Implications for Breast Cancer Restaging Based on the 8th Edition AJCC Staging Manual. Ann Surg. 2018;. [PMID: 30312199 DOI: 10.1097/sla.0000000000003071]

Comparison of survival outcomes for patients with Stage III vs de novo Stage IV breast cancer

PURPOSE

Improvements in systemic therapy have resulted in significant heterogeneity in survival outcomes for metastatic breast cancer patients. As such, recently proposed staging guidelines for de novo metastatic breast cancer stratify patients into four categories (IVA/IVB/IVC/IVD). Expanding on this, overall survival (OS) outcomes for patients with Stage III vs Stage IV breast cancer were compared based on the previously defined American Joint Committee on Cancer guidelines and recently proposed subgroups for de novo metastatic breast cancer.

METHODS

Adult patients diagnosed with Stage III or IV breast cancer in the National Cancer Database (2010-2019) were stratified as IIIA/B/C (American Joint Committee on Cancer, 8th edition) or IVA/B/C/D. OS was estimated using the Kaplan-Meier method. Cox proportional hazards models estimated the association between stage subgroups and OS.

RESULTS

Among 81,128 patients (median follow-up, 76.8 months), 83.5% were Stage III and 16.5% Stage IV. Unadjusted 3-year OS rates were 85.7% for Stage III versus 68.3% for Stage IV. From Stage III to Stage IV, OS declined but there was notable convergence in OS between subgroups. The unadjusted 3-year OS for IIIC was 69.6%, which was lower than IVA (87.0%) and IVB (78.4%). Adjusted analysis showed similar trends, with the HR for IIIC at 1.94, which was worse than IVA at 1.20 and IVB at 1.83 (ref: IIIA, overall p < .001).

CONCLUSIONS

It was demonstrated that the survival outcomes for select patients with Stage IV breast cancer have significant convergence in OS with some patients with Stage III disease. These findings may be important for patient counseling, treatment approaches, and clinical trial design.

The American Joint Committee on Cancer (AJCC) Breast Cancer Staging, Eighth Edition, is more Reflective of Cancer Biology than the Seventh Edition

BACKGROUND

The American Joint Committee on Cancer (AJCC) eighth-edition breast cancer staging system incorporating tumor grade, hormone/human epidermal growth factor receptor 2 (HER2) receptor status, and genomic assays has demonstrated better prognostic value than the seventh edition. Given the crucial role of cancer biology in prognosis, the authors hypothesized that the AJCC eighth-edition criteria offer better biologic differentiation between stages than the seventh edition.

METHODS

This study analyzed 696 breast cancer patients from The Cancer Genome Atlas (TCGA) and Text Information Extraction System (TIES) database, with complete information available for staging according to both the AJCC seventh- and eighth-edition criteria.

RESULTS

The study indicated an increase in the number of patients classified as stage I in the eighth edition compared with the seventh edition, particularly in hormone-positive breast cancers. Furthermore, the eighth edition demonstrated improved discrimination in overall survival between stages I and II cancers. The eighth edition was able to distinguish significant differences in cell proliferation, intratumor heterogeneity, homologous recombination deficiency, and neoantigen load between stages I and II cancers. Moreover, the eighth edition more clearly differentiated immune cell infiltration between stages II and I cancer than the seventh edition. Finally, immune activity and gene expression of immune checkpoints such as PDCD1, PDL1, CTLA4, LAG3, TIGIT, and IDO1 and 2 showed a more pronounced difference between stages I and II cancers in the eighth edition than in the seventh edition.

CONCLUSION

The AJCC eighth edition breast cancer staging system better distinguishes cancers with more aggressive biology than the seventh edition.

Prognostic analysis of N3 locally advanced breast cancer according to the 8th edition of AJCC clinical stage: a propensity-matched SEER analysis

Background

The 8th edition of the American Joint Committee on Cancer (AJCC) clinical staging-including both anatomical and prognostic staging-serves as a valuable tool for predicting the prognosis of N3 locally advanced breast cancer (LABC). This study aims to apply these criteria to analyze changes in staging and evaluate differences in survival outcomes.

Methods

Data from the Surveillance, Epidemiology, and End Results (SEER) database were used for patients with newly diagnosed N3 LABC and complete follow-up from 2010 to 2015. Patients were categorized into N3a, N3b, and N3c groups. Chi-squared tests compared differences, while univariate and multivariate Cox analyses assessed breast cancer-specific survival (BCSS) and overall survival (OS). Kaplan-Meier curves and the log-rank test were used to analyze prognostic factors. Propensity score matching (PSM) was applied to reduce baseline differences and enable further comparative validation.

Results

Before PSM, a total of 5,096 patients were included in this study. Among these patients were classified 4,080 as N3a, 655 as N3b, and 361 as N3c. Significant differences were observed among the three groups in terms of histological grade, tumour stage, estrogen receptor (ER) status, progesterone receptor (PR) status, human epidermal growth factor receptor 2 (HER2) status (all P<0.001). In Kaplan-Meier survival analysis stratified by anatomical staging, the N3b group had the most favourable prognosis, followed by the N3a and N3c groups (OS, P<0.001; BCSS, P<0.001). In prognostic staging, the N3b group had the most favourable prognosis, followed by N3a and N3c groups, for stages IIIb and IIIc (OS, P<0.005; BCSS, P<0.005). Multivariate Cox regression analysis identified that N-stage were significantly associated with prognosis (P<0.05). After PSM, 200 N3a patients, 118 N3b patients, and 287 N3c patients were included in this study. After PSM, Significant differences were observed among the three groups in terms of histological grade (P=0.04), tumor stage (P<0.001), ER status (P<0.001), and PR status (P<0.001). In Kaplan-Meier analysis stratified by anatomical staging, the N3b group had the best prognosis, followed by the N3a and N3c groups (OS, P=0.02; BCSS, P=0.07). In prognostic staging, for stage IIIb prognostic staging, the N3b group again exhibited the most favourable prognosis, followed by the N3a and N3c groups (OS, P=0.03; BCSS, P=0.12). Multivariate Cox regression analysis revealed that the survival risk in the N3b group is slightly lower than that in the N3a group.

Conclusions

In the anatomical and prognostic staging of N3 LABC, the N3b subgroup demonstrates the most promising prognosis. The 8th edition of the AJCC prognostic staging system offers a more detailed framework for assessing prognosis and guiding the diagnosis and treatment of N3 LABC.

SMARCA4/BRG1-deficient non-small cell lung cancer: clinical, imaging, pathological features, and follow-up results of 23 patients

Background

SMARCA4/BRG1-deficient non-small cell lung cancer (S/B-d NSCLC) is a rare subtype of non-small cell lung cancer (NSCLC). The aim of this study was to investigate the clinical, imaging, serum tumor marker, and pathological features of S/B-d NSCLC, particularly computed tomography (CT) and 18F-fluorodeoxyglucose (FDG) positron emission tomography-computed tomography (PET/CT) scan features.

Methods

Our analysis included 23 patients with pathologically confirmed S/B-d NSCLC from January 2021 to December 2023. A retrospective analysis of clinical, serum tumor markers, imaging [including CT, FDG PET/CT, magnetic resonance imaging (MRI)], pathological features, treatment protocols, and follow-up results was performed. Independent samples t-tests were used to assess statistical differences in short diameters and maximum standardized uptake value (SUVmax) between groups.

Results

S/B-d NSCLC occurs predominantly in male patients with a history of smoking and a mean age of 62.78 years (39-77 years). S/B-d NSCLC was found incidentally during physical examination in 56.52% of patients. The CT scan features were as follows: predominantly tumors (72.73%), peripheral in the lungs (77.27%), round or roundish morphology (81.28%), pleural or vascular invasion (95.46%), and moderately to severely enhanced (59.09%). The FDG PET/CT showed FDG-avid with mean SUVmax of 14.78±9.57. Lung cancer-related serum tumor markers had high positivity rates for carcinoembryonic antigen (CEA) (66.67%), recombinant cytokeratin fragment antigen 21-1 (CYFRA21-1) (61.91%), and carbohydrate antigen 125 (CA125) (57.14%). Pathological features are often characterized by grading (poor differentiation, 100%), tumor spread through the air space (STAS, 85.71%), and vascular invasion (85.71%). Immunohistochemistry showed that SMARCA4 (BRG1) was absent, and P40, P63, ALK-Ventana ALK (D5F3), and p-TRK were often negative. Genetic tests showed that the positivity rate of TP53 (76.92%) and KEAP1 (53.85%) was high. Despite diverse treatment options being available, high rates of progression during treatment and poor prognosis were observed. Among CT features (N=22), the short diameter of CT-diagnosed metastatic lymph nodes (LNs) was larger than that of non-metastatic LNs, and the difference was statistically significant (P=0.02). Among the FDG PET/CT features (N=12), SUVmax was larger in tumor group than lesion group, SUVmax was larger in M1 group than M0 group, and the difference was statistically significant in both groups (P=0.001 and P=0.04).

Conclusions

S/B-d NSCLC has distinct features in epidemiology, serum tumor markers, imaging, and pathology. In particular, FDG-avid is evident in the FDG PET/CT scan. The size of the lesion and the degree of FDG avidity provide information about the degree of malignancy and the high probability of distant metastasis in S/B-d NSCLC. FDG PET/CT is recommended when S/B-d NSCLC is suspected based on CT features, especially for large lesions. The FDG PET/CT scan can help with accurate staging and individual treatment planning.

Nomogram prediction of overall survival in breast cancer patients post-surgery: integrating SEER database and multi-center evidence from China

Purpose

Overall survival (OS) in postoperative breast cancer patients is influenced by various clinicopathological features. Current prognostic methods, such as the 7th edition of AJCC staging, have limitations. This study aims to construct and validate a comprehensive nomogram integrating multiple clinicopathological features to predict OS more accurately in breast cancer patients.

Methods

We identified 60,445 .female patients who underwent breast cancer surgery between January 1, 2011, and December 31, 2015, from the Surveillance, Epidemiology, and End Results (SEER) database, randomly divided into training and internal validation cohorts. Additionally, data from 332 breast cancer surgery patients from four hospitals in Taizhou, Zhejiang Province, were included as an external validation cohort. Kaplan-Meier analysis assessed the impact of clinicopathological features on OS, and multivariable Cox regression identified independent prognostic factors. A nomogram based on these factors was constructed to predict 1-, 3-, and 5-year OS. Model predictive performance was evaluated using C-index, AUC, calibration curves, and decision curves during internal and external validation.

Results

Multivariable Cox regression analysis identified age, pathological grade, AJCC stage, ER status, PR status, and HER2 status as independent prognostic factors used in the nomogram construction. The nomogram achieved a C-index of 0.724 (95% CI, 0.716-0.732) in the training cohorts, 0.717 (95% CI, 0.705-0.729) in the internal validation cohorts, and 0.793 (95% CI, 0.724-0.862) in the external validation cohorts, indicating strong discriminative ability. Calibration curves demonstrated good agreement between predicted and observed outcomes in all validation cohorts. Decision curve analysis showed that the nomogram provided maximum net benefit across all validation cohorts.

Conclusion

The nomogram developed in this study integrates multiple clinicopathological features and provides a convenient and accurate tool for predicting individualized OS in breast cancer patients. This tool can optimize treatment strategies and improve patient prognosis.

Assessment of Treatment Sequence in Patients With Stage III Breast Cancer

INTRODUCTION

Stage III breast cancer is defined as locally advanced breast cancer and is treated with curative intent. Historically, overall survival (OS) did not differ based on treatment sequence (neoadjuvant chemotherapy [NAC] followed by surgery versus surgery followed by chemotherapy). Given recent advancements, we examined if treatment sequence may be associated with improved OS in a contemporary cohort of patients with stage III breast cancer.

METHODS

Patients aged 18-80 years with prognostic stage III breast cancer who received chemotherapy and surgery were selected from the Surveillance, Epidemiology, and End Results database. Patients were stratified by treatment sequence (NAC versus surgery first). Unadjusted OS and breast cancer-specific survival (BCSS) were estimated using the Kaplan-Meier method and compared with log-rank tests. Cox proportional hazards models were used to estimate the association of treatment sequence with OS and BCSS after adjustment for selected covariates.

RESULTS

The study included 26,573 patients; median follow-up was 62.0 months (95% confidence interval [CI] 61.0-63.0). Patients receiving NAC had a worse OS and BCSS compared to those who underwent surgery first (5-year OS rates 0.66 versus 0.73; 5-year BCSS rates 0.70 versus 0.77; both log-rank P < 0.001). After adjustment for tumor subtype, receipt of NAC (versus surgery first) remained associated with a worse OS (hazard ratio 1.27, 95% CI 1.2-1.34, P < 0.001) and BCSS (hazard ratio 1.35, 95% CI 1.27-1.43, P < 0.001).

CONCLUSIONS

Based on data from patients treated largely before 2020, undergoing surgery first may be associated with improved survival, even after adjustment for known covariates including tumor subtype. These findings may inform treatment when caring for patients with operable, locally advanced breast cancer.

Internal Mammary Lymphadenopathy Does Not Impact Oncologic Outcomes in Patients Treated with Neoadjuvant Chemotherapy: Results from the I-SPY2 Clinical Trial

BACKGROUND

Internal mammary lymphadenopathy (IML) plays a role in breast cancer stage and prognosis. We aimed to evaluate method of IML detection, how IML impacts response to neoadjuvant chemotherapy (NAC), and oncologic outcomes.

METHODS

We evaluated patients enrolled in the I-SPY-2 clinical trial from 2010 to 2022. We captured the radiographic method of IML detection (magnetic resonance imaging [MRI], positron emission tomography/computed tomography [PET/CT], or both) and compared patients with IML with those without. Rates of locoregional recurrence (LRR), distant recurrence (DR) and event-free survival (EFS) were compared by bivariate analysis.

RESULTS

Of 2095 patients, 198 (9.5%) had IML reported on pretreatment imaging. The method of IML detection was 154 (77.8%) MRI only, 11 (5.6%) PET/CT only, and 33 (16.7%) both. Factors associated with IML were younger age (p = 0.001), larger tumors (p < 0.001), and higher tumor grade (p = 0.027). Pathologic complete response (pCR) was slightly higher in the IML group (41.4% vs. 34.0%; p = 0.03). There was no difference in breast or axillary surgery (p = 0.41 and p = 0.16), however IML patients were more likely to undergo radiation (68.2% vs. 54.1%; p < 0.001). With a median follow up of 3.72 years (range 0.4-10.2), there was no difference between IM+ versus IM- in LRR (5.6% vs. 3.8%; p = 0.25), DR (9.1% vs. 7.9%; p = 0.58), or EFS (61.6% vs. 57.2%; p = 0.48). This was true for patients with and without pCR.

CONCLUSIONS

In this large cohort of patients treated with NAC, outcomes were not negatively impacted by IML. We demonstrated that IML influences treatment selection but is not a poor prognostic indicator when treated with modern NAC and multidisciplinary disease management.

Prediction of breast cancer and axillary positive-node response to neoadjuvant chemotherapy based on multi-parametric magnetic resonance imaging radiomics models

PURPOSE

Accurate identification of primary breast cancer and axillary positive-node response to neoadjuvant chemotherapy (NAC) is important for determining appropriate surgery strategies. We aimed to develop combining models based on breast multi-parametric magnetic resonance imaging and clinicopathologic characteristics for predicting therapeutic response of primary tumor and axillary positive-node prior to treatment.

MATERIALS AND METHODS

A total of 268 breast cancer patients who completed NAC and underwent surgery were enrolled. Radiomics features and clinicopathologic characteristics were analyzed through the analysis of variance and the least absolute shrinkage and selection operator algorithm. Finally, 24 and 28 optimal features were selected to construct machine learning models based on 6 algorithms for predicting each clinical outcome, respectively. The diagnostic performances of models were evaluated in the testing set by the area under the curve (AUC), sensitivity, specificity, and accuracy.

RESULTS

Of the 268 patients, 94 (35.1 %) achieved breast cancer pathological complete response (bpCR) and of the 240 patients with clinical positive-node, 120 (50.0 %) achieved axillary lymph node pathological complete response (apCR). The multi-layer perception (MLP) algorithm yielded the best diagnostic performances in predicting apCR with an AUC of 0.825 (95 % CI, 0.764-0.886) and an accuracy of 77.1 %. And MLP also outperformed other models in predicting bpCR with an AUC of 0.852 (95 % CI, 0.798-0.906) and an accuracy of 81.3 %.

CONCLUSIONS

Our study established non-invasive combining models to predict the therapeutic response of primary breast cancer and axillary positive-node prior to NAC, which may help to modify preoperative treatment and determine post-NAC surgery strategy.

Internal mammary lymphadenopathy in breast cancer: a narrative review and update

Background and Objective

While the axillary nodal basin is the most common lymphatic drainage pathway of the breast, the internal mammary (IM) lymph node chain plays a significant role in breast cancer staging and treatment. It has been identified as sentinel nodal drainage in approximately 13-37% of patients. Despite this, the data is still limited with regard to diagnosis and management when there is suspicion or confirmation of IM lymph node (IMLN) involvement by metastatic breast cancer. The objective of this publication is to provide a comprehensive assessment of the current body of literature surrounding the diagnosis, management and prognostic value of IMLNs in breast cancer treatment.

Methods

Review of the literature published regarding IMLN diagnosis, significance, and management was completed in PubMed. Additional focus was placed on reviewing articles published within the past 10 years as foundation for an update regarding the current practice and future directions in this space.

Key Content and Findings

Improved imaging techniques, with positron emission tomography-computed tomography and magnetic resonance imaging, have led to increase in the identification of IM lymphadenopathy, yielding surgical staging of the IM nodes nearly obsolete. While IM nodal metastases may play a role in overall survival (OS), it has not been demonstrated to be an independent risk factor for increased locoregional recurrence. IM nodal irradiation (IMNI) therapy has been a mainstay in the treatment of IM disease in the context of breast cancer. IMNI has demonstrated improvement in OS and risk of distant recurrence. Wide variations in radiation practices for patients with IM lymphadenopathy exist internationally, highlighting the lack of clear data driven consensus guidelines.

Conclusions

Herein, we provide an updated assessment of the current diagnosis, clinical significance, and management of IM lymphadenopathy for breast cancer patients.

Adverse independent prognostic effect of initial lung cancer on female patients with second primary breast cancer: a propensity score-matched study based on the SEER database

OBJECTIVE

To investigate the prognostic impact of initial lung cancer (LC) on second primary breast cancer after LC (LC-BC) and further develop a nomogram for predicting the survival of patients.

METHODS

All patients diagnosed with LC-BC and first primary BC (BC-1) during 2000-2017 were collected from Surveillance, Epidemiology, and End Results database. Pathological features, treatment strategies and survival outcomes were compared between LC-BC and BC-1 before and after propensity score matching (PSM). Cox regression analysis was performed to identify the prognostic factors associated with LC in patients with LC-BC. Additionally, least absolute shrinkage and selection operator regression analysis was used to select clinical characteristics for nomogram construction, which were subsequently evaluated using the concordance index (C-index), calibration curve and decision curve analysis (DCA).

RESULTS

827 429 patients with BC-1 and 1445 patients with LC-BC were included in the analysis. Before and after PSM, patients with BC-1 had a better prognosis than individuals with LC-BC in terms of both overall survival (OS) and breast cancer-specific survival (BCSS). Furthermore, characteristics such as more regional lymph node dissection, earlier stage and the lack of chemotherapy and radiation for LC were found to have a stronger predictive influence on LC-BC. The C-index values (OS, 0.748; BCSS, 0.818), calibration curves and DCA consistently demonstrated excellent predictive accuracy of the nomogram.

CONCLUSION

In conclusion, patients with LC-BC have a poorer prognosis than those with BC-1, and LC traits can assist clinicians estimate survival of patients with LC-BC more accurately.

The metabolism-related lncRNA signature predicts the prognosis of breast cancer patients

Long non-coding RNAs (lncRNAs) involved in metabolism are recognized as significant factors in breast cancer (BC) progression. We constructed a novel prognostic signature for BC using metabolism-related lncRNAs and investigated their underlying mechanisms. The training and validation cohorts were established from BC patients acquired from two public sources: The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The prognostic signature of metabolism-related lncRNAs was constructed using the least absolute shrinkage and selection operator (LASSO) cox regression analysis. We developed and validated a new prognostic risk model for BC using the signature of metabolism-related lncRNAs (SIRLNT, SIAH2-AS1, MIR205HG, USP30-AS1, MIR200CHG, TFAP2A-AS1, AP005131.2, AL031316.1, C6orf99). The risk score obtained from this signature was proven to be an independent prognostic factor for BC patients, resulting in a poor overall survival (OS) for individuals in the high-risk group. The area under the curve (AUC) for OS at three and five years were 0.67 and 0.65 in the TCGA cohort, and 0.697 and 0.68 in the GEO validation cohort, respectively. The prognostic signature demonstrated a robust association with the immunological state of BC patients. Conventional chemotherapeutics, such as docetaxel and paclitaxel, showed greater efficacy in BC patients classified as high-risk. A nomogram with a c-index of 0.764 was developed to forecast the survival time of BC patients, considering their risk score and age. The silencing of C6orf99 markedly decreased the proliferation, migration, and invasion capacities in MCF-7 cells. Our study identified a signature of metabolism-related lncRNAs that predicts outcomes in BC patients and could assist in tailoring personalized prevention and treatment plans.

Construction and validation of a nomogram for predicting the prognosis of patients with lymph node-positive invasive micropapillary carcinoma of the breast: based on SEER database and external validation cohort

Background

Invasive micropapillary carcinoma (IMPC) of the breast is a rare subtype of breast cancer with high incidence of aggressive clinical behavior, lymph node metastasis (LNM) and poor prognosis. In the present study, using the Surveillance, Epidemiology, and End Results (SEER) database, we analyzed the clinicopathological characteristics and prognostic factors of IMPC with LNM, and constructed a prognostic nomogram.

Methods

We retrospectively analyzed data for 487 breast IMPC patients with LNM in the SEER database from January 2010 to December 2015, and randomly divided these patients into a training cohort (70%) and an internal validation cohort (30%) for the construction and internal validation of the nomogram, respectively. In addition, 248 patients diagnosed with IMPC and LNM at the Fourth Hospital of Hebei Medical University from January 2010 to December 2019 were collected as an external validation cohort. Lasso regression, along with Cox regression, was used to screen risk factors. Further more, the discrimination, calibration, and clinical utility of the nomogram were assessed based on the consistency index (C-index), time-dependent receiver operating characteristic (ROC), calibration curve, and decision curve analysis (DCA).

Results

In summary, we identified six variables including molecular subtype of breast cancer, first malignant primary indicator, tumor grade, AJCC stage, radiotherapy and chemotherapy were independent prognostic factors in predicting the prognosis of IMPC patients with LNM (P < 0.05). Based on these factors, a nomogram was constructed for predicting 3- and 5-year overall survival (OS) of patients. The nomogram achieved a C-index of 0.789 (95%CI: 0.759-0.819) in the training cohort, 0.775 (95%CI: 0.731-0.819) in the internal validation cohort, and 0.788 (95%CI: 0.756-0.820) in the external validation cohort. According to the calculated patient risk score, the patients were divided into a high-risk group and a low-risk group, which showed a significant difference in the survival prognosis of the two groups (P<0.0001). The time-dependent ROC curves, calibration curves and DCA curves proved the superiority of the nomogram.

Conclusions

We have successfully constructed a nomogram that could predict 3- and 5-year OS of IMPC patients with LNM and may assist clinicians in decision-making and personalized treatment planning.

MicroRNA-155 and cancer metastasis: Regulation of invasion, migration, and epithelial-to-mesenchymal transition

Among the leading causes of death globally has been cancer. Nearly 90% of all cancer-related fatalities are attributed to metastasis, which is the growing of additional malignant growths out of the original cancer origin. Therefore, a significant clinical need for a deeper comprehension of metastasis exists. Beginning investigations are being made on the function of microRNAs (miRNAs) in the metastatic process. Tiny non-coding RNAs called miRNAs have a crucial part in controlling the spread of cancer. Some miRNAs regulate migration, invasion, colonization, cancer stem cells' properties, the epithelial-mesenchymal transition (EMT), and the microenvironment, among other processes, to either promote or prevent metastasis. One of the most well-conserved and versatile miRNAs, miR-155 is primarily distinguished by overexpression in a variety of illnesses, including malignant tumors. It has been discovered that altered miR-155 expression is connected to a number of physiological and pathological processes, including metastasis. As a result, miR-155-mediated signaling pathways were identified as possible cancer molecular therapy targets. The current research on miR-155, which is important in controlling cancer cells' invasion, and metastasis as well as migration, will be summarized in the current work. The crucial significance of the lncRNA/circRNA-miR-155-mRNA network as a crucial regulator of carcinogenesis and a player in the regulation of signaling pathways or related genes implicated in cancer metastasis will be covered in the final section. These might provide light on the creation of fresh treatment plans for controlling cancer metastasis.

Prediction of bone metastasis risk of early breast cancer based on nomogram of clinicopathological characteristics and hematological parameters

Objectives

The purpose of this study was to determine the independent risk factors for bone metastasis in breast cancer and to establish a nomogram to predict the risk of bone metastasis in early stages through clinicopathological characteristics and hematological parameters.

Methods

We selected 1042 patients with breast cancer from the database of Shandong Cancer Hospital for retrospective analysis, and determined independent risk factors for bone metastatic breast cancer (BMBC). A BMBC nomogram based on clinicopathological characteristics and hematological parameters was constructed using logistic regression analysis. The performance of the nomograph was evaluated using the receiver operating characteristic (ROC) and calibration curves. The clinical effect of risk stratification was tested using Kaplan-Meier analysis.

Results

BMBC patients were found to be at risk for eight independent risk factors based on multivariate analysis: age at diagnosis, lymphovascular invasion, pathological stage, pathological node stage, molecular subtype, platelet count/lymphocyte count, platelet count * neutrophil count/lymphocyte count ratio, Systemic Immunological Inflammation Index, and radiotherapy. The prediction accuracy of the BMBC nomogram was good. In the training set, the area under the ROC curve (AUC) was 0.909, and in the validation set, it was 0.926, which proved that our model had good calibration. The risk stratification system can analyze the risk of relapse in individuals into high- and low-risk groups.

Conclusion

The proposed nomogram may predict the possibility of breast cancer bone metastasis, which will help clinicians optimize metastatic breast cancer treatment strategies and monitoring plans to provide patients with better treatment.

Anticancer role of mango (Mangifera indica L.) peel and seed kernel extracts against 7,12- dimethylbenz[a]anthracene-induced mammary carcinogenesis in female rats

Breast cancer is the second leading cause of cancer death among women. The present study is an effort to reveal the antiproliferative and antioxidant actions of mango seed kernel extract (KE), peel extract (PE), and their combination (KEPE) on mammary tumors induced by 7,12 dimethylbenz[a]anthracene (DMBA). Seven groups of adult female Sprague-Dawley rats were prepared, including C: (control), DMBA: (rats were administered with DMBA), (DMBA-KE), (DMBA-PE), and (DMBA-KEPE): rats were administered with DMBA and then treated with KE, PE, and (both KE and PE), respectively, (KE) and (PE): rats were administered with KE and PE, separately. The study focused on the assessment of markers of endocrine derangement [serum 17-β estradiol (E2)], apoptosis [caspase-3 and deoxyribonucleic acid fragmentation (DNAF)], and oxidative stress [lipid peroxidation and antioxidants (glutathione, glutathione-S-transferase, glutathione reductase, glutathione peroxidase, and superoxide dismutase)]. Histopathological examination and immunohistochemical expression of caspase-3 and estrogen receptor-α (ER-α) in mammary gland tissues (MGTs) were determined, as well as the characterization of mango extracts. The results showed that DMBA administration induced mammary tumors by increasing cell proliferation and evading apoptosis. In addition, DMBA administration caused oxidative stress by the production of reactive oxygen species, which increased lipid peroxidation and decreased cellular antioxidants, allowing cancer to progress. In contrast, treatment with DMBA-KE, DMBA-PE, or DMBA-KEPE diminished mammary tumors induced by DMBA, where they reduced oxidative stress via increased antioxidant parameters including reduced glutathione, superoxide dismutase, total glutathione peroxidase, glutathione reductase, and glutathione S-transferase. Also, different treatments decreased proliferation through the reduction of E2, and ER-α expression levels. However, these treatments increased the apoptosis of unwanted cells as they increased caspase-3 activity and DNAF. All these changes led to the prevention of breast injuries and the reduction of mammary tumors. This demonstrates that the contents of mango extracts, especially phenolics and flavonoids, have an important role in mammary tumor treatment through their potential antioxidant, antiproliferative, proapoptotic, and anti-estrogenic effects. KE and PE administration for 4 weeks had no adverse effects. Conclusion: Each of KE, PE, and KEPE has a therapeutic effect against DMBA-induced mammary tumors via induction of apoptosis and reduction of each of the OS, proliferation, and estrogenic effects. So, they can play an important role in the pharmacological tole.

Novel Prognostic Staging System for Patients With De Novo Metastatic Breast Cancer

PURPOSE

Given the heterogeneity and improvement in outcomes for metastatic breast cancer (MBC), we developed a staging system that refines prognostic estimates for patients with metastatic cancer at the time of initial diagnosis, de novo MBC (dnMBC), on the basis of survival outcomes and disease-related variables.

METHODS

Patients with dnMBC (2010-2016) were selected from the National Cancer Database (NCDB). Recursive partitioning analysis (RPA) was used to group patients with similar overall survival (OS) on the basis of clinical T category, grade, estrogen receptor (ER), progesterone receptor, human epidermal growth factor receptor 2, histology, organ system site of metastases (bone-only, brain-only, visceral), and number of organ systems involved. Three-year OS rates were used to assign a final stage: IVA: >70%, IVB: 50%-70%, IVC: 25 to <50%, and IVD: <25%. Bootstrapping was applied with 1,000 iterations, and final stage assignments were made based on the most commonly occurring assignment. Unadjusted OS was estimated. Validation analyses were conducted using SEER and NCDB.

RESULTS

At a median follow-up of 52.9 months, the median OS of the original cohort (N = 42,467) was 35.4 months (95% CI, 34.8 to 35.9). RPA stratified patients into 53 groups with 3-year OS rates ranging from 73.5% to 5.7%; these groups were amalgamated into four stage groups: 3-year OS, A = 73.2%, B = 61.9%, C = 40.1%, and D = 17% (log-rank P < .001). After bootstrapping, the survival outcomes for the four stages remained significantly different (log-rank P < .001). This staging system was then validated using SEER data (N = 20,469) and a separate cohort from the NCDB (N = 7,645) (both log-rank P < .001).

CONCLUSION

Our findings regarding the heterogeneity in outcomes for patients with dnMBC could guide future revisions of the current American Joint Committee on Cancer staging guidelines for patients with newly diagnosed stage IV disease. Our findings should be independently confirmed.

Acquired hyperfibrinolysis as the presenting sign of metastatic breast cancer: A case report

Fibrinolysis is a bleeding disorder characterized by hypofibrinogenemia caused by abnormal activation of fibrinolytic system function. Patients with cancer are prone to hypercoagulable and should be vigilant for the risk of venous thrombosis. However, patients with tumors in which bleeding is the first manifestation are relatively rare. The present study reports the case of a 52-year-old woman with metastatic breast cancer with acquired hyperfibrinolysis as the first manifestation. Hyperfibrinolysis is an important sign and manifestation of disease progression. In this case, fibrinogen was used as a sensitive biomarker of tumor burden to specifically predict the efficacy of the antitumor therapy. Effective antitumor therapy can improve the hyperfibrinolysis of patients, and so the fibrinogen levels gradually increased. In conclusion, the present case showed acquired hyperfibrinolysis with bleeding symptoms, which is an uncommon paraneoplastic phenomenon in breast cancer, especially when combined with bone marrow metastasis, as in the present case. Timely diagnosis and treatment of the primary disease is the fundamental way to improve hyperfibrinolysis. As an effective biomarker, fibrinogen level predicts the changes in a patient's illness and guides the clinical diagnosis and treatment process.

Stage-Specific Survival in Breast Cancer in Chinese and White Women: Comparative Data Analysis

BACKGROUND

Stage-specific survival, according to the eighth edition of the American Joint Committee on Cancer (AJCC) pathological prognostic staging (PPS) on breast cancer (BC), between Chinese and White American women remains unclear.

OBJECTIVE

This study aimed to assess stage-specific survival in BC between Chinese and White American women according to the eighth AJCC PPS.

METHODS

We included Chinese and White American women with BC diagnosed between 2010 and 2018 from the Surveillance, Epidemiology, and End Results database. A chi-square test, the Kaplan-Meier method, a receiver operating characteristic (ROC) curve, and multivariate Cox proportional hazards models were used for data analysis.

RESULTS

We included 376,818 individuals in this study: 369,522 White American and 7296 Chinese. Of them, 149,452 (39.7%) migrated from the seventh AJCC anatomic staging (AS) to the eighth AJCC PPS, 22,516 (6.0%) were upstaged, and 126,936 (33.7%) were downstaged. With a median follow-up duration of 44 months, the 5-year overall survival and cancer-specific survival (CSS) for the entire group were 87.4% and 95.9%, respectively. The seventh AJCC AS (P<.001) and the eighth AJCC PPS (P<.001) could significantly predict the survival outcomes of BC, and multivariate analysis revealed that both staging systems were significant prognostic indicators of CSS. The ROC curve revealed that the PPS had a better discriminating ability than the AS (area under the curve [AUC] 0.769 vs 0.753, P<.001). Similar trends were observed after stratification by the 2 ethnic groups. The eighth AJCC PPS had better discriminating ability than the seventh AJCC AS among both White American (AUC 0.769 vs 0.753, P<.001) and Chinese patients (AUC 0.790 vs 0.776, P<.001). In the seventh AJCC AS, Chinese women had better CSS in stage IA (P=.02), stage IIA (P=.005), and stage IIIB (P=.04) disease than White American women, but no significant CSS was observed in stage IB, IIB, IIIA, and IIIC disease between the 2 ethnic groups. Regarding the eighth AJCC PPS, Chinese women had better CSS in stage IA (P=.002) and IIIA (P=.046) disease than White American women, and CSS was similar in Chinese and White American women in other substages.

CONCLUSIONS

The eighth AJCC PPS has a similar discriminative ability between White American and Chinese individuals with BC compared with the seventh AJCC AS. Therefore, the eighth AJCC PPS is also applicable to Chinese individuals with BC.

Identification of molecular subtypes and a six-gene risk model related to cuproptosis for triple negative breast cancer

Background: Breast cancer is the mostly diagnosed cancer worldwide, and triple negative breast cancer (TNBC) has the worst prognosis. Cuproptosis is a newly identified form of cell death, whose mechanism has not been fully explored in TNBC. This study thought to unveil the potential association between cuproptosis and TNBC. Materials and Methods: Gene expression files with clinical data of TNBC downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were included in this study. Consensus clustering was utilized to perform molecular subtyping based on cuproptosis-associated genes. Limma package was applied to distinguish differentially expressed genes. Univariate Cox regression was used to identify prognostic genes. Least absolute shrinkage and selection operator and stepwise Akaike information criterion optimized and established a risk model. Results: We constructed three molecular subtypes based on cuproptosis-associated genes, and the cuproptosis-based subtyping showed a robustness in different datasets. Clust2 showed the worst prognosis and immune-related pathways such as chemokine signaling pathway were significantly activated in clust2. Clust2 also exhibited a high possibility of immune escape to immune checkpoint blockade. In addition, a six-gene risk model was established manifesting a high AUC score over 0.85 in TCGA dataset. High- and low-risk groups had distinct prognosis and immune infiltration. Finally, a nomogram was constructed with strong performance in predicting TNBC prognosis than the staging system. Conclusion: The molecular subtyping system related to cuproptosis had a potential in guiding immunotherapy for TNBC patients. Importantly, the six-gene risk model was effective and reliable to predict TNBC prognosis.

A Prognostic Model Based on Nutritional Risk Index in Operative Breast Cancer

Background: The nutritional risk index (NRI) is an independent prognostic factor for overall survival in various cancers, but its prognostic value in breast cancer remains unclear. This study aimed to explore the relationship between the NRI and overall survival (OS) in breast cancer and to develop a predictive nomogram. Methods: We retrospectively enrolled 1347 breast cancer patients who underwent mastectomy or lumpectomy between January 2011 and November 2012. Using a cutoff value of 110.59, patients were divided into a high-NRI group and a low-NRI group. OS was compared between the two groups. Clinicopathological factors independently associated with survival were used to construct a predictive nomogram. Results: Of the 1347 patients, 534 patients were classified as high NRI and 813 as low NRI. OS was significantly shorter in low-NRI patients. The 3- and 5-year OS rates were 87.3% and 73.4%, respectively, in the high-NRI group whereas they were 83.0% and 67.2%, respectively, in the low-NRI group. Cox regression analysis found that histopathological type, tumor size, lymph node status, progesterone receptor (PR) status, Ki-67, and NRI were independently associated with OS. Conclusions: NRI is an independent prognostic factor of OS in breast cancer patients. The proposed nomogram model may be a useful tool for individualized survival prediction.

Clinical subtype, treatment response, and survival in De Novo and recurrent metastatic breast cancer

PURPOSE

This study evaluated whether patients with de novo metastatic breast cancer (MBC) have superior outcomes compared to those with recurrent MBC in a contemporary treatment era and examined factors related to outcome differentials.

METHODS

Using an institutional database, we examined patient and tumor characteristics, treatment response, and outcome among 232 patients with de novo and 612 patients with recurrent MBC diagnosed between 2011 and 2017.

RESULTS

De novo MBC had 9-month (m) longer overall survival (OS) than recurrent MBC (36.4 vs 27.4 m, p < 0.001). Contributions to this difference included nearly twofold more HER2-positive (29.3% vs 15.2%) and significantly fewer triple-negative breast cancers (20.3% vs 32.4%, both p < 0.001) in de novo compared with recurrent MBC cohorts. Stratified by clinical subtype, progression-free survival (PFS) on first-line therapy was significantly longer in de novo MBC in all but the triple-negative subtype, 25.5 vs 11.6 m (p < 0.001) among 390 patients with hormone receptor-positive, HER2-negative, 11.4 vs 5.4 m (p = 0.002) among 142 patients with HER2-positive, and 4.0 vs 3.0 m (p = 0.121) among 162 with triple-negative MBC. In multivariable analysis, de novo status remained independently associated with improved OS (hazard ratio 0.63, 95% CI 0.49-0.80), regardless of subtype and other features.

CONCLUSION

Patients with de novo MBC have better outcomes than those with recurrent MBC. Differences in clinical subtype and response to therapy in the metastatic setting contribute to, but do not fully explain, this difference. Longer PFS to first-line therapy in de novo MBC suggests biologic differences compared to recurrent MBC, which may be intrinsic or due to acquired resistance from treatment for prior localized breast cancer in recurrent disease.

Stealth Liposomal Chemotherapeutic Agent for Triple Negative Breast Cancer with Improved Pharmacokinetics

Triple-negative breast cancer is one of the most lethal cancers. Chemotherapeutics for targeting CDK4 and CDK6 like Palbociclib (PAB) in triple-negative breast cancer was widely explored. However, poor bioavailability and severe side effects profile limiting its clinical usage in the field of cancer chemotherapy. Herein, we set out to develop the stealth liposomes (LPS) of PAB by rotary thin film evaporation with a vesicle size of less than 100 nm. In vitro, drug release studies were performed and fitted into different release kinetic models. LPS were characterized by electron microscopic techniques for morphology. The engineered nanotherapeutics agents were further evaluated in 4T1 triple-negative breast cancer cell lines for its anti-cancer potential and cellular uptake. The hemolytic potential and pharmacokinetic (PK) behavior of developed LPS-PAB and PAB were analyzed by using robust UHPLC-QTOF-MS method. LPS-PAB demonstrates biphasic release profile with first-order release kinetics. Further, LPS-PAB has shown less IC50 value (1.99 µM) compared to PAB alone (3.24 µM). The designed nanoliposomes were tagged with fluorescent FITC dye to check rapid cellular uptake. Importantly, stealth LPS-PAB has shown a 1.75-fold reduction in hemolytic potential as compared to PAB plain drug at 100 µg/mL concentration. The PK results obtained was displayed 2.5-fold increase in Cmax, 1.45-fold increase in AUCtot, 1.8-fold increase in half-life and 1.3-fold increase in MRT with LPS-PAB when compared to orally administered PAB suspension. These findings suggest that novel LPS-PAB can be employed as an alternate therapeutic strategy to eradicate triple-negative breast cancer.

Expanding the Staging Criteria for T1-2N0 Hormone-Receptor Positive Breast Cancer Patients Enrolled in TAILORx

BACKGROUND

The American Joint Committee on Cancer (AJCC) 8th edition pathologic prognostic staging (PPS) incorporates anatomic and biologic factors. The OncotypeDX Breast Recurrence Score (RS) was included based on the initial report of the TAILORx trial, with T1-2N0 hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) breast cancer patients who had a RS < 11 staged as PPS 1A. This study examined whether the RS criteria for PPS 1A can be further expanded using patients enrolled in the TAILORx trial.

METHODS

The TAILORx trial enrolled 10,273 HR+HER2- T1-2N0 patients. Those with incomplete HR-status/grade and T3 disease were excluded for analysis. The recurrence-free interval (RFI) was compared between the patients who did and those who did not fall into the current PPS 1A category using the Kaplan-Meier method.

RESULTS

The study enrolled 9535 patients for analysis. The RS was < 11 in 16.1%, 11-17 in 35.9%, 18-25 in 32.4%, and > 25 in 15.6% of the patients. The majority (91.2%) of the patients (including all the T1N0 patients regardless of RS) were PPS 1A, and 8.8% were not-PPS 1A. The median follow-up time was 95 months. The PPS 1A patients had an 8-year RFI of 94.2%, which was similar to that of the patients with a RS of 11-17 who were not-PPS 1A (91.7%; p = 0.07) and better than that of the patients with a RS ≥ 18 who were not-PPS 1A (85.4% for a RS of 18-25, 76.0% for a RS > 25; both p < 0.01). Similar RFI trends were seen in patients who received endocrine therapy or chemotherapy followed by endocrine therapy.

CONCLUSIONS

Patients with T1-2N0 HR+HER2- breast cancer and a RS < 18 have an RFI similar to that of patients staged as PPS 1A by the current AJCC staging system, regardless of treatment, suggesting that the criteria for PPS 1A can be expanded to include a RS < 18.

Survival Nomogram for Young Breast Cancer Patients Based on the SEER Database and an External Validation Cohort

Background

Young breast cancer (YBC) patients are more prone to lymph node metastasis than other age groups. Our study aimed to investigate the predictive value of lymph node ratio (LNR) in YBC patients and create a nomogram to predict overall survival (OS), thus helping clinical diagnosis and treatment.

Methods

Patients diagnosed with YBC between January 2010 and December 2015 from the Surveillance, Epidemiology, and End Results (SEER) database were enrolled and randomly divided into a training set and an internal validation set with a ratio of 7:3. An independent cohort from our hospital was used for external validation. Univariate and least absolute shrinkage and selection operator (LASSO) regression were used to identify the significant factors associated with prognosis, which were used to create a nomogram for predicting 3- and 5-year OS.

Results

We selected seven survival predictors (tumor grade, T-stage, N-stage, LNR, ER status, PR status, HER2 status) for nomogram construction. The C-indexes in the training set, the internal validation set, and the external validation set were 0.775, 0.778 and 0.817, respectively. The nomogram model was well calibrated, and the time-dependent ROC curves verified the superiority of our model for clinical usefulness. In addition, the nomogram classification could more precisely differentiate risk subgroups and improve the discrimination of YBC prognosis.

Conclusions

LNR is a strong predictor of OS in YBC patients. The novel nomogram based on LNR is a reliable tool to predict survival, which may assist clinicians in identifying high-risk patients and devising individual treatments.

The Predictive Effect of the 8th AJCC Pathological Prognostic Staging on the Benefit of Postmastectomy Radiotherapy in N2/N3 Breast Cancer

Background

The role of the 8th American Joint Committee on Cancer (AJCC) pathological prognostic staging (PPS) on treatment-decision making of breast cancer (BC) remains unclear. This study aimed to investigate the predictive effect of the 8th AJCC PPS on the benefit of postmastectomy radiotherapy (PMRT) in N2/N3 BC.

Methods

We included women with stage N2/3 BC diagnosed between 2010 and 2018 from the Surveillance, Epidemiology, and End Results database. The effect of PMRT on breast cancer-specific survival (BCSS) was evaluated using the multivariate Cox proportional-hazards models.

Results

A total of 13,445 patients were identified, including 10,547 (78.4%) patients treated with PMRT. All patients had reassigned stages based on the 8th AJCC PPS. There were 7102 patients (52.8%) that had stage changed, including 1160 patients (8.6%) were upstaged and 5942 patients (44.2%) were downstaged from the 7th AJCC anatomical staging (AS) to the 8th AJCC PPS. Regarding the 7th AJCC AS, 7603 (56.5%), 948 (7.1%), and 4895 (36.4%) were stage IIIA, IIIB, and IIIC diseases, respectively. Using the 8th AJCC PPS, 3525 (26.2%), 460 (3.4%), 1335 (9.9%), 3457 (25.7%), 2169 (19.1%), and 2100 (15.6%) patients were restaged as IB, IIA, IIB, IIIA, IIIB, and IIIC diseases, respectively. The PPS displayed increased prognostic accuracy and improved model fit with respect to BCSS compared to the 7th AS (C-index, 0.731 vs 0.605, P < 0.001; Akaike Information Criterion, 42141 vs 43118). Regarding the AS, the receipt of PMRT was associated with a better BCSS in those with stage IIIA (P = 0.004), IIIB (P = 0.003), and IIIC (P < 0.001) diseases. Using the PPS, the receipt of PMRT was not associated with a better BCSS among patients with stage IB (P = 0.446), IIA (P = 0.140), and IIB (P = 0.248) disease, while the receipt of PMRT was associated with a better BCSS for those with stage IIIA (P = 0.009), IIIB (P < 0.001), and IIIC (P < 0.001) disease.

Conclusion

The 8th AJCC staging provides superior risk stratification and a better tool to predict the benefit of PMRT in N2/3 BC.

Emerging Technologies for the Detection of Cancer Micrometastasis

The most efficient way to treat tumors is through surgery. However, many cancer patients have a poor prognosis even when they undergo radical excision at an early stage. Micrometastasis is one of the most critical factors that induced this situation. Undetected micrometastasis can lead to the failure of initial treatment. Therefore, preoperative and intraoperative detection of micrometastasis could have a significant clinical influence on the prognosis and optimal therapy for cancer patients. Additionally, to achieve this goal, researchers have aimed to create more effective detection technologies. Herein, we classify the currently reported micrometastasis detection technologies, introduce some representative samples for each technology, including the limitations, and provide future directions to overcome the limitations.

Conjoint analysis of circulating tumor cells and solid tumors for exploring potential prognostic markers and constructing a robust novel predictive signature for breast cancer

Background

Distance metastasis is the leading cause of death for breast cancer patients, and circulating tumor cells (CTCs) play a key role in cancer metastasis. There have been few studies on CTCs at the molecular level due to their rarity, and the heterogeneity of CTCs may provide special information for solid tumor analysis.

Methods

In this study, we used the gene expression and clinical information of single-cell RNA-seq data of CTCs of breast cancer and discovered a cluster of epithelial cells that had more aggressive characteristics. The differentially expressed genes (DEGs) between the identified epithelial cells cluster and others from single-CTCs were selected for further analysis in bulk sequence data of solid breast cancers.

Results

Eighteen genes closely related to the specific CTC epithelial phenotype and breast cancer patient prognosis were identified. Among these 18 genes, we selected the GARS gene, which has not been studied in breast cancer, for functional research and confirmed that it may be a potential oncogene in breast cancer. A risk score was established by the 18 genes, and a high-risk score was strongly associated with a high metastasis rate and poor survival prognosis in breast cancer. The high-risk score group was related to a defective immune infiltration environment in breast cancer, and the immune checkpoint therapy response rate was lower in this group. The drug-sensitive analysis shows that the high-risk score patients may be more sensitive to AKT-mTOR and the cyclin-dependent kinase (CDK) pathways drugs than low-risk score patients.

Conclusions

Our 18-gene risk score shows good prognostic and predictive values and might be a personalized prognostic marker or therapy guide marker in breast cancer patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02415-8.

Prognostic Factors and a Nomogram Predicting Survival in Patients with Breast Ductal Carcinoma in situ with Microinvasion: A Population-Based Study

Purpose

Ductal carcinoma in situ with microinvasion (DCISM) can be challenging to balance the risks of overtreatment versus undertreatment. We aim to identify prognostic factors in patients with DCISM and construct a nomogram to predict breast cancer-specific survival (BCSS).

Materials and Methods

A retrospective cohort study of women diagnosed with DCISM from 1988 to 2015 who were identified in the Surveillance, Epidemiology and End Results database. Clinical variables and tumor characteristics were evaluated, and Cox proportional-hazards regression was performed. A nomogram was constructed from the multivariate logistic regression to combine all the prognostic factors to predict the prognosis of DCISM patients at 5 years, 10 years, and 15 years.

Results

We identified 5438 total eligible breast cancer patients with a median and max survival time of 78 and 227 months, respectively. Here, patients with poorer survival outcomes were those diagnosed between 1988 and 2001, African-American race, under 40 years of age, higher tumor N stage, progesterone receptor-negative tumor, and received no surgery. The nomogram was constructed by the seven variables and passed the calibration and validation steps. The area under the receiver operating characteristic (ROC) curve (AUC) of both the training set and the validating set (5-year AUC: 0.77 and 0.88, 10-year AUC: 0.75 and 0.73, 15-year AUC: 0.72 and 0.65). Receiving chemotherapy was associated with a better BCSS (hazard ratio, HR=0.45, 95% confidence interval, 95% CI = 0.23–0.89), especially in patients with estrogen receptor (ER) negative, progesterone receptor (PR) negative (HR = 0.35, 95% CI = 0.13–0.97) and ER+PR-/ER-PR+ DCISM (HR = 0.07, 95% CI = 0.01–0.59).

Conclusion

Our current study is the first to construct nomograms of patients with DCISM which could help physicians identify breast cancer patients that more likely to benefit from more intensive treatment and follow-up. Chemotherapy might benefit patients with ER-PR- and ER+PR-/ER-PR+ DCISM.

Validation of the Eighth American Joint Committee on Cancer Anatomic and Prognostic Staging System for Breast Cancer

BACKGROUND

The eighth edition of new staging systems for breast cancer incorporated four biological factors and the anatomic staging system. Validating analysis on Chinese patients has been limited. Our study performed analysis comparing the prognostic value of the staging system based on Chinese data.

METHODS AND MATERIALS

All patients were classified according to the eighth edition and compared between anatomic and prognostic staging systems. The Kaplan-Meier test was used to calculate the overall survival (OS) and disease-free survival (DFS). We performed Harrell concordance index (C-index) analyses to quantify a models' predictive performance. Akaike information criterion (AIC) via Cox regression analysis was used to conduct bootstrap-based goodness-of-fit comparisons of the competing staging systems.

RESULTS

A total of 1556 patients were enrolled in the cohort. The median follow-up time was 76 mo (range, 4-146 mo), the median age was 48 y old (range, 21-87 y). The ratio of movement between anatomic stage (AS) and prognostic stage (PS) was 50.9%. Of these, 691 (44.5%) AS patients were down staged and 100 (6.4%) patients were upstaged when reclassified based on PS. Significant differences between two stages were achieved for stage IIIC in 5-y OS rates and for IIIB in 5-y DFS rates (63.5% versus 50.0% and 58.0% versus44.0%). The value of the C-index for PS and AS were 0.711 and 0.687 (P = 0.04). The AIC reaches a value of 3452.9 for the PS and a value of 3476.4 for the AS.

CONCLUSIONS

The PS might provide better accuracy than the AS in predicting the prognosis of Chinese female breast cancer patients. It also provides a strong basis for the utility of clinical biomarkers to evaluate the prognosis of patients.

Construction and Validation of a Nomogram to Predict Overall Survival in Very Young Female Patients with Curatively Resected Breast Cancer

Purpose

Young age is an independent negative predictor of breast cancer (BC) survival and correlates with the risk of local recurrence and contralateral BC. We aimed to design an effective and comprehensive nomogram to predict prognosis in very young patients with curatively resected BC.

Methods

Female patients with a diagnosis of BC aged ≤35 years at presentation were identified from the SEER database as a training cohort. The validation cohort consisted of 1002 consecutive women with BC aged ≤35 years that had received curative resection for BC at the Sun Yat-sen University Cancer Center. A nomogram was built based on the identified variables in multivariate Cox proportional hazards model. The performance of the nomogram was quantified using Harrell’s concordance index (C-index) and calibration curves.

Results

Overall, 10,872 young female patients who underwent surgery for BC were enrolled in the training cohort, while 1002 very young female BC patients were identified as independent validation cohort. Eight covariables (age, race, grade; ER, PR, and HER2 status; T, and N stages) were identified and incorporated to construct a nomogram. The C-index values of the nomogram were 0.727 (95% CI: 0.714–0.740) and 0.722 (95% CI: 0.666–0.778) for OS in the training and validation cohorts, respectively. The calibration curves showed a high degree of agreement between the predicted and actual observed survival rates in both training and validation cohorts. The nomogram displayed good calibration and acceptable discrimination. Based on the TPS of the nomogram model for OS with the X-tile program, patients were divided into 3 risk groups, which were easily discriminated on survival analyses for OS.

Conclusion

We have successfully constructed an effective nomogram to predict survival outcomes for young female patients with curatively resected BC, which may provide individual survival prediction to benefit prognosis evaluation and individualized therapy.

Prognostic Model for De Novo and Recurrent Metastatic Breast Cancer

PURPOSE

Metastatic breast cancer (MBC) has a heterogeneous clinical course. We sought to develop a prognostic model for overall survival (OS) that incorporated contemporary tumor and clinical factors for estimating individual prognosis.

METHODS

We identified patients with MBC from our institution diagnosed between 1998 and 2017. We developed OS prognostic models by Cox regression using demographic, tumor, and treatment variables. We assessed model predictive accuracy and estimated annual OS probabilities. We evaluated model discrimination and prediction calibration using an external validation data set from the National Comprehensive Cancer Network.

RESULTS

We identified 10,655 patients. A model using age at diagnosis, race or ethnicity, hormone receptor and human epidermal growth factor receptor 2 subtype, de novo versus recurrent MBC categorized by metastasis-free interval, Karnofsky performance status, organ involvement, frontline biotherapy, frontline hormone therapy, and the interaction between variables significantly improved predictive accuracy (C-index, 0.731; 95% CI, 0.724 to 0.739) compared with a model with only hormone receptor and human epidermal growth factor receptor 2 status (C-index, 0.617; 95% CI, 0.609 to 0.626). The extended Cox regression model consisting of six independent models, for < 3, 3-14, 14-20, 20-33, 33-61, and ≥ 61 months, estimated up to 5 years of annual OS probabilities. The selected multifactor model had good discriminative ability but suboptimal calibration in the group of 2,334 National Comprehensive Cancer Network patients. A recalibration model that replaced the baseline survival function with the average of those from the training and validation data improved predictions across both data sets.

CONCLUSION

We have generated and validated a robust prognostic OS model for MBC. This model can be used in clinical decision making and stratification in clinical trials.

Racial and Socioeconomic Disparities in Breast Cancer Outcomes within the AJCC Pathologic Prognostic Staging System

BACKGROUND

Non-Hispanic black (NHB) women and those of lower socioeconomic status (SES) have inferior breast cancer outcomes compared with non-Hispanic white (NHW) women and those of higher SES. We examined racial and SES disparities in breast cancer survival within the AJCC 8th edition pathologic prognostic staging system.

METHODS

Using the Surveillance, Epidemiology and End Results Program, we identified patients diagnosed with invasive breast cancer from 2010 to 2015, with follow-up through 2016. Census tract-level SES (cSES) data were available as a composite index and analyzed in quintiles. Cox proportional-hazards survival analyses adjusted for age, race, cSES, insurance, marital status, histology, pathologic prognostic stage, and treatment were used to estimate disease-specific survival (DSS).

RESULTS

A total of 259,852 patients were included: 176,369 (67.9%) NHW; 28,510 (11.0%) NHB; 29,737 (11.4%) Hispanic; and 22,887 (8.8%) Asian. NHB race and lower cSES were associated with increased incidence of triple-negative disease compared with NHW (p < 0.01). NHB race, lower cSES, public insurance, lower education, and increased poverty were associated with lower DSS. Survival analyses adjusting for cSES, tumor, and treatment characteristics demonstrated that NHB patients had inferior DSS within each AJCC pathologic prognostic stage (hazard ratio [HR] 1.25, 95% confidence interval [CI] 1.20-1.30) compared with NHW patients. Fully adjusted models also showed patients residing in lower SES counties had inferior DSS.

CONCLUSIONS

Racial and cSES disparities in breast cancer-specific mortality were evident across all stages, even within the pathologic prognostic staging system which incorporates tumor biology. Future efforts should assess the biological, behavioral, social, and environmental determinants that underlie racial and SES inequities in outcomes.

Clinical and Genetic Predictive Models for the Prediction of Pathological Complete Response to Optimize the Effectiveness for Trastuzumab Based Chemotherapy

Background

Trastuzumab shows excellent benefits for HER2+ breast cancer patients, although 20% treated remain unresponsive. We conducted a retrospective cohort study to optimize neoadjuvant chemotherapy and trastuzumab treatment in HER2+ breast cancer patients.

Methods

Six hundred patients were analyzed to identify clinical characteristics of those not achieving a pathological complete response (pCR) to develop a clinical predictive model. Available RNA sequence data was also reviewed to develop a genetic model for pCR.

Results

The pCR rate was 39.8% and pCR was associated with superior disease free survival and overall survival. ER negativity and PR negativity, higher HER2 IHC scores, higher Ki-67, and trastuzumab use were associated with improved pCR. Weekly paclitaxel and carboplatin had the highest pCR rate (46.70%) and the anthracycline+taxanes regimen had the lowest rate (11.11%). Four published GEO datasets were analyzed and a 10-gene model and immune signature for pCR were developed. Non-pCR patients were ER⁺PR⁺ and had a lower immune signature and gene model score. Hormone receptor status and immune signatures were independent predictive factors of pCR.

Conclusion

Hormone receptor status and a 10-gene model could predict pCR independently and may be applied for patient selection and drug effectiveness optimization.

A Nomogram for Predicting Survival in Patients With Breast Cancer Liver Metastasis: A Population-Based Study

Objective

The prognosis of patients with breast cancer liver metastasis (BCLM) was poor. We aimed at constructing a nomogram to predict overall survival (OS) for BCLM patients using the SEER (Surveillance Epidemiology and End Results) database, thus choosing an optimized therapeutic regimen to treat.

Methods

We identified 1173 patients with BCLM from the SEER database and randomly divided them into training (n=824) and testing (n=349) cohorts. The Cox proportional hazards model was applied to identify independent prognostic factors for BCLM, based on which a nomogram was constructed to predict 1-, 2-, and 3-year OS. Its discrimination and calibration were evaluated by the Concordance index (C-index) and calibration plots, while the accuracy and benefits were assessed by comparing it to AJCC-TNM staging system using the decision curve analysis (DCA). Kaplan-Meier survival analyses were applied to test the clinical utility of the risk stratification system.

Results

Grade, marital status, surgery, radiation therapy, chemotherapy, CS tumor size, tumor subtypes, bone metastatic, brain metastatic, and lung metastatic were identified to be independent prognostic factors of OS. In comparison with the AJCC-TNM staging system, an improved C-index was obtained (training group: 0.701 vs. 0.557, validation group: 0.634 vs. 0.557). The calibration curves were consistent between nomogram-predicted survival probability and actual survival probability. Additionally, the DCA curves yielded larger net benefits than the AJCC-TNM staging system. Finally, the risk stratification system can significantly distinguish the ones with different survival risk based on the different molecular subtypes.

Conclusion

We have successfully built an effective nomogram and risk stratification system to predict OS in BCLM patients, which can assist clinicians in choosing the appropriate treatment strategies for individual BCLM patients.

Expanding Criteria for Prognostic Stage IA in Hormone Receptor-Positive Breast Cancer

BACKGROUND

The prognostic significance of patients with low-risk recurrence score (RS) results in the context of the American Joint Committee on Cancer (AJCC) eighth edition pathologic prognostic staging has not been investigated. We evaluated if expanded RS criteria can be considered for downstaging in AJCC pathologic prognostic staging.

METHODS

Using Surveillance, Epidemiology, and End Results data, we identified patients with T1-3N0-3M0 hormone receptor-positive, HER2-negative breast cancer treated from 2010 to 2015 with follow-up data through 2016. We evaluated TNM categories, grade, and RS result. The primary outcome measured was 5-year disease-specific survival (DSS) of patients with low-risk RS results not already pathologic prognostic stage IA, determined by T and N categories per AJCC eighth edition. All statistical tests were 2-sided.

RESULTS

Of 154 050 patients with median follow-up of 49 months (range = 0-83), RS results were obtained in 60 886 (39.5%): RS was less than 11 in 13 570 (22.3%); 11-17 in 22 719 (37.3%); 18-25 in 16 521 (27.1%); and 26 or higher in 8076 (13.3%). Five-year DSS for pathologic prognostic stage IA patients (n = 114 910, 74.6%) was 98.8%. Among N0-1 patients with a RS less than 18 not staged as pathologic prognostic stage IA by current criteria, 5-year DSS was excellent and not statistically significantly different than for pathologic prognostic stage IA patients (97.2%-99.7%; P > .05). For those with a RS of 18-25, there was a small decrease in DSS for T2N0 (2.3%) and modest decrease for T1-2N1 (4.2%-6.4%) compared with pathologic prognostic stage IA patients (P < .001).

CONCLUSION

Patients with a RS less than 18 have excellent 5-year DSS regardless of T category for N0-1 disease suggesting further modification of the AJCC staging system using this cutoff.

The Will Rogers phenomenon, breast cancer and race

BACKGROUND

The Will Rogers phenomenon [WRP] describes an apparent improvement in outcome for patients' group due to tumor grade reclassification. Staging of cancers is important to select appropriate treatment and to estimate prognosis. The WRP has been described as one of the most important biases limiting the use of historical cohorts when comparing survival or treatment. The main purpose of this study is to assess whether the WRP exists with the move from the AJCC 7th to AJCC 8th edition in breast cancer [BC] staging, and if racial differences are manifested in the expression of the WRP.

METHODS

This is a retrospective analysis of 300 BC women (2007-2017) at an academic medical center. Overall survival [OS] and disease-free survival [DFS] was estimated by Kaplan-Meier analysis. Bi and multi-variate Cox regression analyses was used to identify racial factors associated with outcomes.

RESULTS

Our patient cohort included 30.3% Caucasians [Whites] and 69.7% African-Americans [Blacks]. Stages I, II, III, and IV were 46.2, 26.3, 23.1, and 4.4% of Whites; 28.7, 43.1, 24.4, and 3.8% of Blacks respectively, in anatomic staging (p = 0.043). In prognostic staging, 52.8, 18.7, 23, and 5.5% were Whites while 35, 17.2, 43.5, and 4.3% were Blacks, respectively (p = 0.011). A total of Whites (45.05% vs. 47.85%) Blacks, upstaged. Whites (16.49% vs. 14.35%) Blacks, downstaged. The remaining, 38.46 and 37.79% patients had their stages unchanged. With a median follow-up of 54 months, the Black patients showed better stage-by-stage 5-year OS rates using 8th edition compared to the 7th edition (p = 0.000). Among the Whites, those who were stage IIIA in the 7th but became stage IB in the 8th had a better prognosis than stages IIA and IIB in the 8th (p = 0.000). The 8th showed complex results (p = 0.176) compared to DFS estimated using the 7th edition (p = 0.004).

CONCLUSION

The WRP exists with significant variability in the move from the AJCC 7th to the 8th edition in BC staging (both White and Black patients). We suggest that caution needs to be exercised when results are compared across staging systems to account for the WRP in the interpretation of the data.

Comparison of Breast Cancer Staging Systems After Neoadjuvant Chemotherapy

BACKGROUND

No consensus exists for optimal staging following neoadjuvant chemotherapy (NAC). We compared the performance of the American Joint Committee on Cancer (AJCC) pathologic prognostic staging system, Residual Cancer Burden (RCB) Index, and the Neo-Bioscore in breast cancer patients after NAC.

METHODS

Patients with stage I-III breast cancer who received NAC at Dana-Farber Cancer Institute from 2004 to 2014 were identified. Kaplan-Meier curves were used to estimate disease-free survival (DFS) and overall survival (OS), and model fits were compared by receiver operator characteristic (ROC) curve using the c-statistic and DeLong's test.

RESULTS

Overall, 802 patients with a median age of 48 years received NAC. Most patients presented with cT2 (n = 470, 58.6%) and cN1 (n = 422, 52.6%) disease. The subtype was estrogen receptor (ER)- and/or progesterone receptor (PR)-positive/human epidermal growth factor receptor 2 (HER2)-negative in 296 (36.9%) patients, HER2-positive in 261 (32.5%) patients, and triple-negative in 245 (30.5%) patients. Median follow-up was 79.5 months. There were 174 recurrences (30 local, 25 regional, 145 distant), with 676 (76.8%) patients alive at last follow-up. AJCC pathologic prognostic staging and RCB had better discrimination for estimated 7-year DFS and OS compared with the Neo-Bioscore. The ROC c-statistics for DFS model fit were similar for AJCC pathologic prognostic stage (0.72) and RCB (0.71, p = non-significant); both had improved model fit versus the Neo-Bioscore (0.65, p < 0.01). The c-statistics for OS were 0.74, 0.71, and 0.70 for AJCC pathologic prognostic stage, RCB, and Neo-Bioscore, respectively (p = non-significant).

CONCLUSIONS

These results validate the ability of these staging systems to stratify survival outcomes in NAC patients, with best discrimination achieved using AJCC pathologic prognostic stage or RCB.

Establishment of a Macrophage Phenotypic Switch Related Prognostic Signature in Patients With Pancreatic Cancer

Introduction

Macrophage phenotype switch plays a vital role in the progression of malignancies. We aimed to build a prognostic signature by exploring the expression pattern of macrophage phenotypic switch related genes (MRGs) in the Cancer Genome Atlas (TCGA)—pancreatic adenocarcinoma (PAAD), Genotype-Tissue Expression (GTEx)-Pancreas, and Gene Expression Omnibus (GEO) databases.

Methods

We identified the differentially expressed genes between the PAAD and normal tissues. We used single factor Cox proportional risk regression analysis, Least Absolute Shrinkage and Selection Operator (LASSO) analysis, and multivariate Cox proportional hazard regression analysis to establish the prognosis risk score by the MRGs. The relationships between the risk score and immune landscape, “key driver” mutations and clinicopathological factors were also analyzed. Gene-set enrichment analysis (GSEA) analysis was also performed.

Results

We detected 198 differentially expressed MRGs. The risk score was constructed based on 9 genes (KIF23, BIN1, LAPTM4A, ERAP2, ATP8B2, FAM118A, RGS16, ELMO1, RAPGEFL1). The median overall survival time of patients in the low-risk group was significantly longer than that of patients in the high-risk group (P < 0.001). The prognostic value of the risk score was validated in GSE62452 dataset. The prognostic performance of nomogram based on risk score was superior to that of TNM stage. And GSEA analysis also showed that the risk score was closely related with P53 signaling pathway, pancreatic cancer and T cell receptor signaling pathway. qRT-PCR assay showed that the expressions of the 9 MRGs in PDAC cell lines were higher than those in human pancreatic ductal epithelium cell line.

Conclusions

The nine gene risk score could be used as an independent prognostic index for PAAD patients. Further studies validating the prognostic value of the risk score are warranted.

Refining breast cancer prognosis by incorporating age at diagnosis into clinical prognostic staging: introduction of a novel online calculator

PURPOSE

American Joint Committee on Cancer (AJCC) clinical staging is used to estimate breast cancer prognosis, but individual patient survival within each stage varies considerably by age at diagnosis. We hypothesized that the addition of age at diagnosis to the staging schema will enable more refined risk stratification.

METHODS

We performed a retrospective population analysis of adult women diagnosed with invasive breast cancer between 2010 and 2015 registered in SEER. Multivariable Cox hazards models were used to evaluate the association of AJCC 8th edition clinical prognostic stage (CPS) and age with risk of overall mortality. Separate hierarchical models were fit to the data: Model 1: CPS alone; Model 2: CPS + age + age²; and Model 3: CPS + age + age² + CPS x age + CPS x age². Models were compared by the Akaike information criterion (AIC), the c-statistic for time-dependent receiver operator characteristic curves, and category-free net reclassification improvement (NRI). Internal validation was performed using bootstrapping samples.

RESULTS

Among 86,637 women, the median follow-up was 36 months and 3-year overall survival was 91.9% ± 0.1%. Age significantly modified the effect of CPS on survival (p < 0.0001). Model 3 was the most precise, with the lowest AIC (126,619.63), the highest c-statistic (0.8212, standard error 0.0187), and superior NRI indices.

CONCLUSION

Age at diagnosis is a highly prognostic variable that warrants consideration for inclusion in future editions of the AJCC Breast Cancer Staging Manual.

Pretransplant solid organ malignancy and organ transplant candidacy: A consensus expert opinion statement

Patients undergoing evaluation for solid organ transplantation (SOT) often have a history of malignancy. Although the cancer has been treated in these patients, the benefits of transplantation need to be balanced against the risk of tumor recurrence, especially in the setting of immunosuppression. Prior guidelines of when to transplant patients with a prior treated malignancy do not take in to account current staging, disease biology, or advances in cancer treatments. To develop contemporary recommendations, the American Society of Transplantation held a consensus workshop to perform a comprehensive review of current literature regarding cancer therapies, cancer stage-specific prognosis, the kinetics of cancer recurrence, and the limited data on the effects of immunosuppression on cancer-specific outcomes. This document contains prognosis based on contemporary treatment and transplant recommendations for breast, colorectal, anal, urological, gynecological, and nonsmall cell lung cancers. This conference and consensus documents aim to provide recommendations to assist in the evaluation of patients for SOT given a history of a pretransplant malignancy.

Prognostic and Predictive Value of the American Joint Committee on Cancer Pathological Prognostic Staging System in Nodal Micrometastatic Breast Cancer

Introduction

To investigate the prognostic and predictive effect of the American Joint Committee on Cancer (AJCC) 8^th edition pathological prognostic staging system in patients with T1-2N1micM0 breast cancer who underwent mastectomy.

Methods

Data from T1-2N1micM0 breast cancer patients who underwent mastectomy from 2010–2014 were obtained from the Surveillance, Epidemiology, and End Results program. The chi-square test, binomial logistics regression, receiver-operating characteristics curve, competing-risk regression model, Cox proportional hazards regression model, and proportional hazard assumption were used for statistical analyses.

Results

We identified 4,729 patients, including 1,062 patients were received postmastectomy radiotherapy (PMRT). Stage change occurred in 88.2% of the patients, of which 84.4% were downstaged and 3.7% were upstaged. Patients with higher pathological prognostic stages were independently predicted to receive PMRT. The 5-year breast cancer-specific survival (BCSS) was 97.5, 93.7, 90.1, 86.0, and 73.5% in disease stages IA, IB, IIA, IIB, and IIIA, respectively, according to the 8^th edition criteria (P < 0.001). The AJCC 8^th edition demonstrated moderate discriminative ability, and it had a significantly better ability to predict the BCSS than the AJCC 7^th edition criteria (P < 0.001). The multivariate prognostic analysis showed that the new pathological prognostic staging was an independent prognostic factor affecting the BCSS. The BCSS worsened with an increase in the stage. The PMRT did not affect the BCSS regardless of the pathological prognostic stage. Similar trends were found using the competing-risks regression model.

Conclusions

The 8^th AJCC breast cancer pathological prognostic staging system downstaged 84.4% of patients with T1-2N1micM0 disease and the survival outcome prediction with this staging system was more accurate than the AJCC 7^th edition system. Our study does not support using the prognostic stage as a guideline to escalate of PMRT.

Treatment Patterns and Outcomes of Women with Breast Cancer and Supraclavicular Nodal Metastases

BACKGROUND

In 2002, breast cancer patients with supraclavicular nodal metastases (cN3c) were downstaged from AJCC stage IV to IIIc, prompting management with locoregional treatment. We sought to estimate the impact of multimodal therapy on overall survival (OS) in a contemporary cohort of cN3c patients.

METHODS

Women ≥ 18 years with cT1-T4c/cN3c invasive breast cancer who underwent systemic therapy were identified from the 2004-2016 National Cancer Database. We compared three patient cohorts: (a) cN3c + multimodal therapy (systemic therapy, surgery, and radiation); (b) cN3c + non-standard therapy; and, (c) cM1. Logistic regression identified factors associated with receipt of multimodal therapy and Kaplan-Meier was used to estimate unadjusted OS. The Cox proportional hazards model estimated effects of diagnosis and treatment on OS after adjustment.

RESULTS

Overall, 1827 (3.7%) patients with cN3c disease and 46,919 (96.3%) cM1 patients were identified. Of cN3c patients, 74.5% (n = 1362) received multimodal therapy and 25.5% (n = 465) received non-standard therapy; receipt of multimodal therapy was associated with improved 5-year OS (multimodal: 59% vs. M1: 28% vs. non-standard: 28%, log-rank p < 0.001). Adjusting for covariates, non-standard therapy was associated with an increased risk of death compared with receipt of multimodal therapy (HR 2.20, 95% CI 1.71-2.83, p < 0.001). Private insurance was the only patient characteristic associated with a greater likelihood of receiving multimodal therapy (OR 2.81; 95% CI, 1.64-4.82; p < 0.001).

CONCLUSION

Women with cN3c breast cancer who received multimodal therapy demonstrated improved overall survival when compared with patients undergoing non-standard therapy and those with metastatic (M1) disease. Although selection bias may contribute to worse overall survival among cN3c patients undergoing non-standard therapy, national guidelines should encourage locoregional treatment in carefully selected patients.

Incorporation of biologic factors for the staging of de novo stage IV breast cancer

This study aimed to investigate the prognostic value of biological factors, including histological grade, estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2) status in de novo stage IV breast cancer. Based on eligibility, patient data deposited between 2010 and 2014 were collected from the surveillance, epidemiology, and end results database. The receiver operating characteristics curve, Kaplan-Meier analysis, and Cox proportional hazard analysis were used for analysis. We included 8725 patients with a median 3-year breast cancer-specific survival (BCSS) of 52.6%. Higher histologic grade, HER2-negative, ER-negative, and PR-negative disease were significantly associated with lower BCSS in the multivariate prognostic analysis. A risk score staging system separated patients into four risk groups. The risk score was assigned according to a point system: 1 point for grade 3, 1 point if hormone receptor-negative, and 1 point if HER2-negative. The 3-year BCSS was 76.3%, 64.5%, 48.5%, and 23.7% in patients with 0, 1, 2, and 3 points, respectively, with a median BCSS of 72, 52, 35, and 16 months, respectively (P < 0.001). The multivariate prognostic analysis showed that the risk score staging system was an independent prognostic factor associated with BCSS. Patients with a higher risk score had a lower BCSS. Sensitivity analyses replicated similar findings after stratification according to tumor stage, nodal stage, the sites of distant metastasis, and the number of distant metastasis. In conclusion, our risk score staging system shows promise for the prognostic stratification of de novo stage IV breast cancer.

Validation of the Prognostic Stage of American Joint Committee on Cancer Eighth Edition Staging Manual in Invasive Lobular Carcinoma Compared to Invasive Ductal Carcinoma and Proposal of a Novel Score System

Purpose: The objective of this study was to evaluate the American Joint Committee on Cancer (AJCC) pathological prognostic stage among patients with invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) and to propose a modified score system if necessary.

Methods: Women diagnosed with IDC and ILC during 2010–2015 in the Surveillance, Epidemiology, and End Results (SEER) database were retrospectively identified. Disease-specific survival (DSS) and overall survival (OS) were estimated by Kaplan–Meier method. Predictive performances of different staging systems were evaluated based on Harrell concordance index (C-index) and Akaike Information Criterion (AIC). Multivariate Cox models were conducted to build preferable score systems.

Results: A total of 184,541 female patients were included in the final analyses, with a median follow-up of 30.0 months. In IDC cohort, the pathological prognostic stage (C-index, 0.8281; AIC, 110274.5) was superior to the anatomic stage (C-index, 0.8125; AIC, 112537.0; P < 0.001 for C-index) in risk stratification with respect to DSS. In ILC cohort, the prognostic stage (C-index, 0.8281; AIC, 7124.423) didn't outperform the anatomic stage (C-index, 0.8324; AIC, 7144.818; P = 0.748 for C-index) with respect to DSS. Similar results were observed with respect to OS. The score system defined by anatomic stage plus grade plus estrogen receptor and progesterone receptor (AS+GEP) allows for better staging (C-index, 0.8085; AIC, 7178.448) for ILC patients.

Conclusion: Compared with anatomic stage, the pathological prognostic stage provided more accurate stratification for patients with IDC, but not for patients with ILC. The AS+GEP score system may fit ILC tumors better.

Validation of the 8th edition of the American Joint Committee on Cancer Pathological Prognostic Staging for young breast cancer patients

Purpose: This study aimed to validate the newly proposed American Joint Committee on Cancer (AJCC) pathological prognostic staging system for young breast cancer patients (aged ≤40 years).

Results: We included 12811 women in this study. Overall, 52.8% of patients in the 7^th AJCC stages were restaged to the 8^th AJCC pathological staging system, including 10.7% upstaged and 42.1% downstaged. The receiver operating characteristics analysis showed that the new staging system had a better role in predicting breast cancer-specific survival (BCSS) compared with 7^th edition staging (P<0.001). The results of the multivariate prognostic analysis showed that the hazard ratio of BCSS increased with the 8^th AJCC stages, while the 7^th anatomic stages had no significant difference in BCSS.

Conclusions: The novel pathological staging system could provide more accurate prognostic stratification for young women with breast cancer because of the high proportion of stage migration.

Patients and Methods: Data for young breast cancer patients diagnosed between 2010 and 2014 were included from the Surveillance, Epidemiology, and End Results program. Chi-squared test, Kaplan–Meier method, receiver operating characteristics curve, and Cox proportional hazard analysis were applied to statistical analysis.

Improved Prognostication for the Updated AJCC Breast Cancer Pathological Prognostic Staging Varied in Higher-Stage Groups

BACKGROUND

In addition to TNM-based anatomical staging (AS), a novel pathological prognostic staging (PPS) has been proposed by the American Joint Committee on Cancer (AJCC). PPS demonstrated better prognostication, but its superiority in breast cancer subtypes and related to staging discrepancies between AS and PPS are not clear.

METHODS

A cohort of 1729 patients with breast cancer was staged into AS and PPS according to the latest AJCC staging. Patient characteristic and restaging outcomes were compared.

RESULTS

Compared with AS, 799 and 135 cases were upstaged and downstaged respectively in PPS, mostly involved stage I cases. For the overall cohort, PPS demonstrated superior prognostic power over AS in both disease-free survival (DFS) and breast cancer-specific survival. However, such superiority was found mainly in estrogen receptor (ER)/progesterone receptor (PR)+ but not ER-PR- cancers. Comparing the restaged cases within the same PPS, PPS 1A cases showed similar survival irrespective of the original AS. Interestingly, in other PPS groups (PPS 1B and higher), there was a difference in outcome among patients with same PPS but different AS. Within PPS 1B patients, downstaged cases from higher AS showed worse DFS (3A>1B vs. 2A>1B: χ² = 4.732, P = .030).

CONCLUSIONS

PPS may provide a more accurate prognostication, mostly among ER/PR+ cancers and with PPS 1A patients. Patients restaged to higher PPS stages showed significant differential survival even within the same PPS. Also, only limited improvement was observed for ER-PR- cancers. Caution needs to be exercised in using PPS for patient prognostication, as in some cases the outcome can be variable with the same PPS.