered.

Efficacy and safety of ondansetron orally soluble pellicle for preventing moderate- to high-emetic risk chemotherapy-induced nausea and vomiting

OBJECTIVE

Ondansetron orally soluble pellicle can serve as an alternative option for preventing nausea and vomiting in patients who receive chemotherapy. However, there is a lack of clinical evidence regarding ondansetron. This study aimed to explore the efficacy and safety of ondansetron in patients with malignant tumours who received chemotherapy drugs with a moderate-to-high emetic risk.

METHODS

In total, 163 patients with malignant tumours received 24 mg of ondansetron via orally soluble pellicles at 30 min before chemotherapy (8 mg each time for three consecutive administrations). The incidence rates of nausea and vomiting in the three days after chemotherapy were recorded.

RESULTS

Regarding the effect of ondansetron on vomiting, the complete response (zero episodes of vomiting), major response (1-2 episodes of vomiting), minor response (3-5 episodes of vomiting), and failure (> 5 episodes of vomiting) rates were 96.9%, 1.2%, 1.2%, and 0%, respectively. The major efficacy rate for vomiting (complete response + major response rates) was 98.1%. Moreover, 96.3% of patients did not experience nausea, 2.5% of patients experienced mild nausea, 1.2% of patients experienced moderate nausea, and 0.0% of patients experienced severe nausea. The major efficacy rate for nausea (no nausea) was 96.3%. Age > 65 years was negatively associated with major efficacy for vomiting, and a chemotherapy regimen involving cisplatin was negatively associated with major efficacy for nausea. A total of 42 (25.8%) patients experienced adverse events. The most common adverse events were elevated levels of alanine transaminase (6.7%), elevated levels of aspartate transaminase (3.7%), fatigue (3.7%), and cough (2.5%).

CONCLUSION

Ondansetron orally soluble pellicle shows good antiemetic efficacy and high safety in patients with malignant tumours who receive chemotherapy drugs with a moderate-to-high emetic risk.

Prognosis of patients with breast cancer who underwent breast-conserving surgery using a 3D-printed surgical guide after neoadjuvant chemotherapy

In breast-conserving surgery (BCS), clear resection margins are crucial to prevent recurrence. Accurate imaging is vital for precise BCS, with MRI being the most accurate. However, MRI has limitations in identifying the exact extent of breast cancer in patients who have undergone neoadjuvant chemotherapy (NACT). A 3D-Printed Breast Surgical Guide (3DP-BSG) can address this issue by effectively pinpointing cancer extent in NACT patients, thus enhancing surgical accuracy. This retrospective single-institution cohort study focused on female patients diagnosed with invasive breast cancer who underwent NACT. Between November 2015 and October 2021, patients received BCS with the aid of a 3DP-BSG. Personalized 3DP-BSG targeted tumors by tracking changes in breast and tumor anatomy on MRI before and after NACT. 203 patients with invasive breast cancer were enrolled in the study. According to exclusion criteria, 197 patients were analyzed. The median follow-up period was 35.3 months (range: 2.2-96.8 months). 3 patients (1.5%) had positive resection margins. During the follow-up period, 17 patients (8.6%) experienced recurrence, with one patient (0.5%) confirmed local recurrences. The application of MRI-based 3DP-BSG is effective in achieving low positive margins and local recurrence in patients undergoing BCS after NACT, offering a promising approach for improving surgical outcomes.

Dual-layer detector spectral computed tomography quantitative parameters for predicting pathological complete remission after neoadjuvant treatment of breast cancer

Background

Breast cancer (BC) is a common cancer among women worldwide, and although the use of neoadjuvant therapy (NAT) for BC has become more widespread, there is no standardized prediction of the efficacy of NAT for BC. This study aimed to evaluate the value of quantitative parameters of dual-layer detector spectral computed tomography (DLCT) in predicting whether BC patients can achieve pathological complete response (pCR) after NAT.

Methods

Patients who were first diagnosed with BC in Shandong Cancer Hospital and Institute and received only NAT before surgery were selected for participation in this study. All breast computed tomography (CT) imaging examinations were performed using DLCT, within 1 week before initiating NAT. The gold standard for evaluating the effect of NAT is pathologic response established at surgery. The Miller-Payne grading system was applied to assess the response to NAT. Quantitative parameters were extracted from DLCT, including CT value, normalized CT value, iodine concentration (IC), normalized iodine concentration (NIC), the slope of the spectral Hounsfield unit (HU) curve, effective atomic number, and the normalized effective atomic number. The Mann-Whitney U test was used to compare the distribution differences of DLCT quantitative parameters between the pCR group and the non-pCR group. The diagnostic performance of the quantitative parameters was analyzed by receiver operating characteristic curve.

Results

In the neoadjuvant chemotherapy group (n=80), compared with the non-pCR group, the slope of the spectral HU curve, IC, effective atomic number, and NIC of arterial phase in the pCR group were higher, and the difference was statistically significant (P<0.05); area under the curve (AUC): 0.768, 0.791, 0.834, and 0.770, respectively. In the neoadjuvant targeted therapy group (n=40), compared with the pCR group, the CT value, IC, effective atomic number, and NIC of the arterial phase in the non-pCR group were higher, and the difference was statistically significant (P<0.05); AUC: 0.844, 0.813, 0.802, and 0.766, respectively. There was no significant difference (P>0.05) in DLCT venous phase quantitative parameters between pCR and non-pCR in 70 patients treated with NAT.

Conclusions

The study suggested a possibility that DLCT provided a potential tool to develop a model for predicting pCR to NAT in BC.

Estrogen Signaling in Early-Stage Breast Cancer: Impact on Neoadjuvant Chemotherapy and Immunotherapy

Neoadjuvant chemoimmunotherapy (NACIT) has been shown to improve pathologic complete response (pCR) rates and survival outcomes in stage II-III triple-negative breast cancer (TNBC). Promising pCR rate improvements have also been documented for selected patients with estrogen receptor-positive (ER+) human epidermal growth factor receptor 2-negative (HER2-) breast cancer (BC). However, one size does not fit all and predicting which patients will benefit from NACIT remains challenging. Accurate predictions would be useful to minimize immune-related toxicity, which can be severe, irreversible, and potentially impact fertility and quality of life, and to identify patients in need of alternative treatments. This review aims to capitalize on the existing translational and clinical evidence on predictors of treatment response in patients with early-stage BC treated with neoadjuvant chemotherapy (NACT) and NACIT. It summarizes evidence suggesting that NACT/NACIT effectiveness may correlate with pre-treatment tumor characteristics, including mutational profiles, ER expression and signaling, immune cell presence and spatial organization, specific gene signatures, and the levels of proliferating versus quiescent cancer cells. However, the predominantly qualitative and descriptive nature of many studies highlights the challenges in integrating various potential response determinants into a validated, comprehensive, and multimodal predictive model. The potential of novel multi-modal approaches, such as those based on artificial intelligence, to overcome current challenges remains unclear, as these tools are not free from bias and shortcut learning. Despite these limitations, the rapid evolution of these technologies, coupled with further efforts in basic and translational research, holds promise for improving treatment outcome predictions in early HER2- BC.

Oncologic and cosmetic outcomes of oncoplastic breast-conserving surgery after neoadjuvant systemic therapy: systematic review and meta-analysis

PURPOSE

Oncoplastic breast-conserving surgery (OBCS) prevents compromise of breast aesthetics following large breast cancer excisions. This systematic review was conducted to investigate the outcomes (oncologic, surgical, cosmetic) of OBCS versus standard breast-conserving surgery (SBCS) and mastectomy post-neo-adjuvant systemic therapy.

METHODS

Ovid, Web of Science, Cochrane, ClinicalTrials.gov databases were searched up to 24/08/2024. English language peer-reviewed RCTs or observational/cohort studies with ≥ 18-year-old women treated for breast cancer with neoadjuvant chemotherapy (NACT) and/or hormonal therapy comparing OBCS to SBCS and/or mastectomy were included. Of 6794 articles, 32 underwent full-text assessment and eleven met the inclusion criteria. The review was conducted using PRISMA guidelines. Two reviewers independently extracted data and assessed risk of bias (Newcastle-Ottowa Scale). Meta-analysis using a random-effects model were performed where data allowed.

RESULTS

Eleven cohort studies (n = 4594) included OBCS (n = 912), SBCS (n = 1122) and mastectomy (n = 2560) after NACT. Post-NACT tumour size was 20(9-44) mm, 13(0-23)mm [SMD 0.62, 95%CI(-0.24,1.48), p = 0.16] and 20(10-31)mm [SMD 0.05, 95%CI(-0.53,0.63), p = 0.86] in the OBCS, SBCS and mastectomy groups respectively. The margin re-excision rate was significantly lower in OBCS than in SBCS [2.9%(0-11.1%) vs. 6.1%(0-18.5%); OR 0.35, 95%CI(0.15,0.80), p = 0.01]. All other oncologic outcomes, including positive margin rate, and overall survival, were not statistically different between the groups. Cosmetic outcomes and patient-reported outcome measures were marginally in favour of OBCS [OBCS 50-66% vs SBCS 37.6-55% very satisfied].

CONCLUSION

OBCS after NACT appears oncologically safe and a potential alternative in patients with partial or poor tumour response to NACT. Further studies are required, directly comparing well-matched OBCS with SBCS and mastectomy patients after NACT.

Dynamic ultrasound-based modeling predictive of response to neoadjuvant chemotherapy in patients with early breast cancer

Early prediction of patient responses to neoadjuvant chemotherapy (NACT) is essential for the precision treatment of early breast cancer (EBC). Therefore, this study aims to noninvasively and early predict pathological complete response (pCR). We used dynamic ultrasound (US) imaging changes acquired during NACT, along with clinicopathological features, to create a nomogram and construct a machine learning model. This retrospective study included 304 EBC patients recruited from multiple centers. All enrollees had completed NACT regimens, and underwent US examinations at baseline and at each NACT cycle. We subsequently determined that percentage reduction of tumor maximum diameter from baseline to third cycle of NACT serves to independent predictor for pCR, enabling creation of a nomogram ([Formula: see text]). Our predictive accuracy further improved ([Formula: see text]) by combining dynamic US data and clinicopathological features in a machine learning model. Such models may offer a means of accurately predicting NACT responses in this setting, helping to individualize patient therapy. Our study may provide additional insights into the US-based response prediction by focusing on the dynamic changes of the tumor in the early and full NACT cycle.

Does T1c-2N0-1M0 triple negative breast cancer derive a benefit from neoadjuvant chemotherapy?

OBJECTIVES

Although neoadjuvant chemotherapy (NCT) is a standard approach for operable triple negative breast cancer (TNBC), the potential risks brought by it should also be noticed. Is the expanding indication of NCT to T1cN0M0 population appropriate? We conducted an investigation to compare the long-term survival of small tumor TNBC between NCT and adjuvant chemotherapy (ACT).

METHODS

For this propensity-matched analysis, we used data from Surveillance, Epidemiology, and End Results (SEER) database. We enrolled 1183 cases with NCT and 2550 cases with ACT who are AJCC clinical T1c-T2 N0-N1, diagnosed with invasive triple-negative breast cancer, from 2016 to 2017. The propensity score matching was utilized to minimize baseline characteristics bias. Hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated by the Cox proportional hazard regression model.

RESULTS

Compared with patients receiving ACT, patients with NCT in this study presented a higher proportion of younger age, T2 stage, N1 stage, and underwent more mastectomy. Multivariate analysis in matched patients showed that NCT had no significant survival benefit compared with ACT in T1c-2N0-1M0 TNBC patients. Stratified analyses by T stage and N stage demonstrated NCT mainly presented a survival advantage in patients with N1 stage. Further investigation found that NCT didn't improve BCSS (HR, 0.472; 95% CI 0.135-1.647; P = 0.239) and OS (HR, 0.392; 95% CI 0.147-1.047; P = 0.062) for patients with T1cN0M0 TNBC; however, it was associated with improved OS (HR, 1.951; 95% CI 1.003-3.797; P = 0.049) only for patients with T2N1M0 TNBC.

CONCLUSIONS

In this study, we did not find any profit brought by NCT in the stage I and stage IIa cohorts, but even more unfavorable outcomes appeared in the T1cN0M0 cohort. Therefore, whether the candidates of NCT should be extended to T1cN0M0 still need to be cautious.

18F-FDG PET/CT for early prediction of pathological complete response in breast cancer neoadjuvant therapy: a retrospective analysis

BACKGROUND

Neoadjuvant treatment has been developed as a systematic approach for patients with early breast cancer and has resulted in improved breast-conserving rate and survival. However, identifying treatment-sensitive patients at the early phase of therapy remains a problem, hampering disease management and raising the possibility of disease progression during treatment.

METHODS

In this retrospective analysis, we collected 2-deoxy-2-[F-18] fluoro-d-glucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) images of primary tumor sites and axillary areas and reciprocal clinical pathological data from 121 patients who underwent neoadjuvant treatment and surgery in our center. The univariate and multivariate logistic regression analyses were performed to investigate features associated with pathological complete response (pCR). An 18F-FDG PET/CT-based prediction model was trained, and the performance was evaluated by receiver operating characteristic curves (ROC).

RESULTS

The maximum standard uptake values (SUVmax) of 18F-FDG PET/CT were a powerful indicator of tumor status. The SUVmax values of axillary areas were closely related to metastatic lymph node counts (R = 0.62). Moreover, the early SUVmax reduction rates (between baseline and second cycle of neoadjuvant treatment) were statistically different between pCR and non-pCR patients. The early SUVmax reduction rates-based model showed great ability to predict pCR (AUC = 0.89), with all molecular subtypes (HR+HER2-, HR+HER2+, HR-HER2+, and HR-HER2-) considered.

CONCLUSION

Our research proved that the SUVmax reduction rate of 18F-FDG PET/CT contributed to the early prediction of pCR, providing rationales for utilizing PET/CT in NAT in the future.

Predictors of mastectomy in breast cancer patients with complete remission of primary tumor after neoadjuvant therapy: A retrospective study

INTRODUCTION

Neoadjuvant therapy (NAT) should increase the rate of breast-conserving surgery (BCS) in non-metastatic breast cancer (BC) patients, especially in those achieving tumor shrinkage. Still, the conversion from a pre-planned mastectomy to BCS in patients responding to NAT is not a widespread standard. We aimed to identify factors influencing surgical choices in this setting.

MATERIALS AND METHODS

We retrospectively collected data of BC patients with complete remission of primitive tumor (ypT0) after NAT, treated with BCS or mastectomy in two Italian breast units. Predictors of mastectomy were explored using logistic regression. Distant recurrence and event-free survival were assessed in the BCS and mastectomy cohort.

RESULTS

243 patients were included, 147 (60.5 %) treated with BCS and 96 (39.5 %) treated with mastectomy. In the mastectomy group, there were more centrally-located, multiple and larger tumors. At univariate regression analysis, central location, baseline tumor extension on ultrasound (US) and magnetic resonance imaging (MRI), multiple foci and clinical stage were significantly associated with the chance of receiving mastectomy. At multivariate analysis, only baseline focality on US and extension on MRI retained significance as predictors of mastectomy. Distant recurrence and event-free survival were significantly longer in patients undergoing BCS.

CONCLUSION

Baseline tumor extension and focality were the main predictors of mastectomy in patients with ypT0 after NAT. However, BCS did not negatively affect survival outcomes in our cohort. An effort should be made to avoid potentially unnecessary mastectomy in this population, aiming at minimizing surgery-associated toxicities and improving patients' quality of life.

Breast Cancer: Multi-b-Value Diffusion Weighted Habitat Imaging in Predicting Pathologic Complete Response to Neoadjuvant Chemotherapy

RATIONALE AND OBJECTIVES

The aim of this study was to ascertain whether the utilization of multiple b-value diffusion-weighted habitat imaging, a technique that depicts tumor heterogeneity, could aid in identifying breast cancer patients who would derive substantial benefit from neoadjuvant chemotherapy (NAC).

MATERIALS AND METHODS

This prospective study enrolled 143 women (II-III breast cancer), who underwent multi-b-value diffusion-weighted imaging (DWI) in 3-T magnetic resonance (MR) before NAC. The patient cohort was partitioned into a training set (consisting of 100 patients, of which 36 demonstrated a pathologic complete response [pCR]) and a test set (featuring 43 patients, 16 of whom exhibited pCR). Utilizing the training set, predictive models for pCR, were constructed using different parameters: whole-tumor radiomics (ModelWH), diffusion-weighted habitat-imaging (ModelHabitats), conventional MRI features (ModelCF), along with combined models ModelHabitats+CF. The performance of these models was assessed based on the area under the receiver operating characteristic curve (AUC) and calibration slope.

RESULTS

In the prediction of pCR, ModelWH, ModelHabitats, ModelCF, and ModelHabitats+CF achieved AUCs of 0.733, 0.722, 0.705, and 0.756 respectively, within the training set. These scores corresponded to AUCs of 0.625, 0.801, 0.700, and 0.824 respectively in the test set. The DeLong test revealed no significant difference between ModelWH and ModelHabitats (P = 0.182), between ModelHabitats and ModelHabitats+CF (P = 0.113).

CONCLUSION

The habitat model we developed, incorporating first-order features along with conventional MRI features, has demonstrated accurate predication of pCR prior to NAC. This model holds the potential to augment decision-making processes in personalized treatment strategies for breast cancer.

Locoregional recurrence after neoadjuvant versus adjuvant chemotherapy based on tumor subtypes in patients with early-stage breast cancer: A multi-institutional retrospective cohort study

BACKGROUND

Neoadjuvant chemotherapy (NACT) for early-stage breast cancer is associated with an increased risk of locoregional recurrence (LRR). We investigated whether the risk of LRR after NACT varies across tumor subtypes.

METHODS

We retrospectively reviewed the medical records of women who underwent breast-conserving surgery for breast cancer at three institutions between January 1, 2004, and December 31, 2018. Patients received either NACT or adjuvant chemotherapy (ACT), followed by radiotherapy. LRR was analyzed according to the hormone receptor (HR) and human epidermal growth factor receptor-2 (HER2) status using propensity score matching, log-rank test, and Cox regression analysis.

RESULTS

Among 10,328 patients, 2479 (24.0 %) received NACT. Within the median follow-up of 84.5 (IQR, 35.1-118.5) months, the 10-year LRR-free survival rates were 94.5 % and 90.7 % for the ACT and NACT groups, respectively (hazard ratio: 2.04, 95 % confidence interval [CI]: 1.68-2.46, p < 0.0001). NACT was significantly associated with higher LRR in the HR+/HER2- (hazard ratio: 2.52, 95 % CI: 1.83-3.46, p < 0.0001) and HR-/HER2- (hazard ratio: 1.85, 95 % CI: 1.37-2.50, p < 0.0001) subtypes. In the HR+/HER2- subtype, the elevated risk remained significant after propensity-score matching and Cox-regression analysis. However, NACT was not associated with LRR in the HR-/HER2- subtype after adjusting for other variables. Annual LRR pattern among the HR+/HER2- subtype showed the highest incidence in the early period of treatment.

CONCLUSION

Patients with the HR+/HER2- subtype showed an increased risk of LRR after NACT, while those with other subtypes showed comparable LRR-free survival.

Neoadjuvant chemotherapy for breast cancer in Italy: A Senonetwork analysis of 37,215 patients treated from 2017 to 2022

BACKGROUND

Adoption of neoadjuvant chemotherapy (NACT) in the "real world" has been poorly investigated. Aim of this study was to examine the rate of NACT in Italy, trends over time and determinants of therapeutic choices.

METHODS

Senonetwork, the recognized network of Breast Centers in Italy, has developed a voluntary national data warehouse with the aim to monitor and improve treatments quality. A retrospective analysis was conducted among 58,661 breast cancer (BC) patients treated between 2017 and 2022 by 24 high-volume Breast Centers participating in the project.

RESULTS

After subset exclusion, 37,215 primary BC patients were analysed, 32,933 underwent primary-breast-surgery and 4,282 underwent NACT. From 2017 to 2022, the overall NACT incidence increased particularly for HR-/HER2+, Triple-Negative, and HR+/HER2+ BC (p < 0.001). In cN + patients the recommendation to axillary lymph-node dissection after NACT decreased over time along with an increase of <4 lymph-nodes removed (p < 0.001). Immediate breast reconstruction and indication for nipple sparing mastectomy increased significantly over time (OR = 1.10, p = 0.011 and OR 1.14, p < 0.001, respectively). On multivariate analysis, there was a trend towards an increased adoption of conservative treatment for HR-/HER2+ (p = 0.01) and Triple Negative tumors (p = 0.06). Implementation of NACT varied significantly among Breast-Centers from 3.8 to 17.7 % (p < 0.001).

CONCLUSION

The impact of NACT on the subsequent surgical management is substantial and continues to evolve over time, resulting in less-extensive surgery. Even among high-volume Centers NACT implementation rate is still highly variable. Although we registered a significant increase in its use during the study period, these results need to be further improved.

Intratumoral and peritumoral radiomics for preoperative prediction of neoadjuvant chemotherapy effect in breast cancer based on 18F-FDG PET/CT

OBJECTIVE

To investigate the value of 18F-FDG PET/CT-based intratumoral and peritumoral radiomics in predicting the efficacy of neoadjuvant chemotherapy (NAC) for breast cancer.

METHODS

190 patients who met the inclusion and exclusion criteria from 2017 to 2022 were studied. Features were extracted from the PET/CT intratumoral and peritumoral regions, feature selection was performed through the correlation analysis, t-tests, and least absolute shrinkage and selection operator regression (LASSO). Four classifiers, support vector machine (SVM), k-nearest neighbor (KNN), logistic regression (LR), and naive bayes (NB) were used to build the prediction models. The receiver operating characteristic (ROC) curves were plotted to measure the predictive performance of the models. Concurrent stratified analysis was conducted to establish subtype-specific features for each molecular subtype.

RESULTS

Compared to intratumoral features alone, intratumoral + peritumoral features achieved higher AUC values in each classifier. The SVM model constructed with intratumoral + peritumoral features achieved the highest AUC values in both the train and test set (train set: 0.95 and test set: 0.83). Subtype-specific features improve performance in predicting the efficacy of NAC (luminal group: 0.90; HER2 + group: 0.86; triple negative group: 0.92).

CONCLUSION

Intratumoral and peritumoral radiomics models based on 18F-FDG PET/CT can reliably forecast the efficacy of NAC, thereby assisting clinical decision-making.

Comparison of proportions and prognostic impact of pathological complete response between evaluations of representative specimen and total specimen in primary breast cancer after neoadjuvant chemoradiotherapy: an ancillary study of JCOG0306

BACKGROUND

In JCOG0306 trial, a phase II study to examine the efficacy of neoadjuvant chemotherapy followed by radiation therapy (NAC-RT) to primary breast cancer, pathological complete response (pCR) was evaluated from specimens of the representative cross-section including the tumor center that had been accurately marked [representative specimen (RS) method]. In this ancillary study, we examined if the RS method was comparable to the conventional total specimen (TS) method, which is widely employed in Japan, to identify the pCR group showing excellent prognosis.

METHODS

We obtained long-term follow-up data of 103 patients enrolled in JCOG0306 trial. As histological therapeutic effect, pCR (ypT0 and ypT0/is) and quasi-pCR [QpCR, ypT0/is plus Grade 2b (only a few remaining invasive cancer cells)] were evaluated with RS and TS methods. Concordance of pCR between these two methods and associations of the pCR with prognosis were examined.

RESULTS

ypT0, ypT0/is, and QpCR were observed in 28 (27.2%), 39 (37.9%), and 45 (43.7%) patients with RS method, whereas these were 20 (19.4%), 25 (24.3%) and 40 (38.9%) with TS method, respectively. Between RS and TS methods, concordance proportions of ypT0 and ypTis were 92.2% and 86.4%, respectively. Risk of recurrence of ypT0/is group was lower than that of non-ypT0/is group (HR 0.408, 95% CI [0.175-0.946], P = 0.037) and risk of death of ypT0/is group was lower than that of non-ypT0/is group (HR 0.251, 95% CI [0.073-0.857], P = 0.027). The ypT0 and ypT0/is groups with RS method showed excellent prognosis similarly with those with TS method, and RS method was able to differentiate the OS and RFS between pCR and non-pCR than TS method significantly even if pCR was classified ypT0 or ypT0/is. With TS method, QpCR criteria stratified patients into the better and worse prognosis groupsmore clearly than pCR criteria of ypT0 or ypT0/is.

CONCLUSIONS

RS method was comparable to TS method for the evaluation of pCR in the patients who received NAC-RT to primary breast cancer provided the tumor center was accurately marked. As pCR criteria with RS method, ypT0/is appeared more appropriate than ypT0.

Predicting pathologic complete response to neoadjuvant chemotherapy in breast cancer using a machine learning approach

BACKGROUND

For patients with breast cancer undergoing neoadjuvant chemotherapy (NACT), most of the existing prediction models of pathologic complete response (pCR) using clinicopathological features were based on standard statistical models like logistic regression, while models based on machine learning mostly utilized imaging data and/or gene expression data. This study aims to develop a robust and accessible machine learning model to predict pCR using clinicopathological features alone, which can be used to facilitate clinical decision-making in diverse settings.

METHODS

The model was developed and validated within the National Cancer Data Base (NCDB, 2018-2020) and an external cohort at the University of Chicago (2010-2020). We compared logistic regression and machine learning models, and examined whether incorporating quantitative clinicopathological features improved model performance. Decision curve analysis was conducted to assess the model's clinical utility.

RESULTS

We identified 56,209 NCDB patients receiving NACT (pCR rate: 34.0%). The machine learning model incorporating quantitative clinicopathological features showed the best discrimination performance among all the fitted models [area under the receiver operating characteristic curve (AUC): 0.785, 95% confidence interval (CI): 0.778-0.792], along with outstanding calibration performance. The model performed best among patients with hormone receptor positive/human epidermal growth factor receptor 2 negative (HR+/HER2-) breast cancer (AUC: 0.817, 95% CI: 0.802-0.832); and by adopting a 7% prediction threshold, the model achieved 90.5% sensitivity and 48.8% specificity, with decision curve analysis finding a 23.1% net reduction in chemotherapy use. In the external testing set of 584 patients (pCR rate: 33.4%), the model maintained robust performance both overall (AUC: 0.711, 95% CI: 0.668-0.753) and in the HR+/HER2- subgroup (AUC: 0.810, 95% CI: 0.742-0.878).

CONCLUSIONS

The study developed a machine learning model ( https://huolab.cri.uchicago.edu/sample-apps/pcrmodel ) to predict pCR in breast cancer patients undergoing NACT that demonstrated robust discrimination and calibration performance. The model performed particularly well among patients with HR+/HER2- breast cancer, having the potential to identify patients who are less likely to achieve pCR and can consider alternative treatment strategies over chemotherapy. The model can also serve as a robust baseline model that can be integrated with smaller datasets containing additional granular features in future research.