Validation of the newly proposed American Joint Committee on Cancer (AJCC) breast cancer prognostic staging group and proposing a new staging system using the National Cancer Database

Improvement in breast cancer survival across molecular subtypes in Hungary between 2011 and 2020: a nationwide, retrospective study

Background

Despite well-documented clinical differences across breast-cancer (BC) molecular subtypes and relevant changes in therapeutic interventions over the past decades, there remains a significant lack of up-to-date epidemiologic data and real-world outcomes, particularly in Central and Eastern Europe.

Methods

This was a nationwide, retrospective study using the claims databases of the Hungarian National Health Insurance Fund (NHIF) that included patients who were newly diagnosed with BC between 2011 and 2020. BC subtypes were defined based on the therapies received. Overall survival (OS) and net survival rates were calculated.

Results

Between 2011 and 2020, 74,143 patients were newly diagnosed with BC based on ICD-10 diagnostic codes in the NHIF database and 80.1% of the cases could be classified into subtypes based on therapy. The most common subtype was HER2-/HR+ BC, identified in 61.9% of patients, followed by triple negative breast cancer (TNBC) in 8.4%, HER2+/HR+ BC in 6.2%, and HER2+/HR- BC in 3.6% of cases. The proportions of TNBC and HER2+/HR+ were higher among younger patients, than in elderly cohorts. The 5-year OS of the total BC population was 74.2% in patients diagnosed between 2015-2019. Patients with TNBC had the poorest 5-year OS (TNBC: 61.4%; HER2+/HR+: 86.5%; HER2-/HR+: 79.1%; HER2+/HR-: 71.9%). Net survival rates (i.e. survival rates after adjusting the effects of other causes of death) varied across diagnostic periods and molecular subtypes. In most cases, patients diagnosed later during the study period tended to have numerically better survival rates. Patients with HER2-/HR+ BC had the most favorable net survival, with 5-year net survival exceeding 92% during the whole observation period, while TNBC patients had the lowest 5-year net survival rates ranging between 63.6% and 65.8% during the study period.

Conclusion

Our nationwide study describes the distribution and survival of BC patients with different subtypes based on a retrospective analysis of the health insurance fund database. There remains a significant room for improvement in the survival of more aggressive molecular subtypes including HR-/HER2+ and triple-negative BC, which are more common in younger age cohorts.

Low-positive controls for monitoring progesterone receptor immunohistochemical staining

AIMS

Progesterone receptor (PR) is a crucial prognostic marker in breast cancer. However, achieving consistent results in PR immunohistochemistry (IHC) remains challenging due to the lack of well-defined low-positive controls. This study aimed to identify benign tissues with consistent low-level PR expression to serve as ideal controls for IHC.

METHODS

We evaluated PR expression in the squamous epithelium of the uterine cervix, nipple smooth muscle and pancreatic islets. QuPath digital image analysis was employed to compare the intensity and quantity of PR staining in target cells within a 2×2 mm area.

RESULTS

The squamous epithelium of the secretory phase cervix, nipple smooth muscle and pancreatic islets displayed appreciable weak PR expression, with mean values of 73, 55 and 60 cells, respectively. Notably, 62% (8/13) of the 2×2 mm areas in the atrophic cervix were completely negative for PR expression. The coefficients of variation for weak PR-expressing cells in pancreatic islets (57.4%) and nipple smooth muscle (65.0%) were lower than those observed in the cervix (96.2%-222.0%). The squamous epithelium of the cervix, especially during the secretory phase, exhibited weak positivity confined to the basal layers, providing another viable control option. However, variations in PR expression may be influenced by physiological factors, such as hormonal fluctuations.

CONCLUSIONS

Pancreatic islets and nipple smooth muscle, with their consistent low-level PR expression, offer a promising solution to the challenges associated with PR IHC. This approach may help minimise variations resulting from differing staining methods across laboratories.

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.

A population-level digital histologic biomarker for enhanced prognosis of invasive breast cancer

Breast cancer is a heterogeneous disease with variable survival outcomes. Pathologists grade the microscopic appearance of breast tissue using the Nottingham criteria, which are qualitative and do not account for noncancerous elements within the tumor microenvironment. Here we present the Histomic Prognostic Signature (HiPS), a comprehensive, interpretable scoring of the survival risk incurred by breast tumor microenvironment morphology. HiPS uses deep learning to accurately map cellular and tissue structures to measure epithelial, stromal, immune, and spatial interaction features. It was developed using a population-level cohort from the Cancer Prevention Study-II and validated using data from three independent cohorts, including the Prostate, Lung, Colorectal, and Ovarian Cancer trial, Cancer Prevention Study-3, and The Cancer Genome Atlas. HiPS consistently outperformed pathologists in predicting survival outcomes, independent of tumor-node-metastasis stage and pertinent variables. This was largely driven by stromal and immune features. In conclusion, HiPS is a robustly validated biomarker to support pathologists and improve patient prognosis.

Prognostic Value of Pretreatment Neutrophil-to-Lymphocyte Ratio in HER2-Positive Metastatic Breast Cancer

This study aimed to examine the prognostic value of the neutrophil-to-lymphocyte ratio (NLR) and other clinicopathological features in HER2+ MBC patients who received first-line anti-HER2 therapy. A total of 129 patients were assigned to NLR-low and NLR-high groups based on a cutoff value of 3.0 at baseline. Peripheral blood lymphocyte subsets and gene mutations in circulating tumor DNA were analyzed by flow cytometry and Next-generation sequencing, respectively. Survival was evaluated by the Kaplan−Meier method and Cox regression analysis. Of the 129 patients, 77 and 52 were assigned to the NLR-low (≤3) and NLR-high (>3) groups, respectively. Compared with NLR-high patients, the NLR-low patients had significantly longer median progression-free survival (PFS) (11.7 vs. 7.7 months) (p = 0.001, HR = 2.703 95% CI 1.543−4.736 and overall survival (OS) (37.4 vs. 28.7 months) (p = 0.044, HR = 2.254 95% CI 1.024−4.924). Furthermore, this association was independent of metastatic sites or estrogen receptor status. Peripheral blood CD3+ (p = 0.034) and CD4+ (p = 0.010) T cell numbers were significantly higher in the NLR-low group than the NLR-high group. The mutational profile of MBC was generally similar between the two groups. Baseline NLR was a prognostic factor of PFS and OS for patients with HER2+ MBC in the first-line setting. These results may facilitate the selection of patients who will benefit most from anti-HER2 treatment.

Deep Learning-Based Pathology Image Analysis Enhances Magee Feature Correlation With Oncotype DX Breast Recurrence Score

Background

Oncotype DX Recurrence Score (RS) has been widely used to predict chemotherapy benefits in patients with estrogen receptor-positive breast cancer. Studies showed that the features used in Magee equations correlate with RS. We aimed to examine whether deep learning (DL)-based histology image analyses can enhance such correlations.

Methods

We retrieved 382 cases with RS diagnosed between 2011 and 2015 from the Emory University and the Ohio State University. All patients received surgery. DL models were developed to detect nuclei of tumor cells and tumor-infiltrating lymphocytes (TILs) and segment tumor cell nuclei in hematoxylin and eosin (H&E) stained histopathology whole slide images (WSIs). Based on the DL-based analysis, we derived image features from WSIs, such as tumor cell number, TIL number variance, and nuclear grades. The entire patient cohorts were divided into one training set (125 cases) and two validation sets (82 and 175 cases) based on the data sources and WSI resolutions. The training set was used to train the linear regression models to predict RS. For prediction performance comparison, we used independent variables from Magee features alone or the combination of WSI-derived image and Magee features.

Results

The Pearson's correlation coefficients between the actual RS and predicted RS by DL-based analysis were 0.7058 (p-value = 1.32 × 10-13) and 0.5041 (p-value = 1.15 × 10-12) for the validation sets 1 and 2, respectively. The adjusted R 2 values using Magee features alone are 0.3442 and 0.2167 in the two validation sets, respectively. In contrast, the adjusted R 2 values were enhanced to 0.4431 and 0.2182 when WSI-derived imaging features were jointly used with Magee features.

Conclusion

Our results suggest that DL-based digital pathological features can enhance Magee feature correlation with RS.

Correlation between contrast-enhanced cone-beam breast computed tomography features and prognostic staging in breast cancer

OBJECTIVE

To evaluate whether contrast-enhanced cone-beam breast CT (CE-CBBCT) features can risk-stratify prognostic stage in breast cancer.

METHODS

Overall, 168 biopsy-proven breast cancer patients were analysed: 115 patients in the training set underwent scanning using v. 1.5 CE-CBBCT between August 2019 and December 2019, whereas 53 patients in the test set underwent scanning using v. 1.0 CE-CBBCT between May 2012 and August 2014. All patients were restaged according to the American Joint Committee on Cancer eighth edition prognostic staging system. Following the combination of CE-CBBCT imaging parameters and clinicopathological factors, predictors that were correlated with stratification of prognostic stage via logistic regression were analysed. Predictive performance was assessed according to the area under the receiver operating characteristic curve (AUC). Goodness-of-fit of the models was assessed using the Hosmer-Lemeshow test.

RESULTS

As regards differentiation between prognostic stage (PS) I and II/III, increased tumour-to-breast volume ratio (TBR), rim enhancement pattern, and the presence of penetrating vessels were significant predictors for PS II/III disease (p < 0.05). The AUCs in the training and test sets were 0.967 [95% confidence interval (CI) 0.938-0.996; p < 0.001] and 0.896 (95% CI, 0.809-0.983; p = 0.001), respectively. Two features were selected in the training set of PS II vs III, including tumour volume [odds ratio (OR)=1.817, p = 0.019] and calcification (OR = 4.600, p = 0.040), achieving an AUC of 0.790 (95% CI, 0.636-0.944, p = 0.001). However, there was no significant difference in the test set of PS II vs III (P＞0.05).

CONCLUSION

CE-CBBCT imaging biomarkers may provide a large amount of anatomical and radiobiological information for the pre-operative distinction of prognostic stage.

ADVANCES IN KNOWLEDGE

CE-CBBCT features have distinctive promise for stratification of prognostic stage in breast cancer.

Evaluation of ER, PR and HER2 markers by flow cytometry for breast cancer diagnosis and prognosis

BACKGROUND AND AIMS

Laboratory diagnosis of breast cancer (BC) is done by morphological analysis and immunohistochemistry (IHC). However, this methodology still has some limitations. The aim of this study is to validate flow cytometry (FC) immunophenotyping to investigate diagnostic and prognostic markers of BC.

METHODS

Tumor samples from surgical specimens of patients previously diagnosed with BC, were first sliced and then macerated together with PBS. Then, sample was filtered and the single cell suspension obtained was labeled with antibodies against estrogen (ERα), progesterone (PR) and HER2 receptors and CD45. The results were compared, in terms of sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV), with reference methods.

RESULTS

Results obtained comparing FC with reference methods were: ERα detection (sensitivity: 75%; specificity: 90%; PPV: 96.7%; NPV: 47.4%); PR detection (sensitivity: 72%; specificity: 70%; PPV: 79.3%; NPV: 60.8%); HER2 detection (sensitivity: 80%; specificity: 90.2%; PPV: 66.7%; NPV: 94.9%).

CONCLUSION

The results obtained show the capacity of this methodology on BC markers differentiation. FC, together with morphological analysis and IHC can overcome individual limitations of each methodology and provide reliable results on a faster and efficient manner, resulting in improvements on BC diagnosis and prognosis.

Type 2 Diabetes Mellitus and Clinicopathological Tumor Characteristics in Women Diagnosed with Breast Cancer: A Systematic Review and Meta-Analysis

Poor prognosis caused by type 2 diabetes mellitus (T2DM) in women with breast cancer is conferred, while the association between T2DM and breast tumor aggressiveness is still a matter of debate. This study aimed to clarify the differences in breast cancer characteristics, including stage, size, lymph node status, grade, estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor (Her2), between patients with and without pre-existing T2DM. PubMed, Embase, and Web of Science were searched for studies from 1 January 2010 to 2 July 2021. Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were pooled by using a random effects model. T2DM was significantly associated with tumor stages III/IV versus cancers in situ and stages I/II (pooled ORs (pOR), 95% CI: 1.19; 1.04-1.36, p = 0.012), tumor size >20 versus ≤20 mm (pOR, 95% CI: 1.18; 1.04-1.35, p = 0.013), and lymph node invasion versus no involvement (pOR, 95% CI: 1.26; 1.05-1.51, p = 0.013). These findings suggest that women with T2DM are at a higher risk of late-stage tumors, large tumor sizes, and invasive lymph nodes at breast cancer diagnosis.

Molecular Classification of Triple Negative Breast Cancer and the Emergence of Targeted Therapies

Triple negative breast cancer (TNBC) represents 15% to 20% of all primary breast cancers and is the most aggressive subtype of breast cancer. There has been rapid progress in targeted therapy and biomarker development to identify the optimal treatments for TNBC. To update recent developments, this article comprehensively reviews molecular classification and biomarkers of TNBC and targeted therapy developments in immunotherapy, PARP and AKT pathway inhibitors, antibody-drug conjugates and androgen receptor blockade. The treatment of TNBC has dramatically evolved beyond basic cytotoxic chemotherapy into an expanding domain of targeted therapies tailored to the heterogeneity of this complex and aggressive disease. Progress will continue through the sustained and devoted efforts of our investigators and the patients who dedicatedly enroll in clinical trials. Through a daring persistence to challenge the status quo we now have the opportunity to offer our patients with TNBC a new sense of hope.

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.

Histologic grading of breast carcinoma: a multi-institution study of interobserver variation using virtual microscopy

Breast carcinoma grading is an important prognostic feature recently incorporated into the AJCC Cancer Staging Manual. There is increased interest in applying virtual microscopy (VM) using digital whole slide imaging (WSI) more broadly. Little is known regarding concordance in grading using VM and how such variability might affect AJCC prognostic staging (PS). We evaluated interobserver variability amongst a multi-institutional group of breast pathologists using digital WSI and how discrepancies in grading would affect PS. A digitally scanned slide from 143 invasive carcinomas was independently reviewed by 6 pathologists and assigned grades based on established criteria for tubule formation (TF), nuclear pleomorphism (NP), and mitotic count (MC). Statistical analysis was performed. Interobserver agreement for grade was moderate (κ = 0.497). Agreement was fair (κ = 0.375), moderate (κ = 0.491), and good (κ = 0.705) for grades 2, 3, and 1, respectively. Observer pair concordance ranged from fair to good (κ = 0.354-0.684) Perfect agreement was observed in 43 cases (30%). Interobserver agreement for the individual components was best for TF (κ = 0.503) and worst for MC (κ = 0.281). Seventeen of 86 (19.8%) discrepant cases would have resulted in changes in PS and discrepancies most frequently resulted in a PS change from IA to IB (n = 9). For two of these nine cases, Oncotype DX results would have led to a PS of 1A regardless of grade. Using VM, a multi-institutional cohort of pathologists showed moderate concordance for breast cancer grading, similar to studies using light microscopy. Agreement was the best at the extremes of grade and for evaluation of TF. Whether the higher variability noted for MC is a consequence of VM grading warrants further investigation. Discordance in grading infrequently leads to clinically meaningful changes in the prognostic stage.

Comparison of three lymph node staging methods for predicting outcome in breast cancer patients with mastectomy

Background

Axillary lymph node (ALN) staging is essential in predicting the clinical outcome of breast cancer (BC) patients. Traditionally, it follows the tumor-node-metastasis (TNM) staging, but its accuracy needs further improvement.

Methods

A total of 9,616 BC patients from the Surveillance, Epidemiology, and End Results (SEER) database and 675 patients from the First Affiliated Hospital of China Medical University underwent mastectomy together with ALN dissection were reviewed. Univariate and multivariate logistic analyses were conducted to find the most meaningful factors relevant to prognosis.

Results

After univariate and multivariate analyses, age, race, primary site, radiation, chemotherapy, grade, T-stage, estrogen receptor (ER), progesterone receptor (PR), total number of positive lymph nodes (pN), positive lymph node ratio (LNR) and log odds of positive LNs (LODDS) were found to be significantly associated with overall survival (OS). Using these non-LN risk factors, we further compared the efficacy of three different ALN staging methods in prognosis via nomograms. Harrell's concordance index (C-index) and Akaike Information Criterion (AIC) were used to measure nomogram performance of the ALN staging methods: pN: C-index=0.687 (95% CI: 0.678-0.696), AIC =61,398.24; LNR: C-index =0.691 (95% CI: 0.683-0.701), AIC =61,313.56; and LODDS: C-index =0.691 (95% CI: 0.682-0.700), AIC =61,315.60. We found that the nomogram incorporating LODDS had better predictive ability compared with other two methods. Furthermore, an external validation revealed a C-index of 0.753 (95% CI: 0.690-0.816) for the Asian population, which indicates the nomogram based on LODDS may have universality for both Western and Asian populations.

Conclusions

Compared with pN and LNR, LODDS showed higher homeostasis in LN evaluation, and showed marked efficacy in evaluating survival differences among patients with negative LN staging. We constructed a BC prognosis model by incorporating highly relevant clinical pathological factors and a new method of LN staging, which may greatly aid in guiding postoperative treatment.

Validation of the revised 8th AJCC breast cancer clinical prognostic staging system: analysis of 5321 cases from a single institution

The anatomic stage groups (ASG) have been arguably the most powerful in predicting breast cancer (BC) outcomes. Recognizing the prognostic influence of histologic grade and receptor status, the 8th AJCC mandates their incorporation into the newly established prognostic stage groups (PSG). This staging scheme was subsequently revised to provide pathological and clinical prognostic stage tables (PPSG/CPSG) due to its incapability to categorize a significant subset of BCs, with the former only used for patients having surgical resection as the initial treatment, and the latter for all patients. Given the increasingly used neoadjuvant therapy, PPSG cannot be assigned in a significant proportion of higher staged BCs. In this study, we validated the CPSG in a cohort of 5321 BCs. Compared to ASG, the application of CPSG resulted in assigning 16.1% and 27.2% of cases to a higher or a lower stage group in non-stage IV BCs, respectively. The changes were seen mostly frequently in ASG IB, followed by IIIC, IIB, IIA, IIIA, IIIB, and IA. In 7.9% of cases, the assigned CPSG changed more than one stage group from the ASG. CPSG provided an improved overall discriminating power in predicting BC-specific survival when compared to ASG. Pairwise comparison using the Cox proportional hazard model demonstrated further advantages for CPSG as the latter showed a significant difference in all categories when compared to their proximate groups, except IIA vs. IB and IIIA vs. IIIB. In contrast, a significantly different hazard was only seen when comparing IIB vs. IIA, IIIA vs. IIB, and IV vs. IIIC for ASG. Thus, the revised 8th AJCC CPSG provided a superior overall staging scheme for predicting prognostic outcomes in BC patients receiving standard of care treatment. Further validation using the available data with larger populations and longer follow-up may be needed to refine and improve this table.

Different Breast Cancer Subtypes Show Different Metastatic Patterns: A Study from A Large Public Database

BACKGROUND

Receptor status in breast cancer is known to be related to survival. However, the relationship between breast cancer subtype, preferential sites of metastasis, and overall survival is not clear.

METHODS

A total of 414,528 patients from the National Cancer Database (2010-2013) were examined. All patients received surgery and systemic treatments. Breast cancer was subtyped based on hormonal receptor (HR) and HER2 status.

RESULTS

HR-/HER2+ breast cancer patients had the highest overall rate of metastasis while HR+/HER2- had the lowest. HR+/HER2+ cancer had the most frequent metastasis to the bone, and HR-/HER2+ to brain, liver, lung and multiple sites. Generally, patients with brain or multiple metastasis had the worst overall survival (OS) across different subtypes.  Patients with bone oligometastasis tend to have better OS than patients with metastasis to other site but significantly worse OS than patients without any metastasis.

CONCLUSIONS

This large study exhibits how breast cancer subtype plays a role in the rate and site of metastasis as well as in overall survival.  Surveillance and treatment strategies should be tailored on the risk and potential site of metastases based upon receptor subtype.

Evaluation of PD-L1, tumor-infiltrating lymphocytes, and CD8+ and FOXP3+ immune cells in HER2-positive breast cancer treated with neoadjuvant therapies

BACKGROUND

The tumor immune microenvironment plays a critical role in the prognosis and outcome of breast cancers. This study examined the role of tumor-infiltrating lymphocytes (TILs), CD8+, FOXP3+ lymphocytes, PD-L1 expression, and other clinicopathological parameters in HER2+ breast cancer and correlate with tumor response to neoadjuvant therapy.

METHODS

We included 173 HER2+ patients treated with neoadjuvant HER2-targeted chemotherapy regimens from 2010 to 2016. 67 cases had biopsy blocks to evaluate TIL, CD8, FOXP3, and PD-L1 immunohistochemistry staining. Tumors were classified as pCR vs non-pCR group. Clinicopathological parameters, TIL, CD8+ and FOXP3+ cell count, and PD-L1 expression were correlated with pCR rate.

RESULTS

Univariate analyses showed that pCR rate was significantly correlated with low PR, low ER, high Ki-67, high FOXP3, HER2 IHC3+ , high HER2 ratio and copy number. By multivariate analysis, Ki-67 was the only variable significantly correlated with pCR. PD-L1 expression was detected in 9.2% cases. TIL hotspot has a non-significant correlation with pCR rate (p = 0.096).

CONCLUSIONS

High Ki-67 is a strong predictor for pCR in HER2+ breast cancer. TIL and FOXP3 T cells may play a role in tumor response in HER2+ cancer. PD-L1 is expressed in a subset of HER2+ breast cancer, supporting a role of immunotherapy in treating a subset of HER2+ breast cancers. The role of PD-L1, TIL, and other markers of immunogenicity as predictors of response to neoadjuvant chemotherapy in HER2+ breast cancer should be further evaluated.

Comparison between AJCC 8th prognostic stage and UICC anatomical stage in patients with primary breast cancer: a single institutional retrospective study

BACKGROUND

The 8th edition American Joint Committee on Cancer (AJCC) proposed a prognostic stage (PS), which included not only anatomical factors, but also biological factors. We aimed to investigate the clinicopathological significance of the PS and to compare PS and anatomical stage (AS) that has been established by the Union for International Cancer Control (UICC).

METHODS

Between 2002 and 2017, 800 patients were included in the study. Patients were classified using pathological UICC AS and pathological AJCC PS. The usefulness of PS in comparison with AS was validated using the Akaike information criterion (AIC) and Harrell concordance index (C-index).

RESULTS

A total of 401 (50.1%) patients had pathological AS I, 324 (40.5%) had AS II, and 75 (9.4%) had AS III. Meanwhile, 535 (66.8%) had pathological PS I, 163 (20.4%) had PS II, and 102 (12.8%) had PS III. The number of AS II cases was 1.99-fold higher than that of PS II cases. For each stage, these survival curves were almost similar between AS and PS classification. Therefore, many patients to be classified into stage I and stage III were included in AS II group, while many patients to be classified into stage II were included in AS I group. To trichotomize the survival groups, PS appeared to be more specific than AS, and AIC and C-index confirmed the speculation.

CONCLUSION

For the prognostication of primary breast cancer patients, AJCC PS appeared to be able to stratify the cases more appropriately than UICC AS.

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.

Validation of a Risk Score Incorporating Tumor Characteristics into the American Joint Committee on Cancer Anatomic Stage for Breast Cancer

Purpose

The American Joint Committee on Cancer 8th edition (AJCC8) prognostic stage (PS) was implemented January 1, 2018, but it is complex due to multiple permutations. A North American group proposed a simpler system using the anatomic stage with a risk score system (RSS) of 1 point each for grade 3 tumor and human epithelial growth factor receptor 2 (HER2) and estrogen receptor (ER) negativity. Here we aimed to evaluate this risk score system with our database of Asian breast cancer patients and compare it against the AJCC8 PS.

Methods

Patients diagnosed with breast cancer stage I–IV in 2006–2012 were identified in the SingHealth Joint Breast Cancer Registry. Five-year breast cancer-specific survival (CSS) and overall survival (OS) were calculated for each anatomic stage according to the risk score and compared with the AJCC8 PS.

Results

A total of 6,656 patients were analyzed. The median follow-up was 61 (interquartile range, 37–90) months. There was a high receipt of endocrine therapy (84.6% of ER+ patients), chemotherapy (84.3% of node-positive patients), and trastuzumab (86.0% of HER2+ patients). Within each anatomic stage, there were significant differences in survival in all sub-stages except IIIB. On multivariate analysis, the hazard ratio for negative ER was 1.74 (1.48–2.06), for negative HER2 was 1.49 (1.26–1.74), and for grade 3 was 1.84 (1.55–2.19). On multivariate analysis controlled for age, ethnicity, and receipt of chemotherapy, the RSS (Akaike information criterion [AIC] = 10,649.45; Harrell's Concordance Index [C] = 0.85) was not inferior to the AJCC8 PS (AIC = 10,726.65; C = 0.84) for CSS, nor was the RSS (AIC = 14,714.4; C = 0.82) inferior to the AJCC8 PS (AIC = 14,784.69; C = 0.81) for OS.

Conclusion

The RSS is comparable to the AJCC8 PS for a patient population receiving chemotherapy as well as endocrine- and HER2-targeted therapy and further stratifies stage IV patients.

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.

ER+/HER2+ Breast Cancer Has Different Metastatic Patterns and Better Survival Than ER-/HER2+ Breast Cancer

BACKGROUND

Human epidermal growth factor receptor 2-positive (HER2⁺) breast cancer is generally treated with HER2-targeted therapy combined with chemotherapy. Patients with HER2⁺ and estrogen receptor-positive (ER⁺) cancer are additionally treated with long-term hormone therapy. This study examined the metastatic pattern and prognosis of both ER⁺/HER2⁺ and ER^-/HER2⁺ breast cancer.

PATIENTS AND METHODS

A total of 54,147 patients with HER2⁺ breast cancer from the National Cancer Data Base (NCDB, 2010-2013) and 31,946 patients with HER2⁺ breast cancer from the Surveillance, Epidemiology, and End Results Program (SEER, 2010-2014) were examined. Sites of metastasis and overall survival (OS) were examined in the NCDB, while OS and breast cancer-specific survival were examined in the SEER database.

RESULTS

Compared to ER^-/HER2⁺ breast cancer, ER⁺/HER2⁺ breast cancer was more likely to metastasize to bone but less likely to brain, liver, and lung and less likely to result in multiple metastases. In univariate analysis based on the NCDB, patients with ER^-/HER2⁺ breast cancer had worse OS in all metastasis subsets, including patients who received HER2-targeted therapy. This poor survival for ER^-/HER2⁺ persisted in patients with metastasis to bone and lung, and multiple metastases. In multivariate analysis adjusting for age, tumor grade, surgery, chemotherapy, HER2-targeted therapy, and hormone therapy, ER^-/HER2⁺ patients with bone metastasis still had worse OS. In the SEER, ER^-/HER2⁺ patients had both worse OS and breast cancer-specific survival in univariate analysis.

CONCLUSION

This large study showed patients with ER⁺/HER2⁺ and ER^-/HER2⁺ breast cancers had different metastatic patterns. Patients with ER^-/HER2⁺ breast cancer may require more aggressive treatment.