Development and Validation of a Novel Model for Predicting Prognosis of Non-PCR Patients After Neoadjuvant Therapy for Breast Cancer

Predicting prognosis of patients with triple‑negative breast cancer undergoing neoadjuvant chemotherapy based on inflammatory status at different time points: A propensity score matching analysis

Triple-negative breast cancer (TNBC) is a highly aggressive subtype of breast cancer with limited targeted treatment options, making the identification of reliable prognostic markers crucial for improving patient outcomes. The present study aimed to assess the predictive ability of pre-chemotherapy and pre-surgery inflammatory status on the prognosis of patients with TNBC undergoing neoadjuvant therapy. A total of 422 patients with TNBC who received neoadjuvant chemotherapy at the Inner Mongolia People's Hospital between January 2017 and December 2022 were selected for analysis. Fasting venous blood samples were collected 1 day prior to chemotherapy and 1 day prior to surgery to assess and calculate inflammatory markers, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI). The optimal cut-off values of the inflammatory markers were determined using receiver operating characteristic curves. Survival analysis was used to evaluate the differences in survival and significant prognostic factors. Propensity score matching (PSM) analysis was performed to further asses the prognostic value of the relevant factors. Survival analysis indicated that patients with high pre-chemotherapy and pre-surgery NLR, PLR, SII and SIRI scores exhibited shorter overall survival (OS) rates compared with those with low scores (all P<0.05). Multivariate analysis revealed that tumor-node-metastasis stage, pathological complete response and pre-surgery SII were independent prognostic factors for OS. Following PSM, the area under the curve for SII was 0.642 and patients with high SII scores exhibited shorter OS rates than those with low scores (χ2=8.452; P=0.004). Therefore, these results indicated that both pre-chemotherapy and pre-surgery inflammatory statuses are associated with the OS of patients with TNBC undergoing neoadjuvant chemotherapy, notably pre-surgery SII.

Surgical Interest of an Accurate Real-World Prediction of Primary Systemic Therapy Response in HER2 Breast Cancers

Human epidermal growth factor receptor 2 (HER2)-enriched breast cancers (BC) present the highest rates of pathological response to primary systemic therapy (PST), but they are also the ones that tend to be larger at diagnosis, with microcalcifications and, often, with axillary involvement. If we do not have a reliable method to predict the degree of response, we may not be able to transfer the benefits of PST to surgery. The post-PST surgery planning is guided by the findings in the magnetic resonance imaging (MRI), whose predictive capacity, although high, is far from optimal. Thus, it seems interesting to find other variables to improve it. A retrospective observational study including women with HER2 BC treated with PST and further surgery was conducted. Information regarding clinical, radiological, and histopathological variables was gathered from a total of 132 patients included. Radiological complete response (rCR) was achieved in 65.9% of the sample, and pathological complete response (pCR), according to Miller and Payne criteria, in 58.3% of cases. A higher Ki67 value, the absence of Hormonal Receptors expression, and an rCR was significantly related to a pCR finding. This information impacts directly in surgery planning, as it permits adjustment of the breast resection volume.

Good practice: The experiences with the utilization of residual cancer burden-A single institution study

INTRODUCTION

The use of neoadjuvant therapy (NAT) has been showing an incraesing tendency in the treatment of locally advanced breast cancer. The evaluation of residual cancer could be performed by Residual Cancer Burden (RCB) calculator. The prognostic system takes the two largest diameters of the tumor, the cellularity, the amount of in situ carcinoma, the number of metastatic lymph nodes, and the size of the largest metastatic deposit into account. The aim of our study was to examine the reproducibility of RCB in NAT treated patients.

METHODS

Patients who were treated with NAT and had resection specimens between 2018 and 2021 were selected. Histological examination was performed by five pathologists. After assessment of the examined variables, RCB points and RCB classes were defined. For statistical analysis, interclass correlation was used (SPSS Statistics V.22.0 software).

RESULTS

Altogether 100 patients were included in our retrospective, cohort study (average age: 57 years). In two-thirds of the cases, third generation chemotherapy was used, and mastectomy was performed. Significant concordance was found in the two largest diameters of the tumor (coefficients, 0.984 and 0.973), the cellularity (coefficient, 0.970), and the largest metastatic deposit (coefficient, 0.998). Although the amount of in situ carcinoma proved to be the least reproducible factor, it resulted in almost 90% of agreement (coefficient, 0.873). Regarding RCB points and classes, similar results were observed (coefficients, 0.989 and 0.960).

CONCLUSIONS

Significant agreement was observed between examiners based on almost all RCB parameters, points, and classes, reflecting the optimal reproducibility of RCB. Therefore, we recommend the use of the calculator in routine histopathological reports in NAT cases.

The prognostic role of lymph node ratio in breast cancer patients received neoadjuvant chemotherapy: A dose-response meta-analysis

BACKGROUND

As neoadjuvant chemotherapy is widely used in breast cancer patients, the lymph node ratio has not been fully validated as a prognostic indicator of breast cancer received neoadjuvant chemotherapy. This study was conducted to investigate the prognostic value of lymph node ratio in breast cancer patients received neoadjuvant chemotherapy.

METHODS

Systematic searches were performed in the PubMed, Embase, and Cochrane Library databases until 15 December 2021 for studies on the association between lymph node ratio and the prognosis of breast cancer after neoadjuvant chemotherapy. Overall survival and disease-free survival were used as outcome events, and hazard ratio was chosen as the parameter to evaluate the correlation. The dose-response relationship was assessed by restricted cubic splines. In the subgroup analyses, which were used to explore potential heterogeneity among the included studies according to study region and sample size. Sensitivity analysis was performed to assess the stability of individual studies, and publication bias was determined with funnel plots, Begg's test, and Egger&apos;s test. All statistical analyses were performed using Stata 15.1.

RESULTS

A total of 12 studies with 4,864 patients were included in this meta-analysis. In this study, high lymph node ratio was significantly associated with decreased overall survival (HR: 4.74; 95%CI: 3.36-6.67; P < 0.001) and disease-free survival (HR: 4.77; 95%CI: 3.69-6.17; P < 0.001). Moreover, the dose-response meta-analysis showed a linear association between higher lymph node ratio and shorter overall survival and disease-free survival in breast cancer patients after neoadjuvant chemotherapy.

CONCLUSIONS

The meta-analysis suggested that high lymph node ratio was significantly associated with short overall survival and disease-free survival in breast cancer patients after neoadjuvant chemotherapy. Therefore, lymph node ratio is an independent predictive factor for the prognosis of breast cancer patients after neoadjuvant chemotherapy, which may better refine the cancer staging system.

Multimodal Prediction of Five-Year Breast Cancer Recurrence in Women Who Receive Neoadjuvant Chemotherapy

In current clinical practice, it is difficult to predict whether a patient receiving neoadjuvant chemotherapy (NAC) for breast cancer is likely to encounter recurrence after treatment and have the cancer recur locally in the breast or in other areas of the body. We explore the use of clinical history, immunohistochemical markers, and multiparametric magnetic resonance imaging (DCE, ADC, Dixon) to predict the risk of post-treatment recurrence within five years. We performed a retrospective study on a cohort of 1738 patients from Institut Curie and analyzed the data using classical machine learning, image processing, and deep learning. Our results demonstrate the ability to predict recurrence prior to NAC treatment initiation using each modality alone, and the possible improvement achieved by combining the modalities. When evaluated on holdout data, the multimodal model achieved an AUC of 0.75 (CI: 0.70, 0.80) and 0.57 specificity at 0.90 sensitivity. We then stratified the data based on known prognostic biomarkers. We found that our models can provide accurate recurrence predictions (AUC > 0.89) for specific groups of women under 50 years old with poor prognoses. A version of our method won second place at the BMMR2 Challenge, with a very small margin from being first, and was a standout from the other challenge entries.

Androgen Receptor: A New Marker to Predict Pathological Complete Response in HER2-Positive Breast Cancer Patients Treated with Trastuzumab Plus Pertuzumab Neoadjuvant Therapy

(1) Background: Neoadjuvant therapy is the main therapeutic strategy for human epidermal growth factor receptor 2 (HER2)-positive breast cancer patients, and the combination of trastuzumab and pertuzumab (HP) has become a routine treatment. How to predict and screen patients who are less likely to respond to neoadjuvant therapy is the focus of research. The androgen receptor (AR) is a biomarker that is widely expressed in all breast cancer subtypes and is probably related to treatment response and prognosis. In this study, we investigated the relationship between AR expression and treatment response in HER2-positive breast cancer patients treated with HP neoadjuvant therapy. (2) Methods: We evaluated early breast cancer patients treated with HP neoadjuvant therapy from Jan. 2019 to Oct. 2020 at Peking University First Hospital Breast Cancer Center. The inclusion criteria were as follows: early HER2-positive breast cancer patients diagnosed by core needle biopsy who underwent both HP neoadjuvant therapy and surgery. We compared the clinical and pathological features between pathological complete response (pCR) and non-pCR patients. (3) Results: We included 44 patients. A total of 90.9% of patients received neoadjuvant therapy of taxanes, carboplatin, trastuzumab and pertuzumab (TCHP), and the total pCR rate was 50%. pCR was negatively related to estrogen receptor (ER) positivity (OR 0.075 [95% confidence interval (CI) 0.008–0.678], p = 0.021) and positively related to high expression levels of AR (OR 33.145 [95% CI 2.803–391.900], p = 0.005). We drew a receiver operating characteristic (ROC) curve to assess the predictive value of AR expression for pCR, and the area under the curve was 0.737 (95% CI 0.585–0.889, p = 0.007). The optimal cutoff of AR for predicting pCR was 85%. (4) Conclusion: AR is a potential marker for the prediction of pCR in HER2-positive breast cancer patients treated with HP neoadjuvant therapy.