Evaluation of the prognostic stage in the 8th edition of the American Joint Committee on Cancer in locally advanced breast cancer: An analysis based on SEER 18 database

Validation of the AJCC 8th Edition Breast Cancer Prognostic Staging System in Legacy Alliance Trials (AFT-01)

BACKGROUND

The 8th edition American Joint Committee on Cancer staging system combined anatomic stage (AS) with receptor status and grade to create prognostic stage (PS). PS has been validated in single-institution and cancer registry studies; however, missing human epidermal growth factor receptor 2 (HER2) status and variable treatment and follow-up create limitations.

OBJECTIVE

Our objective was to compare the relative prognostic ability of PS versus AS to predict survival using breast cancer clinical trial data.

METHODS

Women with non-metastatic breast cancer enrolled in six Alliance for Clinical Trials in Oncology trials were included (enrollment years 1997-2010). AS and PS were constructed using pathological tumor size, nodal status, estrogen receptor (ER), progesterone receptor (PR), HER2 status, and grade. Unadjusted Cox proportional hazard models were estimated to predict overall survival within 5 years, with AS and PS as predictor variables. The relative predictive power of staging models was assessed by comparing Harrell concordance indices (C-indices). Kaplan-Meier-based mortality estimates were compared by stage.

RESULTS

Overall, 6924 women were included (median age 53 years); 45.2% were diagnosed with ER+/PR+/HER2- tumors, 26.2% with HER2+ tumors, and 17.1% with ER-/PR-/HER2- tumors. Median follow-up time was 5 years (interquartile range 2.95-5.00). PS significantly improved predictive performance (C-index 0.721) for overall survival compared with AS (0.700) (p = 0.020). Kaplan-Meier hazard estimates suggested PS did not distinguish mortality risk between patients with IIB and IIIA or IB and IIA disease.

CONCLUSIONS

PS has significantly improved predictive performance for OS compared with AS. As systemic therapies evolve, it will be important to re-evaluate the prognostic staging system, particularly for patients with intermediate-stage cancers.

CLINICALTRIALS

gov Identifier: NCT02171078.

Effectiveness of post-mastectomy adjuvant chemotherapy for the treatment of patients with prognostic stage IB breast cancer: A SEER-based study

BACKGROUND

Adjuvant chemotherapy (AC) is an important, effective treatment for breast cancer. This study evaluates the effectiveness of post-mastectomy AC in treating patients with prognostic stage IB breast cancer.

METHOD

We conducted a retrospective cohort-based study using Surveillance, Epidemiology, and End-Results database. Overall survival (OS) and breast cancer-specific survival (BCSS) were calculated using the Kaplan-Meier method. Multivariate Cox risk models were used to identify the impact of AC. Stratified analysis was performed according to molecular subtypes, anatomic stages, and other risk factors to evaluate the effect of AC on survival.

RESULTS

28,825 women diagnosed with prognostic stage IB breast cancer were included. The 5-year OS was significantly higher in AC group than in non-adjuvant chemotherapy (NAC) group (P < 0.0001); however, the 5-year BCSS in AC group was significantly lower than in NAC group (P = 0.039). Multivariate analysis revealed that AC was a favorable prognostic factor for OS (P < 0.001), but not BCSS (P = 0.407). AC was not an independent prognostic factor for BCSS in patients with hormone receptor-positive, human epidermal growth factor receptor 2-negative (HR[+]/HER2[-]) subtype or pT1a-1b/N0-1 stage with HER2 overexpression (HER2[+]) subtype, regardless of whether HR was positive or negative (P > 0.05). Meanwhile, AC is not an independent prognostic factor for OS and BCSS in patients with lymph node micrometastases.

CONCLUSION

Our study demonstrates that patients with prognostic stage IB do not fully benefit from AC. Individualized treatment management is required for patients with pT1a-1b/N0-1 tumors, lymph node micrometastases, or HR(+)/HER2(-) subtypes.

The impact of tumor characteristics on cardiovascular disease death in breast cancer patients with CT or RT: a population-based study

Background

Previous studies focused on the impact of cardiovascular diseases (CVD) risk factors in breast cancer patients with chemotherapy (CT) or radiotherapy (RT). This study aimed to identify the impact of tumor characteristics on CVD death in these patients.

Methods

Data of female breast cancer patients with CT or RT between 2004 and 2016 were included. The risk factors of CVD death were identified using Cox regression analyses. A nomogram was constructed to evaluate the predicted value of tumor characteristics, and then validated by the concordance indexes (C-index) and calibration curves.

Result

A total of 28,539 patients were included with an average follow-up of 6.1 years. Tumor size > 45 mm (adjusted HR = 1.431, 95% CI = 1.116-1.836, P = 0.005), regional (adjusted HR = 1.278, 95% CI = 1.048-1.560, P = 0.015) and distant stage (adjusted HR = 2.240, 95% CI = 1.444-3.474, P < 0.001) were risk factors of CVD death for breast cancer patients with CT or RT. The prediction nomogram of tumor characteristics (tumor size and stage) on CVD survival was established. The C-index of internal and external validation were 0.780 (95% Cl = 0.751-0.809), and 0.809 (95% Cl = 0.768-0.850), respectively. The calibration curves showed consistency between the actual observation and nomogram. The risk stratification was also significant distinction (P < 0.05).

Conclusion

Tumor size and stage were related to the risk of CVD death for breast cancer patients with CT or RT. The management of CVD death risk in breast cancer patients with CT or RT should focus not only on CVD risk factors but also on tumor size and stage.

Survival Nomogram for Patients With Locally Advanced Breast Cancer Undergoing Immediate Breast Reconstruction: A SEER Population-Based Study

INTRODUCTION/BACKGROUND

This study aimed to construct a nomogram to provide prognostic references for patients with locally advanced breast cancer (LABC) to receive immediate breast reconstruction (IBR).

MATERIALS AND METHODS

All data were obtained from the Surveillance, Epidemiology and End Results (SEER) database. Univariate Cox regression, least absolute shrinkage and selection operator (LASSO) and best subset regression (BSR), separately followed by backward stepwise multivariable Cox, were used to construct the nomogram. Risk stratification was established after validation.

RESULTS

A total of 6,285 patients were enrolled to generate the training group (n = 3,466) and the test group (n = 2,819) by geographical split. Age, marital status, grade, T staging, N staging, radiotherapy, chemotherapy, estrogen receptor status (ER), progesterone receptor status (PR) and human epidermal growth factor receptor type 2 status (HER2) were used to fit the nomogram. The overall Harrell's concordance index (C-index) was 0.772 in the training group and 0.762 in the test group. The area under the receiver operator characteristic curves (AUC) at 3-year and 5-year were respectively 0.824 and 0.720 in the training group, 0.792 and 0.733 in the test group. The calibration curves showed great consistency in both groups. A dynamic nomogram (https://dcpanfromsh.shinyapps.io/NomforLABCafterIBR/) was developed.

CONCLUSION

A nomogram was developed and validated that predicts prognosis more accurately than the AJCC 7th stage and can be used as a reference for decision-making in LABC patients receiving IBR.

Analysis of prognostic factors and construction of prognostic models for triple-positive breast cancer

Objective

By identifying the clinicopathological characteristics and prognostic influences of patients with triple-positive breast cancer (TPBC) at Xijing Hospital in China compared with those in the United States, this study aims to construct a nomogram model to forecast the overall survival rate (OS) of TPBC patients.

Method

The Surveillance, Epidemiology, and End Results (SEER) database was used to screen 5769 patients as the training cohort, and 191 patients from Xijing Hospital were used as the validation cohort. Cox risk-proportional model was applied to select variables and the nomogram model was constructed based on the training cohort. The performance of the model was evaluated by calculating the C-index and generating calibration plots in the training and validation cohorts.

Results

Cox multifactorial analysis showed that age, chemotherapy, radiotherapy, M-stage, T-stage, N-stage, and the mode of surgery were all independent risk factors for the prognosis of TPBC patients (all P<0.05). With this premise, the nomogram model was constructed and evaluated. The C-index value of the nomogram model was 0.830 in the training group and 0.914 in the validation group. Moreover, both the calibration and ROC curves for the proposed model exhibited reliable performance, and the clinical decision curve analysis showed that the proposed model can bring clinical benefits.

Conclusions

The constructed nomogram can accurately predict individual survival probabilities and may serve as a clinical decision support tool for clinicians to optimize treatment in individuals.

Development and validation of nomograms for predicting overall survival and cancer specific survival in locally advanced breast cancer patients: A SEER population-based study

Background

For patients with locally advanced breast cancer (LABC), conventional TNM staging is not accurate in predicting survival outcomes. The aim of this study was to develop two accurate survival prediction models to guide clinical decision making.

Methods

A retrospective analysis of 22,842 LABC patients was performed from 2010 to 2015 using the Surveillance, Epidemiology and End Results (SEER) database. An additional cohort of 200 patients from the Binzhou Medical University Hospital (BMUH) was analyzed. The least absolute shrinkage and selection operator (LASSO) regression was used to screen for variables. The identified variables were used to build a survival prediction model. The performance of the nomogram models was assessed based on the concordance index (C-index), calibration plot, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA).

Results

The LASSO analysis identified 9 variables in patients with LABC, including age, marital status, Grade, histological type, T-stage, N-stage, surgery, radiotherapy, and chemotherapy. In the training cohort, the C-index of the nomogram in predicting the overall survival (OS) was 0.767 [95% confidence intervals (95% CI): 0.751-0.775], cancer specific survival (CSS) was 0.765 (95% CI: 0.756-0.774). In the external validation cohort, the C-index of the nomogram in predicting the OS was 0.858 (95% CI: 0.812-0.904), the CSS was 0.866 (95% CI: 0.817-0.915). In the training cohort, the area under the receiver operator characteristics curve (AUC) values of the nomogram in prediction of the 1, 3, and 5-year OS were 0.836 (95% CI: 0.821-0.851), 0.769 (95% CI: 0.759-0.780), and 0.750 (95% CI: 0.738-0.762), respectively. The AUC values for prediction of the 1, 3, and 5-year CSS were 0.829 (95% CI: 0.811-0.847), 0.769 (95% CI: 0.757-0.780), and 0.745 (95% CI: 0.732-0.758), respectively. Results of the C-index, ROC curve, and DCA demonstrated that the nomogram was more accurate in predicting the OS and CSS of patients compared with conventional TNM staging.

Conclusion

Two prediction models were developed and validated in this study which provided more accurate prediction of the OS and CSS in LABC patients than the TNM staging. The constructed models can be used for predicting survival outcomes and guide treatment plans for LABC patients.

Contemporary Trends in Breast Reconstruction Use and Impact on Survival Among Women with Inflammatory Breast Cancer

BACKGROUND

Breast reconstruction is generally discouraged in women with inflammatory breast cancer (IBC). Nevertheless, reconstruction rates are increasing in this population.

OBJECTIVE

We aimed to determine contemporary trends and predictors of breast reconstruction use and its impact on mortality among IBC patients.

METHODS

Demographic, clinicopathologic, and follow-up data for women with non-metastatic IBC having mastectomy between 2004 and 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) 18 registries database. Rates and predictors of immediate breast reconstruction, along with survival outcomes between the breast reconstruction and no reconstruction groups were calculated. To account for selection bias, a propensity score analysis matching one reconstruction patient to three no reconstruction patients was performed.

RESULTS

A total of 4076 women with non-metastatic IBC who underwent mastectomy (388 [9.5%] with breast reconstruction and 3688 [90.5%] without) were included. The proportion of women undergoing breast reconstruction and contralateral prophylactic mastectomy increased from 6.2 to 15.3% and 12.9 to 29.6%, respectively, between 2004 and 2015. Younger age, higher annual income, metropolitan residence, and bilateral mastectomy predicted breast reconstruction use. The 10-year breast cancer-specific survival was 62.9% for women having breast reconstruction and 47.6% for women not having breast reconstruction. After propensity-matched analysis, 10-year cancer-specific survival was similar between the reconstruction (56.6%) and no reconstruction (62.2%) groups (adjusted hazard ratio 0.96, 95% confidence interval 0.79-1.16; p = 0.65).

CONCLUSIONS

Breast reconstruction rates continue to rise among IBC patients, particularly young women and women with access to reconstruction. Breast reconstruction is not associated with inferior breast cancer-specific survival and can be an option for select patients.

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.

A Novel Staging System for De Novo Metastatic Breast Cancer Refines Prognostic Estimates

OBJECTIVE

We aim to identify prognostic groups within a de novo metastatic cohort, incorporating both anatomic and biologic factors.

BACKGROUND

Staging for breast cancer now includes anatomic and biologic factors, although the guidelines for stage IV disease do not account for how these factors may influence outcomes.

METHODS

Adults with de novo metastatic breast cancer were selected from the National Cancer DataBase (2010-2013). Recursive partitioning analysis was used to group patients with similar overall survival (OS) based on clinical T/N stage, tumor grade, ER, PR, HER2, number of metastatic sites, and presence of bone-only metastases. Categories were created by amalgamating homogeneous groups based on 3-year OS rates (stage IVA: >50%, stage IVB: 30%-50%, stage IVC: <30%).

RESULTS

16,187 patients were identified; median follow-up was 32 months. 65.2% had 1 site of distant metastasis, and 42.9% had bone-only metastases. Recursive partitioning analysis identified the number of metastatic sites (1 vs >1) as the first stratification point, and ER status as the second stratification point for both resulting groups. Additional divisions were made based on HER2 status, PR status, cT stage, tumor grade, and presence of bone-only metastases. After bootstrapping, significant differences in 3-year OS were noted between the 3 groups [stage IVB vs IVA: HR 1.58 (95% confidence interval 1.50-1.67), stage IVC vs IVA: HR 3.54 (95% confidence interval 3.33-3.77)].

CONCLUSIONS

Both anatomic and biologic factors yielded reliable and reproducible prognostic estimates among patients with metastatic disease. These findings support formal stratification of de novo stage IV breast cancer into 3 distinct prognosis groups.

Psychological Distress, Coping Strategies, and Quality of Life in Breast Cancer Patients Under Neoadjuvant Therapy: Protocol of a Systematic Review

Introduction

Women with breast cancer eligible for neoadjuvant therapy (NAT) present a disorder of biopsychosocial variables and alteration of their quality of life. They cope with this changing by adopting psychological adjustment strategies, either passive or active. This systematic review aims to investigate the psychological distress, coping strategies, and quality of life in breast cancer patients under neoadjuvant therapy.

Methods

Cochrane Library, PubMed, ScienceDirect, Scopus, Web of Science, and Wiley Online library represent the databases that were searched to identify relevant published articles until September 27, 2021. Full-text published articles, written in English and assessing the main outcomes (namely: psychological distress, coping strategies, and quality of life) in women with breast cancer under NAT will be included. Also, we will integrate papers dealing with the related bio psychosocial variables to the main variables. The paper selection, data extraction, and quality assessment of selected studies will be performed independently by two researchers, and disagreements will be resolved through discussions. We will bring together the results of all of the included studies to draw conclusions based on the body of evidence. The narrative approach will be adopted to analyze the results and conclusions extracted and we would perform quantitative groupings if we have similar data.

Ethics and dissemination

Ethical approval is not required as the proposed systematic review will not use primary data. The results of this review will be disseminated through publication in a peer-reviewed journal and conference presentation(s). PROSPERO registration number: CRD42021230300.

Validation of the Prognostic Stage from the American Joint Committee on Cancer 8th Staging Manual in Luminal B-Like Human Epidermal Growth Factor Receptor 2-Negative Breast Cancer

Purpose

The 8th edition American Joint Committee on Cancer (AJCC) prognostic staging system (PS) has been validated numerous times; however, the prognostic value of PS for breast cancer based on molecular subtype has rarely been explored. This study aimed to investigate the prognostic value of PS in Chinese patients with luminal B-like human epidermal growth factor receptor 2 (HER2)-negative breast cancer.

Methods

A total of 407 eligible cases were included in the study. All of the cases were restaged using the 8th edition AJCC Anatomic Staging System (AS) and PS. The Kaplan–Meier method was used to calculate estimated survival and the Log rank test was used to compare the survival differences between groups.

Results

The 5-year disease-specific survival (DSS) and overall survival (OS) rates were 90.3% and 93.5%, respectively, and there were statistically significant differences in the 5-year DSS and 5-year OS rates among the different anatomic and prognostic stage groups. The application of the PS resulted in the assignment of 215 (52.8%) patients to a different group. Different prognostic stage groups restaged from anatomic Stage III had significant differences in both DSS (χ² = 4.366, p = 0.037) and OS (χ² = 7.549, p = 0.006); additionally, different prognostic stage groups from the anatomic Stage II group had significant differences in DSS (χ² = 7.724, p = 0.021) but no significant differences in OS (χ² = 5.182, p = 0.075). However, different prognostic stage groups from anatomic Stage I had no significant differences in either DSS (χ²= 0.159, p = 0.690) or OS (χ² = 0.099, p = 0.753).

Conclusion

The 8th edition AJCC PS refined the anatomic stage grouping in luminal B-like HER2-negative breast cancer and could lead to a more personalized approach to breast cancer treatment.

OUP accepted manuscript

Background

Methods

Results

Conclusion

Radiomics in predicting recurrence for patients with locally advanced breast cancer using quantitative ultrasound

Background: The purpose of the study was to investigate the role of pre-treatment quantitative ultrasound (QUS)-radiomics in predicting recurrence for patients with locally advanced breast cancer (LABC).

Materials and Methods: A prospective study was conducted in patients with LABC (n = 83). Primary tumours were scanned using a clinical ultrasound device before starting treatment. Ninety-five imaging features were extracted-spectral features, texture, and texture-derivatives. Patients were determined to have recurrence or no recurrence based on clinical outcomes. Machine learning classifiers with k-nearest neighbour (KNN) and support vector machine (SVM) were evaluated for model development using a maximum of 3 features and leave-one-out cross-validation.

Results: With a median follow up of 69 months (range 7–118 months), 28 patients had disease recurrence (local or distant). The best classification results were obtained using an SVM classifier with a sensitivity, specificity, accuracy and area under curve of 71%, 87%, 82%, and 0.76, respectively. Using the SVM model for the predicted non-recurrence and recurrence groups, the estimated 5-year recurrence-free survival was 83% and 54% (p = 0.003), and the predicted 5-year overall survival was 85% and 74% (p = 0.083), respectively.

Conclusions: A QUS-radiomics model using higher-order texture derivatives can identify patients with LABC at higher risk of disease recurrence before starting treatment.

Role of PTEN, PI3K, and mTOR in Triple-Negative Breast Cancer

Breast cancer is the most commonly occurring malignancy and the leading cause of cancer-related death in women. Triple-negative breast cancer (TNBC) is the most aggressive subtype and is associated with high recurrence rates, high incidence of distant metastases, and poor overall survival. The aim of this study was to investigate the PI3K/PTEN/Akt/mTOR pathway as one of the most frequently deregulated pathways in cancer. We aimed to explore the impact of PI3K and mTOR oncogenes as well as the PTEN tumor suppressor on TNBC clinical behavior, prognosis, and multidrug resistance (MDR), using immunohistochemistry and copy number analysis by quantitative real-time PCR. Our results revealed that loss of PTEN and high expression of PI3K and mTOR proteins are associated with poor outcome of TNBC patients. PTEN deletions appeared as a major cause of reduced or absent PTEN expression in TNBC. Importantly, homozygous deletions of PTEN (and not hemizygous deletions) are a potential molecular marker of metastasis formation and good predictors of TNBC outcome. In conclusion, we believe that concurrent examination of PTEN/PI3K/mTOR protein expression may be more useful in predicting TNBC clinical course than the analysis of single protein expression. Specifically, our results showed that PTEN-reduced/PI3K-high/mTOR-high expression constitutes a ‘high risk’ profile of TNBC.

Triple-negative breast cancer outcomes: Does AJCC 8th staging improve chemotherapy decision-making

PURPOSE

To investigate the effect of the 8th American Joint Committee on Cancer (AJCC) pathological prognostic staging on chemotherapy decision-making for triple-negative breast cancer (TNBC) patients with T1-2N0M0 disease.

METHODS

Patients diagnosed with T1-2N0M0 TNBC were retrieved from the Surveillance, Epidemiology, and End Results program. Statistical methods including Kaplan-Meier survival curve, receiver operating characteristics curve, and Cox proportional hazard model.

RESULTS

We identified 12,156 patients, including 9371 (77.1%) patients who received chemotherapy. Overall, 57.4% of patients (n = 6975) were upstaged after being reassigned by the 8th AJCC staging. However, the 8th staging of AJCC did not have a greater prognostic value compared to the 7th staging (P = 0.064). The receipt of chemotherapy significantly improved the breast cancer-specific survival for stage T1c and T2 tumors (P < 0.001), but not for stage T1a (P = 0.188) and T1b (P = 0.376) tumors. Using AJCC 8th staging, chemotherapy benefit was only found in stage IIA patients (P = 0.002), but not for stage IA (P = 0.653) and IB (P = 0.492) patients. There were 9564 patients with stage T1c and T2 diseases and 4979 patients with 8th AJCC stage IIA disease. Therefore, approximately half of patients (47.9%, n = 4585) may be safe to omit chemotherapy using the AJCC 8th staging compared to the current chemotherapy recommendation for T1-2N0M0 TNBC.

CONCLUSION

The 8th AJCC staging system did not demonstrate the superior discriminatory ability of prognostic stratification than the 7th AJCC staging system in T1-2N0M0 TNBC. However, this new AJCC staging could more accurately predict the chemotherapy benefit, thereby enabling more patients to avoid unnecessary chemotherapy.

Information extraction for prognostic stage prediction from breast cancer medical records using NLP and ML

For cancer prediction, the prognostic stage is the main factor that helps medical experts to decide the optimal treatment for a patient. Specialists study prognostic stage information from medical reports, often in an unstructured form, and take a larger review time. The main objective of this study is to suggest a generic clinical decision-unifying staging method to extract the most reliable prognostic stage information of breast cancer from medical records of various health institutions. Additional prognostic elements should be extracted from medical reports to identify the cancer stage for getting an exact measure of cancer and improving care quality. This study has collected 465 pathological and clinical reports of breast cancer sufferers from India's reputed medical institutions. The unstructured records were found distinct from each institute. Anatomic and biologic factors are extracted from medical records using the natural language processing, machine learning and rule-based method for prognostic stage detection. This study has extracted anatomic stage, grade, estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) from medical reports with high accuracy and predicted prognostic stage for both regions. The prognostic stage prediction's average accuracy is found 92% and 82% in rural and urban areas, respectively. It was essential to combine biological and anatomical elements under a single prognostic staging method. A generic clinical decision-unifying staging method for prognostic stage detection with great accuracy in various institutions of different regional areas suggests that the proposed research improves the prognosis of breast cancer.

Relationship between Prognostic Stage in Breast Cancer and Fluorine-18 Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography

This retrospective study examined the relationship between the standardized uptake value max (SUVmax) of fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) and the prognostic stage of breast cancer. We examined 358 breast cancers in 334 patients who underwent ¹⁸F-FDG PET/CT for initial staging between January 2016 and December 2019. We extracted data including SUVmax of ¹⁸F-FDG PET and pathological biomarkers, including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and nuclear grade. Anatomical and prognostic stages were determined per the American Joint Committee on Cancer (eighth edition). We examined whether there were statistical differences in SUVmax between each prognostic stage. The mean SUVmax values for clinical prognostic stages were as follow: stage 0, 2.2 ± 1.4; stage IA, 2.6 ± 2.1; stage IB, 4.2 ± 3.5; stage IIA, 5.2 ± 2.8; stage IIB, 7.7 ± 6.7; and stage III + IV, 7.0 ± 4.5. The SUVmax values for pathological prognostic stages were as follows: stage 0, 2.2 ± 1.4; stage IA, 2.8 ± 2.2; stage IB, 5.4 ± 3.6; stage IIA, 6.3 ± 3.1; stage IIB, 9.2 ± 7.5, and stage III + IV, 6.2 ± 5.2. There were significant differences in mean SUVmax between clinical prognostic stage 0 and ≥II (p < 0.001) and I and ≥II (p < 0.001). There were also significant differences in mean SUVmax between pathological prognostic stage 0 and ≥II (p < 0.001) and I and ≥II (p < 0.001). In conclusion, mean SUVmax increased with all stages up to prognostic stage IIB, and there were significant differences between several stages. The SUVmax of ¹⁸F-FDG PET/CT may contribute to prognostic stage stratification, particularly in early cases of breast cancers.

Mode of detection matters: Differences in screen-detected versus symptomatic breast cancers

OBJECTIVE

Although extensive analyses evaluating screening mammography for breast cancer have been published, some utilized databases do not distinguish between modes of detection, which confounds the conclusions made about the impact of screening mammography.

METHODS

A retrospective cohort study of women at our institution with pathologically-proven breast cancer from January 2015 to April 2018 was conducted. Subjects were categorized by their mode of diagnosis: screening or non-screening. Patient demographics, tumor characteristics, and treatments were compared between detection methods using Wilcoxon rank-sum test for continuous variables and chi-squared or Fisher's exact test.

RESULTS

1026 breast cancers were analyzed. 80.8% of screen-detected breast cancers were invasive. Compared to symptomatically detected cancers, screen-detected were smaller (median size 8 mm vs. 15 mm, p < 0.001), less invasive (80.8% vs. 94.3), had a lower pathologic grade (29% grade 3 vs. 45.7%, p < 0.001), a lower clinical stage, and less aggressive histology (51.9% low Ki67 vs. 30.5%, and 88.2% HER2 negative vs. 76.6%, p < 0.001). Screen-detected cancers were less likely to have extramammary disease (13.2% positive lymph nodes vs. 34.0% and 0.4% distant metastases vs. 6.9%, p < 0.001). Women with screen-detected cancers were more likely to undergo conservative treatment (74.8% underwent lumpectomy vs. 59.9%, and 80.0% received no chemotherapy vs. 51.3%, p < 0.001).

CONCLUSION

In this study, while the vast majority of screen-detected cancers were invasive, they were more likely to be smaller, less aggressive, and a lower pathologic grade and clinical stage. Furthermore, women with screen-detected cancers were less likely to have extramammary disease and more likely to undergo conservative treatment.

Increasing prediction accuracy of pathogenic staging by sample augmentation with a GAN

Accurate prediction of cancer stage is important in that it enables more appropriate treatment for patients with cancer. Many measures or methods have been proposed for more accurate prediction of cancer stage, but recently, machine learning, especially deep learning-based methods have been receiving increasing attention, mostly owing to their good prediction accuracy in many applications. Machine learning methods can be applied to high throughput DNA mutation or RNA expression data to predict cancer stage. However, because the number of genes or markers generally exceeds 10,000, a considerable number of data samples is required to guarantee high prediction accuracy. To solve this problem of a small number of clinical samples, we used a Generative Adversarial Networks (GANs) to augment the samples. Because GANs are not effective with whole genes, we first selected significant genes using DNA mutation data and random forest feature ranking. Next, RNA expression data for selected genes were expanded using GANs. We compared the classification accuracies using original dataset and expanded datasets generated by proposed and existing methods, using random forest, Deep Neural Networks (DNNs), and 1-Dimensional Convolutional Neural Networks (1DCNN). When using the 1DCNN, the F1 score of GAN5 (a 5-fold increase in data) was improved by 39% in relation to the original data. Moreover, the results using only 30% of the data were better than those using all of the data. Our attempt is the first to use GAN for augmentation using numeric data for both DNA and RNA. The augmented datasets obtained using the proposed method demonstrated significantly increased classification accuracy for most cases. By using GAN and 1DCNN in the prediction of cancer stage, we confirmed that good results can be obtained even with small amounts of samples, and it is expected that a great deal of the cost and time required to obtain clinical samples will be reduced. The proposed sample augmentation method could also be applied for other purposes, such as prognostic prediction or cancer classification.

Evaluation of the AJCC Eighth-Edition Prognostic Staging System for Breast Cancer in a Latin American Cohort

BACKGROUND

The staging of breast cancer has been based on tumor size, lymph node involvement, and presence or absence of distant metastases. The American Joint Committee on Cancer (AJCC) staging system in its eighth edition incorporates hormone receptors, human epidermal growth factor receptor 2 (HER2), and histologic grade due to their prognostic importance. In Latin America, however, the impact of the new edition is unknown. This article evaluates the performance of the AJCC eighth-edition staging system in a cohort of patients with breast cancer at a reference center in Colombia.

METHODS

The study investigated a descriptive cohort of 912 patients who received complete treatment for non-metastatic invasive breast cancer and had information on the anatomic stage and biologic factors,. All the patients were restaged using the AJCC eighth-edition classification. Changes in clinical stages and differences between the two classifications were compared.

RESULTS

The study enrolled 912 patients. Changes in staging occurred for 54.82% (downstaging for 40.3% and upstaging for 14.47%) of these patients. For recurrence-free survival, the C-Index of the eighth-edition AJCC was 0.726, and the AIC was 1323.7, whereas the C-Index of the seventh-edition AJCC was 0.731, and the AIC was 1314.3 (p = 0.99).

CONCLUSIONS

The seventh and eighth editions of the AJCC staging system have similar predictive values in our population for recurrence-free survival. Future studies are necessary to evaluate the performance of the AJCC eighth-edition staging system in predicting overall survival.

Staging for Breast Cancer With Internal Mammary Lymph Nodes Metastasis: Utility of Incorporating Biologic Factors

Purpose

To validate the 8th edition of the American Joint Committee on Cancer (AJCC) pathological prognostic staging system for breast cancer patients with internal mammary lymph nodes (IMN) metastasis (N3b disease, stage IIIC in 7th AJCC anatomical staging).

Methods

Breast cancer patients with IMN metastasis diagnosed between 2010 and 2014 were retrieved from the Surveillance, Epidemiology, and End Results program. Chi-squared test, Log-rank test, Kaplan-Meier method, and Cox proportional hazard analysis were applied to statistical analysis.

Results

We included 678 patients with N3b disease in this study. Overall, 68.4% of patients were downstaged to IIIA and IIIB diseases from the 7th anatomical staging to 8th pathological prognostic staging. The new pathological prognostic staging system had better discriminatory value on prognosis prediction among IMN-metastasized breast cancer patients, with a 5-year breast cancer-specific survival (BCSS) of 92.7, 77.4, and 66.0% in stage IIIA, IIIB, and IIIC diseases, respectively (P<0.0001), and the 5-year overall survival (OS) rates was 85.9, 72.1, and 58.7%, respectively (P<0.0001). The results of the multivariate prognostic analysis showed that the new pathological prognostic staging was the independent prognosis related to BCSS and OS, the 8th AJCC pathological prognostic stages showed worse BCSS and OS with gradually increased hazard ratios.

Conclusion

The 8th AJCC pathological prognostic staging system offers more refined prognostic stratification to IMN-metastasized breast cancer patients and endorses its use in routine clinical practice for this specific subgroup of breast cancer.

Correlation between MRI morphological response patterns and histopathological tumor regression after neoadjuvant endocrine therapy in locally advanced breast cancer: a randomized phase II trial

PURPOSE

To correlate MRI morphological response patterns with histopathological tumor regression grading system based on tumor cellularity in locally advanced breast cancer (LABC)-treated neoadjuvant with third-generation aromatase inhibitors.

METHODS

Fifty postmenopausal patients with ER-positive/HER-2-negative LABC treated with neoadjuvant letrozole and exemestane given sequentially in an intra-patient cross-over regimen for at least 4 months with MRI response monitoring at baseline as well as after at least 2 and 4 months on treatment. The MRI morphological response pattern was classified into 6 categories: 0/complete imaging response; I/concentric shrinkage; II/fragmentation; III/diffuse; IV/stable; and V/progressive. Histopathological tumor regression was assessed based on the recommendations from The Royal College of Pathologists regarding tumor cellularity.

RESULTS

Following 2 and 4 months with therapy, the most common MRI pattern was pattern II (24/50 and 21/50, respectively). After 4 months on therapy, the most common histopathological tumor regression grade was grade 3 (21/50). After 4 months an increasing correlation is observed between MRI patterns and histopathology. The overall correlation, between the largest tumor diameter obtained from MRI and histopathology, was moderate and positive (r = 0.50, P-value = 2e-04). Among them, the correlation was highest in type IV (r = 0.53).

CONCLUSION

The type II MRI pattern "fragmentation" was more frequent in the histopathological responder group; and types I and IV in the non-responder group. Type II pattern showed the best endocrine responsiveness and a relatively moderate correlation between sizes obtained from MRI and histology, whereas type IV pattern indicated endocrine resistance but the strongest correlation between MRI and histology.

The prognostic and predictive value of the 8th American Joint Committee on Cancer (AJCC) staging system among early breast cancer patients aged <50 years

Background

This study respectively analyzed the prognostic value and the role in treatment decision-making [breast-conserving surgery (BCS) + radiotherapy (RT) or mastectomy (MAST)] of the 8th American Joint Committee on Cancer (AJCC) pathological prognostic staging system compared with the 7th AJCC anatomical staging system among early breast cancer patients aged <50 years.

Methods

Patients with T1-2N0M0 breast cancer aged <50 years were extracted from the Surveillance, Epidemiology, and End Results database between 2010 and 2014. Breast cancer-specific survival (BCSS) was used as the primary endpoint. Chi-squared test, receiver operating characteristics analysis, Kaplan-Meier method, and multivariate Cox proportional models were used to conduct statistical analysis.

Results

A total of 22,640 female patients were identified, and 24.4% of them reallocated to new stage groups from the 7th to the 8th AJCC staging. Among them, 46.2% (n=10,450) and 53.8% (n=12,190) of patients received BCS + RT and MAST, respectively. The 8th AJCC staging system was an independent prognostic factor for BCSS. Patients treated with BCS + RT had better BCSS compared to those treated with MAST (P<0.001). According to the 8th AJCC staging, BCS + RT could improve 5-year BCSS compared with MAST in patients with stage IA (P=0.006) and stage IB (P=0.001) diseases, while comparable BCSS was found between the two treatment arms in patients' stage IIA disease (P=0.366). Multivariate analyses replicated similar findings after stratification by the 8th AJCC stages.

Conclusions

In patients with T1-2N0 breast cancer and aged <50 years, the 8th AJCC pathological staging system provides accurate prognostic information than the 7th anatomical staging. BCS + RT is the optimal local management for stage IA and IB diseases, while it is the optional management in stage IIA disease according to the 8th AJCC staging.

Validation of Prognostic Stage and Anatomic Stage in the American Joint Committee on Cancer 8th Edition for Inflammatory Breast Cancer

The AJCC updated its breast cancer staging system to incorporate biological factors in the "prognostic stage". We undertook this study to validate the prognostic and anatomic stages for inflammatory breast cancer (IBC). We established two cohorts of IBC diagnosed without distant metastasis: (1) patients treated at The University of Texas MD Anderson Cancer Center between 1991 and 2017 (MDA cohort) and (2) patients registered in the national Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015 (SEER cohort). For prognostic staging, estrogen receptor (ER)+/progesterone receptor (PR)+/ human epidermal growth factor receptor-2 (HER2)+/grade 1-2 was staged as IIIA; ER+/PR-/HER2-/grade 3, ER-/PR+/HER2-/grade 3, and triple-negative cancers as IIIC; and all others as IIIB. Endpoints were breast cancer-specific survival (BCSS), overall survival (OS), and disease-free survival (DFS). We studied 885 patients in the MDA cohort and 338 in the SEER cohort. In the MDA cohort, the prognostic stage showed significant predictive power for BCSS, OS, and DFS (all p < 0.0001), although the anatomic stage did not. In both cohorts, the Harrell concordance index (C index) was significantly higher in the prognostic stage than the anatomic stage for all endpoints. In conclusion, the prognostic stage provided more accurate prognostication for IBC than the anatomic stage. Our results show that the prognostic staging is applicable in IBC.

Quantitative ultrasound radiomics using texture derivatives in prediction of treatment response to neo-adjuvant chemotherapy for locally advanced breast cancer

Background: To investigate quantitative ultrasound (QUS) based higher-order texture derivatives in predicting the response to neoadjuvant chemotherapy (NAC) in patients with locally advanced breast cancer (LABC).

Materials and Methods: 100 Patients with LABC were scanned before starting NAC. Five QUS parametric image-types were generated from radio-frequency data over the tumor volume. From each QUS parametric-image, 4 grey level co-occurrence matrix-based texture images were derived (20 QUS-Tex¹), which were further processed to create texture derivatives (80 QUS-Tex¹-Tex²). Patients were classified into responders and non-responders based on clinical/pathological responses to treatment. Three machine learning algorithms based on linear discriminant (FLD), k-nearest-neighbors (KNN), and support vector machine (SVM) were used for developing radiomic models of response prediction.

Results: A KNN-model provided the best results with sensitivity, specificity, accuracy, and area under curve (AUC) of 87%, 81%, 82%, and 0.86, respectively. The most helpful features in separating the two response groups were QUS-Tex¹-Tex² features. The 5-year recurrence-free survival (RFS) calculated for KNN predicted responders and non-responders using QUS-Tex¹-Tex² model were comparable to RFS for the actual response groups.

Conclusions: We report the first study demonstrating QUS texture-derivative methods in predicting NAC responses in LABC, which leads to better results compared to using texture features alone.

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.

Extracranial Stereotactic Body Radiotherapy in Oligometastatic or Oligoprogressive Breast Cancer

Purpose/Objective: Oligometastatic disease (OMD) and oligoprogressive disease (OPD) describe tumor states with a limited metastasization. In contrast to other disease states, treatment of OMD or OPD has not yet become common for breast cancer. We sought to understand the outcomes and toxicities of this treatment paradigm.

Material/Methods: We retrospectively analyzed female breast cancer patients with OMD (≤3 metastases) or OPD (1 progressive lesion) who received stereotactic body radiotherapy (SBRT) for their respective extracranial metastatic lesions between 01/2002 and 07/2019. Survival analysis was performed using the Kaplan-Meier method with log-rank test being used for evaluation of significance. Cox regression was used to detect prognostic outcome factors. Toxicity was evaluated using the Common Terminology Criteria for Adverse Events (CTCAE v. 5.0).

Results: Forty-six patients (70% OMD; 30% OPD) with 58 lesions met criteria for inclusion. The majority of treatments (34 out of 58; 58.6%) were delivered from 2017 to 2018. Treatment sites were bone, liver, lung [n = 19 (33%) for each site], and adrenal gland [n = 1 (1%)]. Median biologically effective dose (BED at α/β = 10) was 81.6 Gy (range: 45–112.5 Gy) and median planning target volume was 36.60 mL (range: 3.76–311.00 mL). At 2 years, local control (LC) was 89%, distant control (DC) was 44%, progression free survival (PFS) was 17% and overall survival (OS) was 62%. Multivariate analysis identified the diagnosis of a solitary metastasis as an independent prognostic factor for superior DC (HR = 0.186, CI [0.055; 0.626], p = 0.007) and PFS (HR = 0.363, CI [0.152; 0.863], p = 0.022). OS was independently inferior for patients treated at a higher age (HR = 5.788, CI [1.077; 31.119] p = 0.041). Nine (15.5%) grade I° and one (1.7%) grade II° toxicities were recorded, with no grade III° or higher toxicities.

Conclusion: Extracranial SBRT in breast cancer patients with OMD or OPD was well-tolerated with excellent LC. SBRT should especially be offered to younger OMD and OPD breast cancer patients with only one metastasis. The increase in utilization since 2017 points toward a growing acceptance of SBRT for OMD and OPD in breast cancer.

Epidemiological, clinical and diagnostic profile of breast cancer patients treated at Potchefstroom regional hospital, South Africa, 2012-2018: an open-cohort study

Introduction

Breast cancer is the second most diagnosed cancer worldwide. We aimed to depict the diagnostic approach as well as the epidemiological and clinical profile of patients with breast cancer at Potchefstroom regional hospital, South Africa.

Methods

This descriptive open-cohort study included patients with primary invasive breast cancer, confirmed by histology results and treated at the hospital from 01 January 2012 to 31 December 2018. Data such as demographics, patient history, histology, breast clinical findings, physical mass description and diagnostic investigations were captured from hospital registries and patient files.

Result

One-hundred thirty-eight patients (mean age 56.2 (SD: 14.4) (95% CI 54.6-59.7) years) met inclusion criteria. Most patients were female (98.6%), from African (67.4%) or Caucasian (23.9%) descent. Findings included mostly left-sided breast involvement (51.8%), lesions in the upper-outer quadrant (43.1%), extensions to the skin (25.6%, N = 39), and tumour size of 2 ≤ 5 cm (49.3%), or > 5 cm (39.1%). Most patients (57.9%, N = 135) were categorised as BIRADS-5, with a ductal pattern (89.6%) (p < 0.01). Patients mostly presented in stages II to IV of disease (89.1%; p < 0.05). Late-stage (stages III-IV) at time of diagnosis (n = 84) was significantly associated with mass location (p = 0.006; Cramér's V = 0.280), tumour size (p < 0.001, Cramér's V = 0.239), and skin changes (p = 0.027, Cramér's V = 0.492).

Conclusion

Most patients consulted at a late-stage of the disease, indicating a need for the promotion of breast awareness campaigns, early detection, and timeous referral.

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.

Evaluation of the 8th edition of the American joint committee on cancer's pathological staging system in prognosis assessment and treatment decision making for stage T1-2N1 breast cancer after mastectomy

Purpose

The 8th edition of the American Joint Committee on Cancer (AJCC) pathological staging system for breast cancer considers biologic factors in addition to the anatomical features included in the previous systems. The purpose of this study was to determine the validity of the 8th AJCC staging system for T1-2N1 breast cancer and to assess the effect of additional chemotherapy and radiotherapy according to the new pathologic stages.

Methods

The cohort included patients from the Surveillance, Epidemiology, and End Results program (2010–2012) who had stage T1-2N1 invasive breast carcinoma and underwent mastectomy. All patients were restaged using the 8th AJCC staging system. The Kaplan–Meier method, Cox proportional hazards regression, and competing risks models were used for data analysis.

Results

We identified 9908 patients including 3022 (30.5%), 3131 (31.6%), 1940 (19.6%), 1194 (12.1%), and 621 (6.3%) were classified with stage IA, IB, IIA, IIB, and IIIA disease, respectively. The 5-year breast cancer-specific survival (BCSS) was 97.3%, 94.3%, 88.3%, 84.0%, and 71.1% for stage IA, IB, IIA, IIB, and IIIA disease, respectively. Higher pathological stage was associated with a significantly higher risk of breast cancer-related death. Chemotherapy was associated with better BCSS regardless of the pathological stage, but radiotherapy was only associated with better BCSS in stage IIIA disease.

Conclusions

The 8th AJCC pathological staging system provides more refined stratification for T1-2N1 breast cancer patients after mastectomy and may meet the needs of the current trend of individualized decision making for chemotherapy and radiotherapy in this patient subset.

•

Higher pathological stage was associated with significantly lower BCSS.

•

Chemotherapy was associated with better BCSS regardless of the pathological stage.

•

Radiotherapy was associated with better BCSS in only stage IIIA disease.

FKBP4 is a malignant indicator in luminal A subtype of breast cancer

Purpose: FKBP4 is a member of the immunophilin protein family, which plays a role in immunoregulation and basic cellular processes involving protein folding and trafficking associated with HSP90. However, the relationship between abnormal expression of FKBP4 and clinical outcome in luminal A subtype breast cancer (LABC) patients remains to be elucidated.

Methods: Oncomine, bc-GenExMiner and HPA database were used for data mining and analyzing FKBP4 and its co-expressed genes. GEPIA database was used for screening co-expressed genes of FKBP4.

Results: For the first time, we found that higher FKBP4 expression correlated with LABC patients and worse survival. Moreover, the upregulated co-expressed genes of FKBP4 were assessed to be significantly correlated with worse survival in LABC, and might be involved in the biological role of FKBP4.

Conclusion: The expression status of FKBP4 is a significant prognostic indicator and a potential drug target for LABC.

Assessment of the Prognostic Staging System of American Joint Committee on Cancer 8th Edition for Breast Cancer: Comparisons with the Conventional Anatomic Staging System

Purpose

The 8th edition of the American Joint Committee on Cancer (AJCC) staging manual introduced a new prognostic staging system for breast cancer. This study aimed to evaluate the changes in staging distribution and predictive power of the new staging system.

Methods

Of the 12,275 patients with breast cancer identified from the Severance Breast Cancer Registry who underwent surgery between 1978 and 2016, 12,125 patients met the inclusion criteria.

Results

In both the 7th and 8th staging systems, stage I patients constituted the largest proportion (38.2% and 48.4%). Migration from the 7th to 8th edition of the AJCC manual resulted in a decrease in stage II population and an increase in stage I and III populations. A total of 1,293 (15.4%) patients were upstaged, and 1,201 (14.3%) were downstaged. Downstaged patients had better recurrence-free and overall survival (p < 0.001). Pathologic complete response after neoadjuvant therapy showed good prognosis as p stage 0, and yp stages I and III showed poorer outcomes than the same p stage (p < 0.001).

Conclusions

Staging migrations are common in early breast cancer under the prognostic staging system. The prognostic staging system of the 8th edition of the AJCC manual discriminates survival outcomes better than the anatomical staging system of the 7th edition of the AJCC manual.

AJCC 8th edition prognostic staging provides no better discriminatory ability in prognosis than anatomical staging in triple negative breast cancer

BACKGROUND

We retrospectively compared the prognostic value between the AJCC 8th edition anatomic (AS) and prognostic staging (PS) system for triple negative breast cancer (TNBC) in a cohort from two involved institutions and a large population database.

METHODS

Clinicopathological data of TNBCs were identified in two involved institutions (SYSUCC-PWH cohort). Data from SEER database during 2010-2015 was also accessed. We restaged all cases into AS and PS group according to the AJCC 8th staging system.

RESULTS

A total of 611 and 31,941 TNBCs were identified in two cohorts, with a median follow-up of 53.5 and 27 months respectively. PS upstaged 46.1% of patients in SYSUCC-PWH cohort, and 62.4% in SEER cohort. No significant difference was observed in C index between AS and PS models for disease-specific survival (DSS), progression-free survival (PFS) or overall survival (OS) in either cohort. χ2 statistic and Hazard Ratio for PFS, DSS and OS showed better discrimination between IA and IB, IIB and IIIA, IIIA and IIIB in AS model than PS model. Besides, patients with IIIC unchanged stage showed worse PFS compared to those with AS IIIA or IIIB upstaged to PS IIIC in both cohorts(p = 0.049, p < 0.001).

CONCLUSIONS

Our findings demonstrated that prognostic staging system did not provide better discriminatory ability in predicting TNBCs prognosis than anatomic staging system.

Validation of the AJCC prognostic stage for HER2-positive breast cancer in the ShortHER trial

BACKGROUND

The 8th edition of the American Joint Committee on Cancer (AJCC) staging has introduced prognostic stage based on anatomic stage combined with biologic factors. We aimed to validate the prognostic stage in HER2-positive breast cancer patients enrolled in the ShortHER trial.

METHODS

The ShortHER trial randomized 1253 HER2-positive patients to 9 weeks or 1 year of adjuvant trastuzumab combined with chemotherapy. Patients were classified according to the anatomic and the prognostic stage. Distant disease-free survival (DDFS) was calculated from randomization to distant relapse or death.

RESULTS

A total of 1244 patients were included. Compared to anatomic stage, the prognostic stage downstaged 41.6% (n = 517) of patients to a more favorable stage category. Five-year DDFS based on anatomic stage was as follows: IA 96.6%, IB 94.1%, IIA 92.4%, IIB 87.3%, IIIA 81.3%, IIIC 70.5% (P < 0.001). Five-year DDFS according to prognostic stage was as follows: IA 95.7%, IB 91.4%, IIA 86.9%, IIB 85.0%, IIIA 77.6%, IIIC 67.7% (P < 0.001). The C index was similar (0.69209 and 0.69249, P = 0.975). Within anatomic stage I, the outcome was similar for patients treated with 9 weeks or 1 year trastuzumab (5-year DDFS 96.2% and 96.6%, P = 0.856). Within prognostic stage I, the outcome was numerically worse for patients treated with 9 weeks trastuzumab (5-year DDFS 93.7% and 96.3%, P = 0.080).

CONCLUSIONS

The prognostic stage downstaged 41.6% of patients, while maintaining a similar prognostic performance as the anatomic stage. The prognostic stage is valuable in counseling patients and may serve as reference for a clinical trial design. Our data do not support prognostic stage as guidance to de-escalate treatment.

TRIAL REGISTRATION

EUDRACT number: 2007-004326-25; NCI ClinicalTrials.gov number: NCT00629278.

Evaluation of the Incorporation of Recurrence Score into the American Joint Committee on Cancer Eighth Edition Staging System in Patients with T1-2N0M0, Estrogen Receptor-Positive, Human Epidermal Growth Receptor 2-Negative Invasive Breast Cancer: A Population-Based Analysis

BACKGROUND

The current study aimed to evaluate the predictive performance of the American Joint Committee on Cancer eighth edition staging system in patients with invasive breast cancer based on the Surveillance, Epidemiology, and End Results database.

SUBJECTS, MATERIALS, AND METHODS

Patients diagnosed with T1-2N0M0, estrogen receptor-positive, human epidermal growth factor receptor 2-negative breast cancer from 2010 to 2014 were retrospectively recruited in this analysis. Patients were reassigned to different stages according to the anatomic staging system (AS), prognostic staging system (PS), and prognostic and genomic staging criteria downstaging patients with recurrence score (RS) lower than 11 (PGS_RS11). Cox models were conducted for multivariate analyses, and likelihood ratio (LR) χ², Akaike information criterion (AIC), and Harrell's concordance index (C-index) were calculated for the comparison of different staging systems. Additionally, adjustments were made to generate prognostic and genomic staging criteria downstaging patients with RS lower than 18 (PGS_RS18) and RS lower than 25 (PGS_RS25).

RESULTS

PGS_RS11 was an independent predictor for breast cancer-specific survival, as were PS and AS. Adjusted for age and ethnicity, PGS_RS11 (AIC = 2,322.763, C-index = 0.7482, LR χ² = 113.17) showed superiority in predicting survival outcomes and discriminating patients compared with AS (AIC = 2,369.132, C-index = 0.6986, LR χ² = 60.80) but didn't outperform PS (AIC = 2,320.992, C-index = 0.7487, LR χ² = 114.94). The predictive and discriminative ability of PGS_RS18 was the best (AIC = 2297.434, C-index = 0.7828, LR χ² = 138.50) when compared with PS and PGS_RS11.

CONCLUSION

PGS_RS11 was superior to AS but comparable with PS in predicting prognosis. Further validations and refinements are needed for the better incorporation of RS into staging systems.

IMPLICATIONS FOR PRACTICE

Staging systems are of critical importance in informing prognosis and guiding treatment. This study's objective was to evaluate the newly proposed staging system in the American Joint Committee on Cancer eighth edition staging manual, which combined biological and genomic information with the traditional TNM classification for the first time to determine tumor stages of breast cancer. The superiority of the prognostic and genomic staging system was validated in our cohort and possibly could encourage the utility of genomic assays in clinical practice for staging assessment and prognosis prediction.

Future Aspects for Cannabinoids in Breast Cancer Therapy

Cannabinoids (CBs) from Cannabis sativa provide relief for tumor-associated symptoms (including nausea, anorexia, and neuropathic pain) in the palliative treatment of cancer patients. Additionally, they may decelerate tumor progression in breast cancer patients. Indeed, the psychoactive delta-9-tetrahydrocannabinol (THC), non-psychoactive cannabidiol (CBD) and other CBs inhibited disease progression in breast cancer models. The effects of CBs on signaling pathways in cancer cells are conferred via G-protein coupled CB-receptors (CB-Rs), CB1-R and CB2-R, but also via other receptors, and in a receptor-independent way. THC is a partial agonist for CB1-R and CB2-R; CBD is an inverse agonist for both. In breast cancer, CB1-R expression is moderate, but CB2-R expression is high, which is related to tumor aggressiveness. CBs block cell cycle progression and cell growth and induce cancer cell apoptosis by inhibiting constitutive active pro-oncogenic signaling pathways, such as the extracellular-signal-regulated kinase pathway. They reduce angiogenesis and tumor metastasis in animal breast cancer models. CBs are not only active against estrogen receptor-positive, but also against estrogen-resistant breast cancer cells. In human epidermal growth factor receptor 2-positive and triple-negative breast cancer cells, blocking protein kinase B- and cyclooxygenase-2 signaling via CB2-R prevents tumor progression and metastasis. Furthermore, selective estrogen receptor modulators (SERMs), including tamoxifen, bind to CB-Rs; this process may contribute to the growth inhibitory effect of SERMs in cancer cells lacking the estrogen receptor. In summary, CBs are already administered to breast cancer patients at advanced stages of the disease, but they might also be effective at earlier stages to decelerate tumor progression.

New and important changes in breast cancer TNM: incorporation of biologic factors into staging

INTRODUCTION

Cancer staging has historically been based solely on the anatomic extent of the tumor (T), spread to lymph nodes (N), and the presence of distant metastases (M). More recently biologic factors have been added to modify TNM stage groups to provide more accurate prognosis for patients. Areas covered: The American Joint Committee on Cancer (AJCC) updated breast cancer staging in 2016 to include T, N, M, tumor grade and expression of estrogen and progesterone receptors and HER2. Addition of these factors changed the stage group for a large fraction of cases compared to prior TNM stage groupings. This updated 'prognostic stage' provides more robust and precise prognosis information. Expert opinion: Inclusion of biological information in staging changes the meaning and the use of stage in clinical practice. This paper reviews the evidence supporting these changes, limitations affecting staging, and discusses the implications for clinical practice and the future of breast cancer staging.

The predictive value of the prognostic staging system in the 8th edition of the American Joint Committee on Cancer for triple-negative breast cancer: a SEER population-based analysis

Aim: To examine the stage changes and survival differences among triple-negative breast cancer (TNBC) patients based on the prognostic staging system. Methods: We used the SEER database to identify eligible patients with TNBC diagnosed between 2010 and 2014. Kaplan–Meier curves were drawn for comparison. The primary end point was breast cancer-specific survival. Results: The median follow-up time was 26 months for 19,608 patients. The stages of all TNBC patients increased or remained unchanged during rearrangement from anatomic staging to prognostic staging. Stage IIA, IIIA and IIIC comprised the majority of patients. Several patients did not have prognostic staging. Stage IIIC incorporated six substages that contributed to high heterogeneity. Overall, the Kaplan–Meier curves still showed the favorable differentiation among stages and substages, with the exception of stage IIB and substage IIIA (T2N0, grade 2–3) patients. Conclusion: The prognostic information for breast cancer patients provided by the novel prognostic staging system may be less accurate for TNBC patients in our independent analysis. Moreover, stage IIB and substage IIIA (T2N0, grade 2–3) should possibly undergo further evaluation.

Different prognostic implication of ypTNM stage and pTNM stage for gastric cancer: a propensity score-matched analysis

Background

Pathological stage is considered as the best prognosis indicator for gastric cancer. With the increasing use of neoadjuvant chemotherapy (NACT), the latest TNM staging included a new pathological stage of ypTNM for patients with NACT. However, no study has investigated if ypTNM stage has the same prognostic implication as pTNM stage for gastric cancer.

Methods

We retrospectively selected eligible patients within a prospectively maintained database containing all patients treated with gastric cancer in Peking University Cancer Hospital from 2007 to 2015 using overall survival as the outcome. Patients using ypTNM and pTNM were 1:1 matched by propensity scores (PS) calculated from a model containing variables associated with ypTNM use or survival. Overall survival was compared by unconditional Cox regression. Conventional multivariate analysis was conducted to corroborate PS matching results.

Results

1441 patients were included in the analysis with a median follow-up of 37 months (range = 2–106). The matched sample contained 756 patients. After PS matching, patients with specific ypTNM stage were 1.34 (95%CI = 1.05–1.72, P = 0.019) times more likely to die than patients with the same pTNM stage. Similar to the results of PS matching, multivariate Cox regression yielded a hazard ratio (HR) of 1.35 (95%CI = 1.09–1.67, P = 0.006). Subgroup analysis indicated this survival difference between ypTNM and pTNM stage varied by the specific TNM stage of patients. The HR was 3.44 (95%CI = 1.06–11.18, P = 0.040) and 1.28 (95%CI = 1.00–1.62, P = 0.048) for patients in stage I and III, respectively; whereas for stage II patients, no significant difference was observed (HR = 1.37, 95%CI = 0.78–2.38, P = 0.27).

Conclusion

Gastric cancer patients with specific ypTNM stage had worse prognosis compared to those at the same stage defined by pTNM.

Electronic supplementary material

The online version of this article (10.1186/s12885-019-5283-3) contains supplementary material, which is available to authorized users.

A nomogram to predict prognosis in patients undergoing sublobar resection for stage IA non-small-cell lung cancer

Introduction

This study aimed to develop a practical nomogram to predict prognosis in patients who are undergoing sublobar resection for stage IA non-small-cell lung cancer (NSCLC). Data from Surveillance, Epidemiology, and End Results (SEER) databases were used to construct the nomogram.

Methods

Data from patients undergoing sublobar resection for stage IA NSCLC diagnosed between 2004 and 2014 were extracted from the SEER database. Factors that may predict the outcome were identified using the Kaplan–Meier method and the Cox proportional-hazards model. A nomogram was constructed to predict the 3- and 5-year overall survival (OS) and lung cancer-specific survival (LCSS) rates of these patients. The predictive accuracy of the nomogram was measured using the concordance index (C-index) and calibration curve.

Results

A total of 4,866 patients were selected for this study. Using univariate and multivariate analyses, eight independent prognostic factors associated with OS were identified, including sex (P<0.001), age (P<0.001), race (P=0.043), marital status (P=0.009), pathology (P=0.004), differentiation (P<0.001), tumor size (P<0.001), and surgery (P=0.001), and five independent prognostic factors associated with LCSS were also identified, including sex (P<0.001), age (P<0.001), differentiation (P<0.001), tumor size (P<0.001), and surgery (P=0.011). A nomogram was established based on these results and validated using the internal bootstrap resampling method. The C-index of the established nomogram for OS and LCSS was 0.649 (95% CI: 0.635–0.663) and 0.640 (95% CI: 0.622–0.658), respectively. The calibration curves for probability of 3-, and 5-year OS and LCSS rates demonstrated good agreement between the nomogram prediction and actual observation.

Conclusion

This innovative nomogram delivered a relatively accurate individual prognostic prediction for patients undergoing sublobar resection for stage IA NSCLC.

Identification of a 4-mRNA metastasis-related prognostic signature for patients with breast cancer

Metastasis‐related mRNAs have showed great promise as prognostic biomarkers in various types of cancers. Therefore, we attempted to develop a metastasis‐associated gene signature to enhance prognostic prediction of breast cancer (BC) based on gene expression profiling. We firstly screened and identified 56 differentially expressed mRNAs by analysing BC tumour tissues with and without metastasis in the discovery cohort (GSE102484, n = 683). We then found 26 of these differentially expressed genes were associated with metastasis‐free survival (MFS) in the training set (GSE20685, n = 319). A metastasis‐associated gene signature built using a LASSO Cox regression model, which consisted of four mRNAs, can classify patients into high‐ and low‐risk groups in the training cohort. Patients with high‐risk scores in the training cohort had shorter MFS (hazard ratio [HR] 3.89, 95% CI 2.53‐5.98; P < 0.001), disease‐free survival (DFS) (HR 4.69, 2.93‐7.50; P < 0.001) and overall survival (HR 4.06, 2.56‐6.45; P < 0.001) than patients with low‐risk scores. The prognostic accuracy of mRNAs signature was validated in the two independent validation cohorts (GSE21653, n = 248; GSE31448, n = 246). We then developed a nomogram based on the mRNAs signature and clinical‐related risk factors (T stage and N stage) that predicted an individual's risk of disease, which can be assessed by calibration curves. Our study demonstrated that this 4‐mRNA signature might be a reliable and useful prognostic tool for DFS evaluation and will facilitate tailored therapy for BC patients at different risk of disease.

An accurate regression of developmental stages for breast cancer based on transcriptomic biomarkers

AIM

Breast cancers at different stages have tremendous differences on both phenotypic and molecular patterns. The developmental stage is an essential factor in the clinical decision of treatment plans, but was usually formulated as a classification problem, which ignored the consecutive relationships among them.

MATERIALS & METHODS

This study proposed a regression-based procedure to detect the stage biomarkers of breast cancers. Biomarkers were detected by the Lasso and Ridge algorithms.

RESULTS & CONCLUSION

A collaboration duet of Lasso and Ridge regression algorithms achieved the best performances, with classification accuracy (Acc) equal to 0.8294 and regression goodness-of-fit (R²) equal to 0.7810. The 265 biomarker genes were enriched with the signal peptide-based secretion function with the Bonferroni-corrected p-value equal to 6.9408e-3 and false discovery rate (FDR) equal to 1.1614e-2.

Clinical Differences in Triple-Positive Operable Breast Cancer Subtypes in Korean Patients: An Analysis of Korean Breast Cancer Registry Data

Purpose

Triple-positive breast cancer is defined by estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 (HER2) positivity. Several systemic breast cancer therapies target hormonal and HER2 responsiveness. We compared clinical outcomes of triple-positive disease with those of HER2-enriched and luminal HER2-negative disease and investigated the clinical efficacy of anti-HER2 therapy for triple-positive disease.

Methods

We retrospectively compared overall and recurrence-free survival among cases included in the Korean Breast Cancer Society (KBCS) and Seoul St. Mary's Hospital breast cancer registries and the therapeutic efficacy of trastuzumab for triple-positive and HER2-enriched cases.

Results

KBCS registry data (2006–2010; median follow-up, 76 months) indicated that patients with triple-positive breast cancer had intermediate survival between those with luminal A and HER2-enriched subtypes (p<0.001). Trastuzumab did not improve overall survival among patients with triple-positive breast cancer (p=0.899) in contrast to the HER2-enriched subtype (p=0.018). Seoul St. Mary's Hospital registry data indicated similar recurrence-free survival outcomes (p<0.001) and a lack of improvement with trastuzumab among patients with triple-positive breast cancer (median follow-up, 33 months; p=0.800). Multivariate analysis revealed that patients with triple-positive breast cancer had better overall survival than those with HER2-enriched disease and similar survival as those with the luminal A subtype (triple-positive: hazard ratio, 1.258, p=0.118; HER2-enriched: hazard ratio, 2.377, p<0.001).

Conclusion

Our findings showed that anti-HER2 therapy was less beneficial for treatment of triple-positive breast cancer than for HER2-enriched subtypes of breast cancer, and the triple-positive subtype had a distinct prognosis.

American Joint Committee on Cancer's Staging System for Breast Cancer, Eighth Edition: What the Radiologist Needs to Know

The TNM staging system for cancer was developed by Pierre Denoix in France in the 1940s and 1950s. The North American effort to standardize the TNM system for cancer staging was first organized in 1959 as the American Joint Committee for Cancer Staging and End-Results Reporting, which is now the American Joint Committee on Cancer (AJCC). The most recent edition of the AJCC Cancer Staging Manual, the eighth edition, was globally adopted on January 1, 2018. Previous editions of the manual have relied on anatomic methods of staging alone, which used population-based survival data to predict clinical outcomes. In the era of precision medicine, the major change in the eighth edition is the incorporation of prognostic biomarkers to more accurately predict clinical outcomes and treatment response on an individual basis, without relying solely on the anatomic extent of disease. Factors such as tumor grade, hormone receptor and oncogene expression, and multigene panel recurrence scores are now integrated with anatomic information to yield a final prognostic stage group, which will provide better stratification of patient prognosis. The purpose of this article is to review the major changes in the AJCC eighth edition for breast cancer staging, review anatomic TNM staging, familiarize the radiologist with prognostic biomarkers and prognostic staging, and identify key sites of disease that may alter clinical management. ^©RSNA, 2018.