Novel staging system for predicting disease-specific survival in patients with breast cancer treated with surgery as the first intervention: time to modify the current American Joint Committee on Cancer staging system

Pretreatment Axillary Nodal Volume as a Prognostic Factor for Breast Cancer

Background and Objectives: We evaluated the prognostic value of pretreatment axillary nodal volume in breast cancer patients treated with neoadjuvant systemic therapy. Methods: We retrospectively reviewed 302 breast cancer patients with biopsy-proven axillary LN involvement who received neoadjuvant systemic therapy. Axillary nodal volumes were obtained from pretreatment magnetic resonance imaging. Univariate and multivariate analyses for disease-free survival (DFS) and overall survival (OS) rates were conducted. Results: The median follow-up period was 57.0 months, and 5-year DFS and OS rates were 81.6% and 91.9%, respectively. Pretreatment axillary nodal volume ranged from 0.2 mL to 134.2 mL, and the first tertile (2.6 mL) and fifth quintile (12.0 mL) were chosen as the optimal cutoff points for survival outcomes. In the multivariate analysis, nodal volume (< 2.6 mL vs. 2.6-12.0 mL vs. ≥ 12.0 mL) was a significant prognostic factor for DFS (5-year DFS, 90.1% vs. 79.6% vs. 72.2%) and OS (5-year OS, 97.9% vs. 90.9% vs. 84.2%), whereas the N stage was not. Conclusions: In breast cancer patients treated with neoadjuvant systemic therapy, larger pretreatment axillary nodal volume was associated with poor survival outcomes.

Activity and Efficacy of Neoadjuvant Chemotherapy in Luminal-HER2 Negative Early Breast Cancer According to HER2 Score (Low vs. Score 0): A Retrospective Study

BACKGROUND

The predictive and prognostic role of HER2 status in patients with luminal-HER2 negative early breast cancer (BC) undergoing neoadjuvant chemotherapy is unclear. A retrospective analysis evaluating the correlation between HER2 status (low vs. score 0) and pCR/IDFS was conducted.

METHODS

Patients with BC undergoing neoadjuvant chemotherapy and surgery were included. HER2 low BC was defined as IHC 1+ or 2+ with negative FISH. Logistic regression model and Cox proportional hazard model were adopted to investigate the independent role of HER2 status and outcomes of interest (pCR, CPS-EG and IDFS).

RESULTS

About 566 patients were included: 60% were HER2 low and 40% were HER2 0. pCR was achieved in 13.2% of HER2 low versus 17.7% of HER2 0 (P = .15). There was no correlation between baseline HER2 status and CPS-EG score (P = .18). A trend toward improved IDFS for HER2 low BC was observed (P = .07). The relapse rate of the HER2 0 cohort peaked at 12 months after surgery, similar to the HER2 low cohort, which showed an additional peak at 36 months after surgery.

CONCLUSIONS

Among Luminal-HER2 negative early BCs, our results do not support a clear predictive and prognostic effect of HER2 status, although a trend of worse pCR and better survival for HER2 low BCs cannot be ruled out.

Relative burden of cancer and noncancer mortality among long-term survivors of differentiated thyroid cancer in the US

Background

Limited information is available regarding the relative risks of cancer-specific mortality and noncancer-specific mortality among long-term survivors with differentiated thyroid cancer (DTC).

Methods

In this retrospective study, nationwide data from the Surveillance, Epidemiology, and End Results database (1992-2020) were utilized. The Accelerated Failure Time Model was applied to calculate Survival Time Ratios (TR), with the primary focus on mortality resulting from DTC. The competing risks model was employed to investigate the relative risks of various outcomes in DTC patients with a survival duration of 5 years or more.

Results

In our cohort, 279 patients succumbed to DTC, while 748 died from other diseases. Notably, in DTC cohorts, noncancer-specific mortality rates were consistently higher than DTC-specific mortality rates across different age groups and genders. The risk of DTC and noncancer-specific mortality varied based on the TNM stage. With more advanced disease stages, the risk of DTC and other cancer-specific mortality gradually increased. The cumulative mortality from other cancer-specific causes was consistently the lowest.

Conclusions

In long-term surviving DTC patients, noncancer-specific mortality outweighed DTC-specific mortality irrespective of age and gender. For stage I and II patients, increased attention should be directed toward noncancer-specific mortality in postoperative follow-ups. Conversely, for stage III and IV patients, greater consideration should be given to DTC-related causes of death. In addition, for stage III and IV DTC patients, the risk of death from other cancers was significantly higher than for stages I and II.

Preoperative evaluation of red blood cell distribution width as a promising biomarker for discriminating between benign and malignant breast tumors and assessing breast cancer activity

BACKGROUND

The red cell distribution width (RDW) has been recognized as a new prognostic factor in various pathophysiological states including breast cancers. The aim of this study was to compare the RDW values between patients diagnosed with benign and malignant breast tumors and to evaluate the potential of elevated RDW as a biomarker for breast cancer activity.

MATERIALS AND METHODS

A cross-sectional study compared RDW values in age-matched cohorts diagnosed with benign and malignant breast lesions and correlated them with prognostic factors for malignant breast tumors. The study excluded individuals with inflammatory disorders, pre-neoplastic disease, hematological disorders, or those taking immunosuppressive or anti-inflammatory medications. The RDW values were measured using an automated hematology analyzer. The study's statistical analysis was conducted using SPSS software at a significance level of 0.05.

RESULTS

RDW demonstrated a statistically significant elevation in the cohort of patients with malignant breast tumors, those with metastatic breast tumors, a greater number of infiltrated axillary lymph nodes, larger tumor diameter, and a higher grade of the primary tumor mass.

CONCLUSIONS

The findings of this study suggest that RDW has the potential to serve as a biomarker for assessing breast cancer activity and could offer substantial advantages in clinical contexts. The present study is not without limitations, and the authors suggest that a larger multicenter prospective study be conducted to further validate it's efficacy over an extended duration.

PET/CT and SPECT/CT Imaging of HER2-Positive Breast Cancer

HER2 (Human Epidermal Growth Factor Receptor 2)-positive breast cancer is characterized by amplification of the HER2 gene and is associated with more aggressive tumor growth, increased risk of metastasis, and poorer prognosis when compared to other subtypes of breast cancer. HER2 expression is therefore a critical tumor feature that can be used to diagnose and treat breast cancer. Moving forward, advances in HER2 in vivo imaging, involving the use of techniques such as positron emission tomography (PET) and single-photon emission computed tomography (SPECT), may allow for a greater role for HER2 status in guiding the management of breast cancer patients. This will apply both to patients who are HER2-positive and those who have limited-to-minimal immunohistochemical HER2 expression (HER2-low), with imaging ultimately helping clinicians determine the size and location of tumors. Additionally, PET and SPECT could help evaluate effectiveness of HER2-targeted therapies, such as trastuzumab or pertuzumab for HER2-positive cancers, and specially modified antibody drug conjugates (ADC), such as trastuzumab-deruxtecan, for HER2-low variants. This review will explore the current and future role of HER2 imaging in personalizing the care of patients diagnosed with breast cancer.

Relative Burden of Cancer and Noncancer Mortality Among Long-Term Survivors of Breast, Prostate, and Colorectal Cancer in the US

Importance

Improvements in cancer outcomes have led to a need to better understand long-term oncologic and nononcologic outcomes and quantify cancer-specific vs noncancer-specific mortality risks among long-term survivors.

Objective

To assess absolute and relative cancer-specific vs noncancer-specific mortality rates among long-term survivors of cancer, as well as associated risk factors.

Design, Setting, and Participants

This cohort study included 627 702 patients in the Surveillance, Epidemiology, and End Results cancer registry with breast, prostate, or colorectal cancer who received a diagnosis between January 1, 2003, and December 31, 2014, who received definitive treatment for localized disease and who were alive 5 years after their initial diagnosis (ie, long-term survivors of cancer). Statistical analysis was conducted from November 2022 to January 2023.

Main Outcomes and Measures

Survival time ratios (TRs) were calculated using accelerated failure time models, and the primary outcome of interest examined was death from index cancer vs alternative (nonindex cancer) mortality across breast, prostate, colon, and rectal cancer cohorts. Secondary outcomes included subgroup mortality in cancer-specific risk groups, categorized based on prognostic factors, and proportion of deaths due to cancer-specific vs noncancer-specific causes. Independent variables included age, sex, race and ethnicity, income, residence, stage, grade, estrogen receptor status, progesterone receptor status, prostate-specific antigen level, and Gleason score. Follow-up ended in 2019.

Results

The study included 627 702 patients (mean [SD] age, 61.1 [12.3] years; 434 848 women [69.3%]): 364 230 with breast cancer, 118 839 with prostate cancer, and 144 633 with colorectal cancer who survived 5 years or more from an initial diagnosis of early-stage cancer. Factors associated with shorter median cancer-specific survival included stage III disease for breast cancer (TR, 0.54; 95% CI, 0.53-0.55) and colorectal cancer (colon: TR, 0.60; 95% CI, 0.58-0.62; rectal: TR, 0.71; 95% CI, 0.69-0.74), as well as a Gleason score of 8 or higher for prostate cancer (TR, 0.61; 95% CI, 0.58-0.63). For all cancer cohorts, patients at low risk had at least a 3-fold higher noncancer-specific mortality compared with cancer-specific mortality at 10 years of diagnosis. Patients at high risk had a higher cumulative incidence of cancer-specific mortality than noncancer-specific mortality in all cancer cohorts except prostate.

Conclusions and Relevance

This study is the first to date to examine competing oncologic and nononcologic risks focusing on long-term adult survivors of cancer. Knowledge of the relative risks facing long-term survivors may help provide pragmatic guidance to patients and clinicians regarding the importance of ongoing primary and oncologic-focused care.

A prospective cohort study of clinical characteristics and outcomes in Chinese patients with estrogen receptor-negative/progesterone receptor-positive early breast cancer

PURPOSE

This study aimed to examine the clinical characteristics and outcomes of patients with estrogen receptor-negative (ER-)/progesterone receptor-positive (PR+) early breast cancer. We also aimed to investigate the benefits of adjuvant endocrine therapy (ET) in this patient population.

METHODS

Patients with early breast cancer diagnosed at West China Hospital were divided into the ER-/PR+, ER+, and ER-/PR- groups. The chi-square test was used to analyze differences in clinical and pathological features among the groups. Multivariable Cox and Fine-Gray regression models were used to compare mortality and locoregional recurrence (LRR)/distant recurrence (DR), respectively. We performed a subgroup analysis to determine which ER-/PR+ patients can benefit more from ET.

RESULTS

From 2008 to 2020, we enrolled 443, 7104, and 2892 patients into the ER-/PR+, ER+, and ER-/PR- groups, respectively. The ER-/PR+ group showed more unfavorable clinical features and aggressive pathological characteristics than the ER+ group. The mortality, LRR, and DR rates were higher in the ER-/PR+ than in the ER+ group. Most clinical features and pathological characteristics were similar between the ER-/PR+ and ER-/PR- group and their outcomes were comparable. In the ER-/PR+ group, patients who received ET showed significantly lower LRR and mortality rates than those who did not; however, no difference was observed in DR. Subgroup analysis suggested that ER-/PR+ patients age ≥ 55 years, and postmenopausal status can benefit from ET.

CONCLUSION

ER-/PR+ tumors have more aggressive pathological characteristics and more unfavorable clinical features than ER+ tumors. ET can reduce the LRR and mortality rates in ER-/PR+ patients. Postmenopausal and age ≥ 55 years ER-/PR+ patients can benefit from ET.

Combination of Anatomical and Biological Factors to Predict Disease-Free Survival in Breast Cancer

PURPOSE

The combination of anatomical and biological factors of breast cancer in a new staging system has a prognostic role. This study investigates the prognostic value of the Bioscore among patients with breast cancer with respect to disease-free survival (DFS).

MATERIAL AND METHODS

This study included 317 patients with breast cancer who were identified between January 2015 and December 2018 at Clinical Oncology Department of Assiut University Hospital. Their cancer baseline characteristics were recorded: pathologic stage (PS), T stage (T), nodal stage (N), grade (G), estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor (HER2) status. Univariate and two multivariate analyses were performed to identify which of these variables are associated with DFS. Model performance was quantified using Harrell's concordance index (C-index), and the Akaike information criterion (AIC) was used to compare model fits.

RESULTS

The significant factors in the univariate analysis were PS3, T2, T3, T4, N3, G2, G3, ER-negative, PR-negative, and HER2-negative. In the first multivariate analysis, PS3, G3, and ER-negative were the significant factors, and in the second multivariate analysis, T2, T4, N3, G3, and ER-negative were the significant factors. Two sets of models were built to determine the utility of combining variables. Models incorporating G and ER status had the highest C-index (0.72) for T + N + G + ER in comparison with (0.69) PS + G + ER and the lowest AIC (953.01) for T + N + G + ER and (966.9) for PS + G + ER.

CONCLUSION

Using the Bioscore in breast cancer staging helps to identify patients at increased risk of recurrence. It provides more optimistic prognostic stratification than the anatomical staging alone for DFS.

Development of a nomogram for predicting pathological complete response in luminal breast cancer patients following neoadjuvant chemotherapy

Background

Given the low chance of response to neoadjuvant chemotherapy (NACT) in luminal breast cancer (LBC), the identification of predictive factors of pathological complete response (pCR) represents a challenge. A multicenter retrospective analysis was performed to develop and validate a predictive nomogram for pCR, based on pre-treatment clinicopathological features.

Methods

Clinicopathological data from stage I-III LBC patients undergone NACT and surgery were retrospectively collected. Descriptive statistics was adopted. A multivariate model was used to identify independent predictors of pCR. The obtained log-odds ratios (ORs) were adopted to derive weighting factors for the predictive nomogram. The receiver operating characteristic analysis was applied to determine the nomogram accuracy. The model was internally and externally validated.

Results

In the training set, data from 539 patients were gathered: pCR rate was 11.3% [95% confidence interval (CI): 8.6-13.9] (luminal A-like: 5.3%, 95% CI: 1.5-9.1, and luminal B-like: 13.1%, 95% CI: 9.8-13.4). The optimal Ki67 cutoff to predict pCR was 44% (area under the curve (AUC): 0.69; p < 0.001). Clinical stage I-II (OR: 3.67, 95% CI: 1.75-7.71, p = 0.001), Ki67 ⩾44% (OR: 3.00, 95% CI: 1.59-5.65, p = 0.001), and progesterone receptor (PR) <1% (OR: 2.49, 95% CI: 1.15-5.38, p = 0.019) were independent predictors of pCR, with high replication rates at internal validation (100%, 98%, and 87%, respectively). According to the nomogram, the probability of pCR ranged from 3.4% for clinical stage III, PR > 1%, and Ki67 <44% to 53.3% for clinical stage I-II, PR < 1%, and Ki67 ⩾44% (accuracy: AUC, 0.73; p < 0.0001). In the validation set (248 patients), the predictive performance of the model was confirmed (AUC: 0.7; p < 0.0001).

Conclusion

The combination of commonly available clinicopathological pre-NACT factors allows to develop a nomogram which appears to reliably predict pCR in LBC.

Applying a neoscore in locally advanced rectal cancer is beneficial in predicting local recurrences after surgery

BACKGROUND AND AIM

The current study was undertaken to provide more detailed prognostic models for early prediction of local recurrences and local recurrence free survival (RFS) using different radiologic and pathologic features of locally advanced rectal carcinomas treated with neoadjuvant chemoradiation (CRT).

METHODS

One hundred patients with locally advanced rectal carcinomas decided to receive neoadjuvant CRT were retrospectively recruited, Hazard ratios (HR) were determined in the two cox regression models and only significant ratios were considered for pointing, Models were built to determine their important effects of different predictors including: pathologic T (T), pathologic N (N), grade (G), clinical stage (cTNM), site (S), perineural invasion (PNI), and response to CRT (R) on 3-year RFS, goodness of performance of each model was measured by Harrell's C index.

RESULTS

HR of 1st group of models: T+N, T+N+G, T+N+G+S, T+N+G+S+PNI, and T+N+G+S+PNI+R were summated and categorized into scores, these scores were significantly correlated with the risk of recurrence (Somer's D = 0.5, p<0.0001) & Harrell's C index = 0.751, (Somer's D = 0.6, p<0.0001) & its Harrell's C index = 0.794, (Somer's D = 0.7, p<0.0001) & C index = 0.826, Somer's D = 0.7, p<0.0001) & C index = 0.827, and (Somer's D = 0.7, p<0.0001) & C index = 0.843 respectively. The 2nd group of models including: cTNM stage, cTNM+G, cTNM+G+S, cTNM+G+S+PNI, cTNM+G+S+PNI+R scores which were significantly correlated with the HR of LRR (Somer's D = 0.2, 0.5, 0.6, 0.6, & 0.6 respectively), (p = 0.006, <0.0001, <0.0001, <0.0001, <0.0001 respectively), the corresponding Harrell's C indices were 0.595, 0.743, 0.782, 0.795, & 0.813 respectively.

CONCLUSION

We propose that the addition of biologic factors to staging of rectal cancer provide precise stratification and association with local recurrences in patients received preoperative CRT.

MRI-Based Radiomics for Preoperative Prediction of Lymphovascular Invasion in Patients With Invasive Breast Cancer

Objective

Preoperative identification of lymphovascular invasion (LVI) in patients with invasive breast cancer is challenging due to absence of reliable biomarkers or tools in clinical settings. We aimed to establish and validate multiparametric magnetic resonance imaging (MRI)-based radiomic models to predict the risk of lymphovascular invasion (LVI) in patients with invasive breast cancer.

Methods

This retrospective study included a total of 175 patients with confirmed invasive breast cancer who had known LVI status and preoperative MRI from two tertiary centers. The patients from center 1 was randomly divided into a training set (n=99) and a validation set (n = 26), while the patients from center 2 was used as a test set (n=50). A total of 1409 radiomic features were extracted from the T2-weighted imaging (T2WI), dynamic contrast-enhanced (DCE) imaging, diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC), respectively. A three-step feature selection including SelectKBest, interclass correlation coefficients (ICC), and least absolute shrinkage and selection operator (LASSO) was performed to identify the features most associated with LVI. Subsequently, a Support Vector Machine (SVM) classifier was trained to develop single-layer radiomic models and fusion radiomic models. Model performance was evaluated and compared by the area under the curve (AUC), sensitivity, and specificity.

Results

Based on one feature of wavelet-HLH_gldm_GrayLevelVariance, the ADC radiomic model achieved an AUC of 0.87 (95% confidence interval [CI]: 0.80–0.94) in the training set, 0.87 (0.70-1.00) in the validation set, and 0.77 (95%CI: 0.64-0.86) in the test set. However, the combination of radiomic features derived from other MR sequences failed to yield incremental value.

Conclusions

ADC-based radiomic model demonstrated a favorable performance in predicting LVI prior to surgery in patients with invasive breast cancer. Such model holds the potential for improving clinical decision-making regarding treatment for breast cancer.

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.

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 (χ 2 = 4.366, p = 0.037) and OS (χ 2 = 7.549, p = 0.006); additionally, different prognostic stage groups from the anatomic Stage II group had significant differences in DSS (χ 2 = 7.724, p = 0.021) but no significant differences in OS (χ 2 = 5.182, p = 0.075). However, different prognostic stage groups from anatomic Stage I had no significant differences in either DSS (χ 2= 0.159, p = 0.690) or OS (χ 2 = 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.

A pathologic method for extracting good prognosis group in triple negative breast cancer after neoadjuvant chemotherapy

The area of residual tumor (ART) is a prognostic factor in patients treated with neoadjuvant chemotherapy (NAC) for lung, pancreatic, and rectal cancers. This study aimed to evaluate the usefulness of ART as a method for predicting the prognosis of triple-negative breast cancer (TNBC) patients after neoadjuvant chemotherapy. We included 143 patients with TNBC treated with NAC. The ART at the maximum cut surface of the residual tumor was measured. We divided the patients into three groups: ART-0 (ART=0 mm² ), ART-low (0 mm² < ART ≤ 136mm² ), and ART-high (ART > 136 mm² ), and compared their clinicopathological factors and prognosis. There were no significant differences in both recurrence-free survival (RFS) and overall survival (OS) between ART-0 and ART-low; however, the ART-high group had significantly shorter RFS and OS than the ART-0 and ART-low groups. Multivariate analysis showed that ART-0, and -low and ypN (-) were independent favorable prognostic factors for RFS. Groups with both ART-low and ypN(-) as well as those with ART-0 and ypN(-) showed significantly longer OS and RFS than the other groups (p<0.05). Moreover, there was no significant difference in the RFS and OS between the ART-0 and ypN(-) groups and the ART-low and ypN(-) groups (p=0.249 and p=0.554, respectively). We concluded that ART is a candidate histopathological evaluation method for predicting the prognosis of TNBC patients treated with NAC. Furthermore, postoperative chemotherapy could be omitted in patients with ART-0 and ypN(-) (pathological complete response) and those with ART-low and ypN(-).

A simplified breast cancer prognostic score: comparison with the AJCC clinical prognostic staging system

There have been many breast cancer prognostic models proposed in the last few decades, varying in their methods of development and validation, predictors, outcomes, and patients included. Most models were developed to assess prognostic outcomes for early breast cancers. In this study, we established a simplified prognostic score to predict survival outcomes in all breast cancer patients. A total of 36,152 breast cancer patients diagnosed between 2010 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were used as the training dataset. Multivariate analyses were performed to identify independent factors for disease-specific survival (DSS). A prognostic score was calculated by summing the point values based on the magnitude of the hazard ratio for all independent factors. The authors institutional cohort (n = 4982) was used as the validation dataset. The prognostic score model consisting of histologic grade, ER, PR, HER2, and TNM status demonstrated a similar predictive power when compared to the revised 8th AJCC Clinical Prognostic Staging system in both training and validation datasets, whereas the addition of age and race did not facilitate stratification of prognostic groups. Pairwise comparison of hazard ratios showed a significant difference in all categories when compared to their proximate groups in both prognostic schemes in the SEER database, while the prognostic score model demonstrated a slightly better discriminating power in the validation dataset. Thus, the proposed prognostic score showed at least a comparable predicting power for survival outcomes in breast cancer patients receiving standard-of-care treatment when compared to the AJCC Clinical Prognostic Stage. This prognostic model provides a convenient and alternative modality in clinical practice thus warranting further validation using larger cohorts with longer follow-up.

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

BACKGROUND

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

METHODS AND MATERIALS

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

RESULTS

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

CONCLUSIONS

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

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.

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.

Breast Cancer Staging: Updates in the AJCC Cancer Staging Manual, 8th Edition, and Current Challenges for Radiologists, From the AJR Special Series on Cancer Staging

The standardization of the AJCC TNM staging system for breast cancer allows physicians to evaluate patients with breast cancer using standard language and criteria, assess treatment response, and compare patient outcomes. Previous editions of the AJCC Cancer Staging Manual relied on the anatomic TNM method of staging that incorporates imaging and uses population-level survival data to predict patient outcomes. Recent advances in therapy based on biomarker status and multigene panels have improved treatment strategies. In the newest edition of the AJCC Cancer Staging Manual (8th edition, adopted on January 1, 2018), breast cancer staging integrates anatomic staging with tumor grade, biomarker data regarding hormone receptor status, oncogene expression, and gene expression profiling to assign a prognostic stage. This article reviews the 8th edition of the AJCC breast cancer staging system with a focus on anatomic staging and the challenges that anatomic staging poses for radiologists. We highlight key imaging findings that impact patient treatment and discuss the role of imaging in evaluating response to neoadjuvant therapy. Finally, we discuss biomarkers and multigene panels and how these impact prognostic stage. The review will help radiologists identify critical findings that affect breast cancer staging and understand ongoing limitations of imaging in staging.

Molecular Subtypes of Breast Cancer: A Review for Breast Radiologists

Gene expression profiling has reshaped our understanding of breast cancer by identifying four molecular subtypes: (1) luminal A, (2) luminal B, (3) human epidermal growth factor receptor 2 (HER2)-enriched, and (4) basal-like, which have critical differences in incidence, response to treatment, disease progression, survival, and imaging features. Luminal tumors are most common (60%-70%), characterized by estrogen receptor (ER) expression. Luminal A tumors have the best prognosis of all subtypes, whereas patients with luminal B tumors have significantly shorter overall and disease-free survival. Distinguishing between these tumors is important because luminal B tumors require more aggressive treatment. Both commonly present as irregular masses without associated calcifications at mammography; however, luminal B tumors more commonly demonstrate axillary involvement at diagnosis. HER2-enriched tumors are characterized by overexpression of the HER2 oncogene and low-to-absent ER expression. HER2+ disease carries a poor prognosis, but the development of anti-HER2 therapies has greatly improved outcomes for women with HER2+ breast cancer. HER2+ tumors most commonly present as spiculated masses with pleomorphic calcifications or as calcifications alone. Basal-like cancers (15% of all invasive breast cancers) predominate among "triple negative" cancers, which lack ER, progesterone receptor (PR), and HER2 expression. Basal-like cancers are frequently high-grade, large at diagnosis, with high rates of recurrence. Although imaging commonly reveals irregular masses with ill-defined or spiculated margins, some circumscribed basal-like tumors can be mistaken for benign lesions. Incorporating biomarker data (histologic grade, ER/PR/HER2 status, and multigene assays) into classic anatomic tumor, node, metastasis (TNM) staging can better inform clinical management of this heterogeneous disease.

Prognostic and predictive parameters in breast pathology: a pathologist's primer

The pathologist's role in the breast cancer treatment team has evolved from rendering a diagnosis of breast cancer, to providing a growing list of prognostic and predictive parameters such that individualized treatment decisions can be made based on likelihood of benefit from additional treatments and potential benefit from specific therapies. In all stages, ER and HER2 status help segregate breast cancers into treatment groups with similar outcomes and treatment response rates, however, traditional pathologic parameters such as favorable histologic subtype, size, lymph node status, and Nottingham grade also have remained clinically relevant in early stage disease decision-making. This is especially true for the most common subtype of breast cancer; ER positive, HER2 negative disease. For this same group of breast cancers, an ever-expanding list of gene-expression panels also can provide prediction and prognostication about potential chemotherapy benefit beyond standard endocrine therapies, with the 21-gene Recurrence Score, currently the only prospectively validated predictive test for this purpose. In the more aggressive ER-negative cancer subtypes, response to neoadjuvant therapy and` the extent of tumor infiltrating lymphocytes (TILs) are more recently recognized powerful prognostic parameters, and clinical guidelines now offer additional treatment options for those high-risk patients with residual cancer after standard neoadjuvant therapy. In stage four disease, predictive tests like germline BRCA status, tumor PIK3CA mutation status (in ER+ metastatic disease) and PDL-1 status (in triple negative metastatic disease) are now used to determine additional new treatment options. The objective of this review is to describe the latest in prognostic and predictive parameters in breast cancer as they are relevant to standard pathology reporting and how they are used in breast cancer clinical treatment decisions.

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 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.

Implications for Breast Cancer Restaging Based on the 8th Edition AJCC Staging Manual

OBJECTIVE

We assessed the changes that have resulted from the latest breast cancer staging guidelines and the potential impact on prognosis.

BACKGROUND

Contemporary data suggest that combining anatomic staging and tumor biology yields a predictive synergy for determining breast cancer prognosis. This forms the basis for the American Joint Committee on Cancer's (AJCC) Staging Manual, 8th edition. We assessed the changes that have resulted from the new staging guidelines and the potential impact on prognosis.

METHODS

Women with stages I to III breast cancer from 2010 to 2014 in the National Cancer Data Base were pathologically staged according to the 7th and 8th editions of the AJCC Staging Manual. Patient characteristics and restaging outcomes were summarized. Unadjusted overall survival (OS) was estimated, and differences were assessed. Cox proportional-hazards models were utilized to estimate the adjusted association of stage with OS.

RESULTS

After restaging the 493,854 women identified, 6.8% were upstaged and 29.7% were downstaged. The stage changes varied by tumor histology, receptor status, tumor grade, and Oncotype DX scores (all P < 0.0001). Applying the 8th edition criteria yielded an incremental reduction in survival for each increase in stage, which was not consistently seen in the 7th edition. In a subgroup analysis based on hormone receptor (HR) status, those with stages II and III, and HR- disease had a worse OS than those with HR+ disease.

CONCLUSIONS

Applying the 8th edition staging criteria resulted in a stage change for >35% of patients diagnosed with invasive breast cancer and refined OS estimates. Overall, the transition to the 8th edition is expected to better drive clinical care, treatment recommendations, and future research.

Evaluating overall survival and competing risks of survival in patients with early-stage breast cancer using a comprehensive nomogram

BACKGROUND

Patients with early-stage breast cancer (BC) live long but have competing comorbidities. This study aimed to estimate the effect of cancer and other causes of death in patients with early-stage BC and further quantify the survival differences.

MATERIALS AND METHODS

Data of patients diagnosed with BC between 2010 and 2016 were collected from the Surveillance, Epidemiology, and End Results database. The cumulative incidence function for breast cancer-specific mortality (BCSM) and other cause-specific mortality (OCSM) was estimated, and the differences were tested using the Gray test. The nomogram for estimating 3-, 4-, and 5-year overall survival (OS), breast cancer-specific survival, and other cause-specific survival was established based on Cox regression analysis and Fine and Gray competing risk analysis. The discriminative ability, calibration, and precision of the nomogram were evaluated and compared using C statistics, calibration plots, and area under the receiver operating characteristic curve.

RESULTS

A total of 196 304 eligible patients with early-stage BC were identified in this study. Of these, 12 417 (6.3%) patients died: 5628 (45.3%) due to BC and 6789 (54.7%) due to other causes. Five validated variables were incorporated to develop the prognostic nomogram: age, grade, tumor size, subtype, and surgery of primary site (Figure 3). Age was a strong predictive factor, which was more obvious in OCSM. The effect of surgery was more prominent in BCSM. Increased tumor size was correlated with OS and BCSM and slightly correlated with OCSM. Grade and subtype differences were more predominant in BCSM than in OCSM. The established nomogram was well calibrated and displayed good discrimination.

CONCLUSIONS

We evaluate OS and competing risks of death in patients with early-stage BC, establishing the first comprehensive prognostic nomogram.

Incorporation of clinical and biological factors improves prognostication and reflects contemporary clinical practice

We developed prognostic models for breast cancer-specific survival (BCSS) that consider anatomic stage and other important determinants of prognosis and survival in breast cancer, such as age, grade, and receptor-based subtypes with the intention to demonstrate that these factors, conditional on stage, improve prediction of BCSS. A total of 20,928 patients with stage I–III invasive primary breast cancer treated at The University of Texas MD Anderson Cancer Center between 1990 and 2016, who received surgery as an initial treatment were identified to generate prognostic models by Fine-Gray competing risk regression model. Model predictive accuracy was assessed using Harrell’s C-index. The Aalen–Johansen estimator and a selected Fine–Gray model were used to estimate the 5-year and 10-year BCSS probabilities. The performance of the selected model was evaluated by assessing discrimination and prediction calibration in an external validation dataset of 29,727 patients from the National Comprehensive Cancer Network (NCCN). The inclusion of age, grade, and receptor-based subtype in addition to stage significantly improved the model predictive accuracy (C-index: 0.774 (95% CI 0.755–0.794) vs. 0.692 for stage alone, p < 0.0001). Young age (<40), higher grade, and TNBC subtype were significantly associated with worse BCSS. The selected model showed good discriminative ability but poor calibration when applied to the validation data. After recalibration, the predictions showed good calibration in the training and validation data. More refined BCSS prediction is possible through a model that has been externally validated and includes clinical and biological factors.

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.

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Higher pathological stage was associated with significantly lower BCSS.

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

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

Comparative Analysis of Proposed Strategies for Incorporating Biologic Factors into Breast Cancer Staging

BACKGROUND

Tumor biology is an important prognostic factor in breast cancer. This study aimed to compare three staging systems incorporating both biologic factors and anatomic staging (AJCC 8th-edition pathologic prognostic staging, Bioscore, and Risk Score) in a large population-based cohort.

METHODS

The Surveillance, Epidemiology and End Results program was used to select patients with primary stages 1-4 breast cancer diagnosed in 2010. Patients with inflammatory carcinoma, those with missing data for biologic factors, and those with stages 1-3 disease not treated with surgery were excluded from the study. Estimates of 5-year disease-specific survival (DSS) were calculated using the Kaplan-Meier method. The Harrel concordance index (C-index) and the Akaike Information Criterion were used to compare each model in terms of predicting DSS.

RESULTS

The study included 21,901 patients with a median age of 60 years. The median follow-up period was 52 months. All the staging models stratified DSS, with a stepwise decrease in DSS for each increase in risk category or score. The C-index of each model incorporating biologic factors was higher than the C-index for anatomic staging alone (C-index: 0.832 vs. 0.856 for AJCC pathologic prognostic staging, 0.856 for Bioscore, and 0.864 for Risk Score, all p < 0.001). The staging systems incorporating biologic factors did not differ significantly in terms of model fit.

CONCLUSION

Staging systems incorporating biologic factors perform better than anatomic staging alone. Implementation of the AJCC 8th-edition pathologic prognostic staging was an important initial step in the inclusion of tumor biology in staging. Given its simplicity and ease of use, the Risk Score should be given consideration as an alternative staging system.

Proposal for a Histological Staging System of Mammary Carcinomas in Dogs and Cats. Part 2: Feline Mammary Carcinomas

Background: Feline mammary carcinomas (FMCs) are characterized by a high frequency of metastatic spread. The clinical TNM (Tumor, Node, Metastasis) system is used to describe local, regional, and distant tumor extent within the patient, but few publications confirmed its association with survival in cats with FMC. The purpose of this study was to determine if the histological staging system proposed for dogs in part 1 of this article had significant association with prognosis in cats.

Materials and Methods: This retrospective study included 395 female cats with a surgically removed mammary carcinoma, with a 2-year follow-up. Invasiveness (distinction between in situ and invasive FMCs), the pathologic tumor size (pT), lymphovascular invasion (LVI), and the pathologic nodal stage (pN) defined a 5-stage system: Stage 0 (FMCs in situ), Stage I (pT1, LVI–, pN0–pNX), Stage II (pT2, LVI–, pN0–pNX), Stage IIIA (pT1, LVI+ and/or pN+), and Stage IIIB (pT2, LVI+ and/or pN+), where pT1 was ≤20 mm, pT2 was >20 mm, and pNX corresponded to unsampled draining lymph node.

Results: Higher histological stages were associated with reduced disease-free interval, overall survival, and specific survival. For cancer-specific survival, by univariate analysis (p < 0.0001), median survival times and 1-year specific survival rates (1ySSR) were: stage 0 (1484 days; 1ySSR = 85%; N = 55; 14% of the cats), stage I (808 days; 1ySSR = 76%; N = 103; 26%), stage II (377 days; 1ySSR = 51%; N = 56; 14%), stage IIIA (448 days; 1ySSR = 60%; N = 83; 21%), and stage IIIB (207 days; 1ySSR = 29%; N = 98; 25%). The histological stages were also associated with specific survival by multivariate analysis (Hazard Ratio (HR) = 2.72 for stage IIIB, HR = 1.76 for stage IIIA, HR = 1.50 for stage II compared with stage I), independently of Progesterone Receptor expression (HR = 0.34 for PR+ compared with PR– FMCs) and tumor-associated inflammation (HR = 1.33 when moderate to severe compared with absent to mild).

Conclusion: A same histological staging system could be applied in dogs and cats with mammary carcinoma to refine prognosis assessment. In the near future, a preoperative complete tumor clinical staging and treatment based on the published standard of care should be performed in order to better validate the histological staging system here proposed.

Validation Study of the American Joint Committee on Cancer Eighth Edition Prognostic Stage Compared With the Anatomic Stage in Breast Cancer

Importance

The American Joint Committee on Cancer (AJCC) eighth edition staging manual introduced a new prognostic stage for breast cancer incorporating biologic factors in addition to traditional anatomic factors.

Objective

To perform a validation study of the AJCC eighth edition prognostic stage in a single-institution cohort and a large population database.

Design, Setting, and Participants

Patients with breast cancer treated with surgery as an initial intervention were identified in a prospective institutional database from The University of Texas MD Anderson Cancer Center and the California Cancer Registry. Vital status data were complete through December 31, 2016, in The University of Texas MD Anderson cohort and through December 31, 2014, in the California Cancer Registry cohort. Patients receiving neoadjuvant systemic therapy, those with inflammatory or rare breast cancers, and those with unknown clinicopathologic factors were excluded. Factors evaluated included T, N, and M categories and tumor grade, as well as estrogen receptor, progesterone receptor, and HER2 status.

Main Outcomes and Measures

Disease-specific survival was calculated by the Kaplan-Meier method. The Harrell concordance index (C index) was used to quantify models' predictive performance, and the Akaike information criterion (AIC) was used to compare model fits.

Results

A total of 3327 patients with stage I to IIIC breast cancer treated between 2007 and 2013 at The University of Texas MD Anderson Cancer Center (median follow-up of 5 years) with complete clinicopathologic data were identified. Compared with the AJCC anatomic stage, the prognostic stage upstaged 29.5% of patients and downstaged 28.1%. The prognostic stage (C index, 0.8357 and AIC, 816.8) provided more accurate stratification with respect to disease-specific survival than the anatomic stage (C index, 0.737 and AIC, 1039.8) (P < .001 for the C index). A total of 54 727 patients with stage I to IV breast cancer treated between 2005 and 2009 were identified in the California Cancer Registry (median follow-up of 7 years). The prognostic stage upstaged 31.0% of patients and downstaged 20.6%. The prognostic stage (C index, 0.8426 and AIC, 80 661.68) performed better than the anatomic stage (C index, 0.8097 and AIC, 81 577.89) (P < .001 for the C index).

Conclusions and Relevance

The prognostic stage provided more accurate prognostic information than the anatomic stage alone in both a single-institution cohort and a large population database, thereby supporting its use in breast cancer staging.

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.

Comparison of the 7th and 8th edition of American Joint Committee on Cancer (AJCC) staging systems for breast cancer patients: a Surveillance, Epidemiology and End Results (SEER) Analysis

Background

The 8th edition of the American Joint Committee on Cancer (AJCC) staging system for breast cancer has incorporated tumor grade, estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 status as staging biologic factors reflecting prognosis. The purpose of this study was to compare the 7th and 8th edition of AJCC staging system for prognostic impact.

Materials and methods

Primary breast cancer patients diagnosed from 2010 to 2014 were identified using the Surveillance, Epidemiology and End Results 18 registries research database. Breast cancer-specific survival (BCSS) and overall survival (OS) between stages were estimated using the Kaplan–Meier method and compared using the log-rank test. Multivariable analysis was performed using Cox proportional hazards regression analysis to identify factors independently associated with outcome. Akaike’s information criterion (AIC) was calculated to estimate how well the staging system fitted the data and the complexity of the model.

Results

A total of 184,221 primary breast cancer patients were identified in the 7th AJCC staging system; 16,145 (8.8%) patients could not be categorized according to 8th AJCC prognostic staging system leaving 168,076 patients included for final analyses. The 8th AJCC performed well with the BCSS and OS concordant with stage. A total of 89,494 (53.2%) of patients were restaged to a different stage group in the 8th AJCC; stage IIIA in the 7th AJCC migrated to stage IB with a worse prognosis than IIA and IIB in the 8th AJCC. Nevertheless, the 8th AJCC had a better AIC than the 7th staging system.

Conclusion

The prognostic accuracy of the 8th AJCC staging system was generally superior to the 7th AJCC, although subtle differences between the two systems should be noted in comparative studies.

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.

Introduction of a New Staging System of Breast Cancer for Radiologists: An Emphasis on the Prognostic Stage

In 2017, the American Joint Committee on Cancer announced the 8th edition of its cancer staging system. For breast cancer, the most significant change in the staging system is the incorporation of biomarkers into the anatomic staging to create prognostic stages. Different prognostic stages are assigned to tumors with the same anatomic stages according to the tumor grade, hormone receptor (estrogen receptor; progesterone receptor) status, and HER2 status. A Clinical Prognostic Stage is assigned to all patients regardless of the type of therapy used; in contrast, a Pathologic Prognosis Stage is assigned to patients in whom surgery is the initial treatment. In a few situations, low Oncotype DX recurrence scores can change the prognostic stage. The radiologists need to understand the importance of the biologic factors that can influence cancer staging.

Incorporating Biology Into Breast Cancer Staging: American Joint Committee on Cancer, Eighth Edition, Revisions and Beyond

Higher-quality imaging, refined surgical procedures, enhanced pathologic evaluation, and improved understanding of the impact of tumor biology on treatment and prognosis have necessitated revisions of the AJCC breast cancer staging system. The eighth edition includes clinical and pathologic prognostic stages that incorporate biologic variables-grade, estrogen and progesterone receptor status, HER2 status, and multigene panels-with the anatomic extent of disease defined by tumor, node, and metastasis categories. The prognostic staging systems facilitate more refined stratification with respect to survival than anatomic stage alone. Because the prognostic staging systems are dependent on biologic factors, accuracy is dependent on rigorous pathologic evaluation of tumors and on administration of treatment dictated by tumor biology. It is anticipated that technological advances will facilitate even more refined determination of underlying biology within tumors and in the peripheral blood, which increasingly is being evaluated as a compartment that reflects the primary tumor and sites of distant metastases. Diseases should be staged according to the eighth edition staging system to accurately reflect prognosis and to allow standardized data collection. Such standardization will facilitate assessment of the impact of advances in diagnosis and treatment of patients with breast cancer.

M-bioscore: proposing a new statistical model for prognostic factors in metastatic breast cancer patients

AIM

The current study aims to propose and internally validate 'M-bioscore', which is a model to help predict the outcomes of untreated metastatic breast cancer patients.

METHODOLOGY

Surveillance, epidemiology and end results (SEER) database (2010-2013) was accessed. Patients were divided into two groups: a training set and a validation set. Through a Cox proportional model, multivariate analysis for potential prognostic factors was performed. M-bioscore was calculated for all patients. Survival analyses were conducted through Kaplan-Meier analysis/log-rank testing.

RESULTS

A total of 6655 metastatic breast cancer patients were analyzed. In the training set, the following factors were linked to better cancer-specific survival in multivariate analysis: estrogen receptor positivity, isolated distant nodal metastases, progesterone receptor positivity, lower nuclear grade and HER2 neu positivity (p < 0.01). Cancer-specific survival was then assessed according to M-bioscore. Adjusted Cox regression cause-specific hazard (using breast cancer death as the event of interest) was evaluated in the validation cohort. Pairwise hazard ratio comparisons between different scores were significant (p < 0.05) except for the comparison between score 6 and 7. C-index for the validation cohort was 0.665 (Standard error (SE): 0.010; 95% CI: 0.646- 0.685).

CONCLUSION

M-bioscore can predict the outcomes of untreated metastatic breast cancer patients. Validation of external datasets is needed.

Racial disparities in chemotherapy administration for early-stage breast cancer: a systematic review and meta-analysis

PURPOSE

We conducted a systematic review and meta-analysis to measure the extent to which race is associated with delayed initiation or receipt of inadequate chemotherapy among women with early-stage breast cancer.

METHODS

We performed a systematic search of all articles published from January 1987 until June 2017 within four databases: PubMed/Medline, EMBASE, CINAHL, and Cochrane CENTRAL. Eligible studies were US-based and examined the influence of race on chemotherapy delays, cessation, or dose reductions among women with stage I, II, or III breast cancer. Data were pooled using a random effects model.

RESULTS

A total of twelve studies were included in the quantitative analysis. Blacks were significantly more likely than whites to have delays to initiation of adjuvant therapy of 90 days or more (OR 1.41, 95% CI 1.06-1.87; X² = 31.05, p < 0.00001; I² = 90%). There was no significant association between race and chemotherapy dosing. Due to overlap between studies assessing the relationship between race and completion of chemotherapy, we conducted two separate analyses. Black patients were significantly more likely to discontinue chemotherapy, however, this was no longer statistically significant when larger numbers of patients with more advanced (stage III) breast cancer were included.

CONCLUSIONS

These results suggest that black breast cancer patients experience clinically relevant delays in the initiation of adjuvant chemotherapy more often than white patients, which may in part explain the increased mortality observed among black patients.

Anatomy and Breast Cancer Staging: Is It Still Relevant?

Breast cancer staging concisely summarizes disease status, creating a framework for assessing and relaying prognostic information. The fundamental concepts and components of breast cancer staging are reviewed. The AJCC Cancer Staging Manual, which includes traditional anatomic factors, now includes additional tumor characteristics: tumor grade, estrogen receptor status, progesterone receptor status, human epidermal growth factor receptor 2 status, and (when available) multigene panel testing from the primary tumor. With these updates, staging provides the most reliable system for accurately predicting patient outcome. When the AJCC 8th edition guidelines are adopted, they will more closely reflect tumor biology.

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

BACKGROUND

The eighth edition of AJCC cancer staging manual incorporated biomarker status into the prognostic staging group (PSG). We used data from National Cancer Database (NCDB) to validate and improve the PSG.

METHODS

All patients had surgery and at least some systemic treatment (endocrine therapy, chemotherapy or HER2 targeted therapy). Information from 420,520 patients was assessed for potential predictors of overall survival (OS), including age at diagnosis (age), tumor grade (G), hormonal receptor and HER2 status, and presence of lymph vascular invasion (LVI), stratified by stage or sub-stages. Based on the multivariate Cox analyses, we built different point systems to predict OS and evaluated the different point systems by Akaike's information criterion (AIC), Harrell's concordance index (C-index), and Uno's concordance index.

RESULTS

Age, G, hormonal receptor and HER2 status, LVI and being TNBC were significantly associated with OS (all P < 0.0001). Three staging systems were correlated with OS: system 1 was the conventional anatomic TNM staging; system 2 included TNM, age, G, hormonal receptor, HER2, and LVI; system 3 included TNM, age, G, TNBC versus non-TNBC, and LVI. System 3 (C-index; 0.7316; AIC: 488138.91) achieved the best balance between predictive performance and goodness-of-fit to the NCDB data as compared to system 2 (C-index: 0.7325; AIC: 498087.73) and system 1 (C-index: 0.716; AIC: 688536.49).

CONCLUSIONS

The new PSG is a better staging system than the conventional anatomic TNM system. Grouping breast cancer into TNBC versus non-TNBC may be simpler while retaining similar accuracy as using ER/PR/HER2 status to predict OS.

Survival Comparisons Between Early Male and Female Breast Cancer Patients

We aimed to compare the overall survival (OS) and standardized mortality rate (SMR) of the male breast cancer (MBC) with female breast cancer (FBC) after propensity score matching. Based on the Surveillance, Epidemiology, and End Results (SEER), the early breast cancer patients (T1-2N0-2M0) were extracted from 1998-2007. This study included 1,111 and 2,151 patients with early MBC and FBC, respectively, whose clinicopathological characteristics were well balanced. At a mean follow-up time of 97 months, 10-year OS rate was 58.3% in the MBC group and 68.7% in the FBC (log-rank test, P < 0.001; hazard ratio (HR) = 1.45, 95% confidence interval (CI) = 1.29 to 1.64). Adjusted HR for OS between MBC and FBC were revealed from propensity score matched-multivariable Cox proportional hazards models (HR = 1.53, 95% CI = 1.35 to 1.73). Similar adjusted SMRs between MBC and FBC ((SMR = 1.98, 95% CI = 1.83,2.14) for FBC and (SMR = 2.07, 95% CI = 1.88-2.28) for MBC) were observed. The nomogram was constructed for FBC, and predicted probabilities were generally good (C-index = 0.71), whose area under curve is higher than TNM stage classification (0.74 vs 0.62). OS was significantly decreased among early MBC patients compared with FBC, but similar SMRs and its trends by age groups were observed between MBC and FBC except for young patients.

A Potential Prognostic Long Noncoding RNA Signature to Predict Recurrence among ER-positive Breast Cancer Patients Treated with Tamoxifen

Limited predictable long noncoding RNA (lncRNA) signature was reported in tamoxifen resistance among estrogen receptor (ER)-positive breast cancer (BC) patients. The aim of this study was to identify and assess prognostic lncRNA signature to predict recurrence among ER-positive BC patients treated with tamoxifen. Cohorts from Gene Expression Omnibus (GEO) (n = 298) and The Cancer Genome Atlas (TCGA) (n = 160) were defined as training and validation cohort, respectively. BC relapse associated lnRNAs was identify within training cohort, and the predictable value of recurrence was assessed in both cohorts. A total of 11lncRNAs were recognized to be associated with relapse free survival (RFS) of ER-positive BC patients receiving tamoxifen, who were divided into low-risk and high-risk group on basis of relapse risk scores (RRS). Multivariate cox regression analyses revealed that the RRS is an independent prognostic biomarker in the prediction of ER-positive BC patients' survival. GSEA indicated that high-risk group was associated with several signaling pathways in processing of BC recurrence and metastasis such as PI3K-Akt and Wnt signaling. Our 11-lncRNA based classifier is a reliable prognostic and predictive tool for disease relapse in BC patients receiving tamoxifen.

Mortality and recurrence rates among systemically untreated high risk breast cancer patients included in the DBCG 77 trials

BACKGROUND

Following loco-regional treatment for early breast cancer accurate prognostication is essential for communicating benefits of systemic treatment. The aim of this study was to determine time to recurrence and long-term mortality rates in high risk patients according to patient characteristics and subtypes as assigned by immunohistochemistry panels.

PATIENTS AND METHODS

In November 1977 through January 1983, 2862 patients with tumors larger than 5 cm or positive axillary nodes were included in the DBCG 77 trials. Archival tumor tissue from patients randomly assigned to no systemic treatment was analyzed for ER, PR, Ki67, EGFR and HER2. Intrinsic subtypes were defined as follows: Luminal A, ER or PR >0%, HER2-negative, PR >10% and Ki67 < 14%; Luminal B, ER or PR >0%, (PR ≤10% or HER2-positive or Ki67 ≥ 14%); HER2E, ER 0%, PR 0%, HER2 positive; Core basal, ER 0%, PR 0%, HER2 negative and EGFR positive. Multivariate categorical and fractional polynomials (MFP) models were used to construct prognostic subsets by clinicopathologic characteristics.

RESULTS

In a multivariate model, mortality rate was significantly associated with age, tumor size, nodal status, invasion, histological type and grade, as well as subtype classification.

CONCLUSIONS

With 35 years of follow-up, in this population of high-risk patients with no systemic therapy, no subgroup based on a composite prognostic score and/or molecular subtypes could be identified without excess mortality as compared to the background population.